Pandas Tutorial - Top 40 Useful Tricks.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas Tutorial: Top 40 Useful Tricks\n",
    "\n",
    "\n",
    "## PART - 1  ( 1 to 10)\n",
    "1.\tExtracting data with Regular Expression\n",
    "2.\tPandas Pivot Table\n",
    "3.\tPandas cut function, convert continuous to categorical data (wine)\n",
    "4.\tSplit strings to columns, expand\n",
    "5.\tRemove Outliers by  Filtering\n",
    "6.\tHandle missing values with dropna() \n",
    "7.\tPandas Apply Function\n",
    "8.\tPandas set_option for formating, change default max_columns\n",
    "9.\tExtracting Month and Year as separate columns from Pandas Datetime column\n",
    "10.\tPercentage change function in Pandas DataFrame.\n",
    "\n",
    "## PART - 2  ( 11 to 20)\n",
    "11.\tCorrelation Matrix Plot Pandas DataFrame\n",
    "12.\tImport number column as str\n",
    "13.\tRead date column from data as Index in DataFrame.\n",
    "14.\tRead data only specific columns\n",
    "15.\tFind percentage of records with missing values\n",
    "16.\tReading Multiple Files\n",
    "17.\tRearrange Numerical and Categorical Columns\n",
    "18.\tLabel encoding multiple columns\n",
    "19.\tFinding correllation b/w features and target variable\n",
    "20.\tReplace special chars in columns names with underscore\n",
    "\n",
    "\n",
    "## PART - 3  ( 21 to 30)\n",
    "21.\tSelect data with Regular Expression\n",
    "22.\tPandas profiling - Complete EDA\n",
    "23.\tFilter DataFrame by specific row values, using isin()\n",
    "24.\tTilda ~ Operator\n",
    "25.\tPandas read skipinitialspace\n",
    "26.\tScalar filtering with ix\n",
    "27.\tMove column(s) to the begining or end in Pandas DataFrame (Alexander from Stackoverflow)\n",
    "28.\tPandas reading broad charsets\n",
    "29.\tCreate Random DataFrame (numpy students marks)\n",
    "30.\tRandom sample from large data\n",
    "\n",
    "\n",
    "## PART - 4  ( 31 to 40)\n",
    "31.\tPandas Cumulative sum cumsum() function\n",
    "32.\tBest way to loop through DataFrame : for index, row in df.iterrows():\n",
    "33.\tPandas rank\n",
    "34.\tPandas map and applymap\n",
    "35.\tPandas read from Clipboard, useful?\n",
    "36.\tSelect columns by data type select_dtypes\n",
    "37.\treverse row/column\n",
    "38.\tConvert data type of columns\n",
    "39.\tCreate csv Zip file from DataFrame\n",
    "40.\tLoad large dataset in Pandas\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing packages, set data source paths\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "breast_cancer = 'https://raw.githubusercontent.com/datamites/pandas/master/breast_cancer.csv'\n",
    "adult = 'https://raw.githubusercontent.com/datamites/pandas/master/adult10.data'\n",
    "book_price = 'https://raw.githubusercontent.com/datamites/pandas/master/book_price_data.xlsx'\n",
    "book_reviews = 'https://raw.githubusercontent.com/datamites/pandas/master/book_reviews_price.xlsx'\n",
    "hp_costs = 'https://raw.githubusercontent.com/datamites/pandas/master/hp_other_costs.csv'\n",
    "house_price_bangalore = 'https://raw.githubusercontent.com/datamites/pandas/master/house_price_bangalore.csv'\n",
    "mtcars = 'https://raw.githubusercontent.com/datamites/pandas/master/mtcars.csv'\n",
    "mtcars_missing = 'https://raw.githubusercontent.com/datamites/pandas/master/mtcars_missing.csv'\n",
    "wine= 'https://raw.githubusercontent.com/datamites/pandas/master/winequality.csv'\n",
    "sales_returns = 'https://raw.githubusercontent.com/datamites/pandas/master/sales_returns.csv'\n",
    "superstore_orders = 'https://raw.githubusercontent.com/datamites/pandas/master/superstore_orders.csv'\n",
    "car_sales = 'https://raw.githubusercontent.com/datamites/pandas/master/car-sales.csv'\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PART - 1 (1 to 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.    Extracting data with Regular Expression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(13320, 10)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area_type</th>\n",
       "      <th>availability</th>\n",
       "      <th>location</th>\n",
       "      <th>size</th>\n",
       "      <th>society</th>\n",
       "      <th>total_sqft</th>\n",
       "      <th>bath</th>\n",
       "      <th>balcony</th>\n",
       "      <th>other_costs</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>19-Dec</td>\n",
       "      <td>Electronic City Phase II</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>Coomee</td>\n",
       "      <td>1056</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>custom 2.0L reg 1.76L misc 3.7L</td>\n",
       "      <td>39.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Plot  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Chikka Tirupathi</td>\n",
       "      <td>4 Bedroom</td>\n",
       "      <td>Theanmp</td>\n",
       "      <td>2600</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>custom 2.4L reg 5.4L</td>\n",
       "      <td>120.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Uttarahalli</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1440</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>reg 2.79L misc 3.5L</td>\n",
       "      <td>62.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Lingadheeranahalli</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>Soiewre</td>\n",
       "      <td>1521</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>custom 2.5L reg 4.28L pd 1.34L misc 1.6L</td>\n",
       "      <td>95.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Kothanur</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1200</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>reg 2.3L</td>\n",
       "      <td>51.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              area_type   availability                  location       size  \\\n",
       "0  Super built-up  Area         19-Dec  Electronic City Phase II      2 BHK   \n",
       "1            Plot  Area  Ready To Move          Chikka Tirupathi  4 Bedroom   \n",
       "2        Built-up  Area  Ready To Move               Uttarahalli      3 BHK   \n",
       "3  Super built-up  Area  Ready To Move        Lingadheeranahalli      3 BHK   \n",
       "4  Super built-up  Area  Ready To Move                  Kothanur      2 BHK   \n",
       "\n",
       "   society total_sqft  bath  balcony  \\\n",
       "0  Coomee        1056   2.0      1.0   \n",
       "1  Theanmp       2600   5.0      3.0   \n",
       "2      NaN       1440   2.0      3.0   \n",
       "3  Soiewre       1521   3.0      1.0   \n",
       "4      NaN       1200   2.0      1.0   \n",
       "\n",
       "                                 other_costs   price  \n",
       "0            custom 2.0L reg 1.76L misc 3.7L   39.07  \n",
       "1                       custom 2.4L reg 5.4L  120.00  \n",
       "2                        reg 2.79L misc 3.5L   62.00  \n",
       "3  custom 2.5L reg 4.28L pd 1.34L misc 1.6L    95.00  \n",
       "4                                   reg 2.3L   51.00  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(hp_costs)\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area_type</th>\n",
       "      <th>availability</th>\n",
       "      <th>location</th>\n",
       "      <th>size</th>\n",
       "      <th>society</th>\n",
       "      <th>total_sqft</th>\n",
       "      <th>bath</th>\n",
       "      <th>balcony</th>\n",
       "      <th>other_costs</th>\n",
       "      <th>price</th>\n",
       "      <th>other_costs_list</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>19-Dec</td>\n",
       "      <td>Electronic City Phase II</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>Coomee</td>\n",
       "      <td>1056</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>custom 2.0L reg 1.76L misc 3.7L</td>\n",
       "      <td>39.07</td>\n",
       "      <td>[2.0, 1.76, 3.7]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Plot  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Chikka Tirupathi</td>\n",
       "      <td>4 Bedroom</td>\n",
       "      <td>Theanmp</td>\n",
       "      <td>2600</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>custom 2.4L reg 5.4L</td>\n",
       "      <td>120.00</td>\n",
       "      <td>[2.4, 5.4]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Uttarahalli</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1440</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>reg 2.79L misc 3.5L</td>\n",
       "      <td>62.00</td>\n",
       "      <td>[2.79, 3.5]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Lingadheeranahalli</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>Soiewre</td>\n",
       "      <td>1521</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>custom 2.5L reg 4.28L pd 1.34L misc 1.6L</td>\n",
       "      <td>95.00</td>\n",
       "      <td>[2.5, 4.28, 1.34, 1.6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Kothanur</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1200</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>reg 2.3L</td>\n",
       "      <td>51.00</td>\n",
       "      <td>[2.3]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              area_type   availability                  location       size  \\\n",
       "0  Super built-up  Area         19-Dec  Electronic City Phase II      2 BHK   \n",
       "1            Plot  Area  Ready To Move          Chikka Tirupathi  4 Bedroom   \n",
       "2        Built-up  Area  Ready To Move               Uttarahalli      3 BHK   \n",
       "3  Super built-up  Area  Ready To Move        Lingadheeranahalli      3 BHK   \n",
       "4  Super built-up  Area  Ready To Move                  Kothanur      2 BHK   \n",
       "\n",
       "   society total_sqft  bath  balcony  \\\n",
       "0  Coomee        1056   2.0      1.0   \n",
       "1  Theanmp       2600   5.0      3.0   \n",
       "2      NaN       1440   2.0      3.0   \n",
       "3  Soiewre       1521   3.0      1.0   \n",
       "4      NaN       1200   2.0      1.0   \n",
       "\n",
       "                                 other_costs   price        other_costs_list  \n",
       "0            custom 2.0L reg 1.76L misc 3.7L   39.07        [2.0, 1.76, 3.7]  \n",
       "1                       custom 2.4L reg 5.4L  120.00              [2.4, 5.4]  \n",
       "2                        reg 2.79L misc 3.5L   62.00             [2.79, 3.5]  \n",
       "3  custom 2.5L reg 4.28L pd 1.34L misc 1.6L    95.00  [2.5, 4.28, 1.34, 1.6]  \n",
       "4                                   reg 2.3L   51.00                   [2.3]  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['other_costs_list'] =  data.other_costs.str.findall('\\d+.\\d+')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2.0', '1.76', '3.7']"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.other_costs_list[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i,row in data.iterrows():\n",
    "    data.loc[i,'total_cost'] = row.price + sum([float(x) for x in row.other_costs_list])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area_type</th>\n",
       "      <th>availability</th>\n",
       "      <th>location</th>\n",
       "      <th>size</th>\n",
       "      <th>society</th>\n",
       "      <th>total_sqft</th>\n",
       "      <th>bath</th>\n",
       "      <th>balcony</th>\n",
       "      <th>other_costs</th>\n",
       "      <th>price</th>\n",
       "      <th>other_costs_list</th>\n",
       "      <th>total_cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>19-Dec</td>\n",
       "      <td>Electronic City Phase II</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>Coomee</td>\n",
       "      <td>1056</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>custom 2.0L reg 1.76L misc 3.7L</td>\n",
       "      <td>39.07</td>\n",
       "      <td>[2.0, 1.76, 3.7]</td>\n",
       "      <td>46.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Plot  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Chikka Tirupathi</td>\n",
       "      <td>4 Bedroom</td>\n",
       "      <td>Theanmp</td>\n",
       "      <td>2600</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>custom 2.4L reg 5.4L</td>\n",
       "      <td>120.00</td>\n",
       "      <td>[2.4, 5.4]</td>\n",
       "      <td>127.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Uttarahalli</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1440</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>reg 2.79L misc 3.5L</td>\n",
       "      <td>62.00</td>\n",
       "      <td>[2.79, 3.5]</td>\n",
       "      <td>68.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Lingadheeranahalli</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>Soiewre</td>\n",
       "      <td>1521</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>custom 2.5L reg 4.28L pd 1.34L misc 1.6L</td>\n",
       "      <td>95.00</td>\n",
       "      <td>[2.5, 4.28, 1.34, 1.6]</td>\n",
       "      <td>104.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Kothanur</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1200</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>reg 2.3L</td>\n",
       "      <td>51.00</td>\n",
       "      <td>[2.3]</td>\n",
       "      <td>53.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              area_type   availability                  location       size  \\\n",
       "0  Super built-up  Area         19-Dec  Electronic City Phase II      2 BHK   \n",
       "1            Plot  Area  Ready To Move          Chikka Tirupathi  4 Bedroom   \n",
       "2        Built-up  Area  Ready To Move               Uttarahalli      3 BHK   \n",
       "3  Super built-up  Area  Ready To Move        Lingadheeranahalli      3 BHK   \n",
       "4  Super built-up  Area  Ready To Move                  Kothanur      2 BHK   \n",
       "\n",
       "   society total_sqft  bath  balcony  \\\n",
       "0  Coomee        1056   2.0      1.0   \n",
       "1  Theanmp       2600   5.0      3.0   \n",
       "2      NaN       1440   2.0      3.0   \n",
       "3  Soiewre       1521   3.0      1.0   \n",
       "4      NaN       1200   2.0      1.0   \n",
       "\n",
       "                                 other_costs   price        other_costs_list  \\\n",
       "0            custom 2.0L reg 1.76L misc 3.7L   39.07        [2.0, 1.76, 3.7]   \n",
       "1                       custom 2.4L reg 5.4L  120.00              [2.4, 5.4]   \n",
       "2                        reg 2.79L misc 3.5L   62.00             [2.79, 3.5]   \n",
       "3  custom 2.5L reg 4.28L pd 1.34L misc 1.6L    95.00  [2.5, 4.28, 1.34, 1.6]   \n",
       "4                                   reg 2.3L   51.00                   [2.3]   \n",
       "\n",
       "   total_cost  \n",
       "0       46.53  \n",
       "1      127.80  \n",
       "2       68.29  \n",
       "3      104.72  \n",
       "4       53.30  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.\tPandas Pivot Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(9994, 21)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>row_id</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_date</th>\n",
       "      <th>ship_date</th>\n",
       "      <th>ship_mode</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>customer_name</th>\n",
       "      <th>segment</th>\n",
       "      <th>country</th>\n",
       "      <th>city</th>\n",
       "      <th>...</th>\n",
       "      <th>postal_code</th>\n",
       "      <th>region</th>\n",
       "      <th>product_id</th>\n",
       "      <th>category</th>\n",
       "      <th>sub_category</th>\n",
       "      <th>product_name</th>\n",
       "      <th>sales</th>\n",
       "      <th>quantity</th>\n",
       "      <th>discount</th>\n",
       "      <th>profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>CA-2017-152156</td>\n",
       "      <td>2017-11-08</td>\n",
       "      <td>2017-11-11</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>CG-12520</td>\n",
       "      <td>Claire Gute</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>...</td>\n",
       "      <td>42420.0</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-BO-10001798</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Bookcases</td>\n",
       "      <td>Bush Somerset Collection Bookcase</td>\n",
       "      <td>261.9600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.9136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>CA-2017-152156</td>\n",
       "      <td>2017-11-08</td>\n",
       "      <td>2017-11-11</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>CG-12520</td>\n",
       "      <td>Claire Gute</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>...</td>\n",
       "      <td>42420.0</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-CH-10000454</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Chairs</td>\n",
       "      <td>Hon Deluxe Fabric Upholstered Stacking Chairs,...</td>\n",
       "      <td>731.9400</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>219.5820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>CA-2017-138688</td>\n",
       "      <td>2017-06-12</td>\n",
       "      <td>2017-06-16</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>DV-13045</td>\n",
       "      <td>Darrin Van Huff</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>...</td>\n",
       "      <td>90036.0</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-LA-10000240</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Labels</td>\n",
       "      <td>Self-Adhesive Address Labels for Typewriters b...</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.8714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>US-2016-108966</td>\n",
       "      <td>2016-10-11</td>\n",
       "      <td>2016-10-18</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SO-20335</td>\n",
       "      <td>Sean O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>...</td>\n",
       "      <td>33311.0</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-TA-10000577</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Tables</td>\n",
       "      <td>Bretford CR4500 Series Slim Rectangular Table</td>\n",
       "      <td>957.5775</td>\n",
       "      <td>5</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-383.0310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>US-2016-108966</td>\n",
       "      <td>2016-10-11</td>\n",
       "      <td>2016-10-18</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SO-20335</td>\n",
       "      <td>Sean O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>...</td>\n",
       "      <td>33311.0</td>\n",
       "      <td>South</td>\n",
       "      <td>OFF-ST-10000760</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Eldon Fold 'N Roll Cart System</td>\n",
       "      <td>22.3680</td>\n",
       "      <td>2</td>\n",
       "      <td>0.20</td>\n",
       "      <td>2.5164</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   row_id        order_id  order_date   ship_date       ship_mode customer_id  \\\n",
       "0       1  CA-2017-152156  2017-11-08  2017-11-11    Second Class    CG-12520   \n",
       "1       2  CA-2017-152156  2017-11-08  2017-11-11    Second Class    CG-12520   \n",
       "2       3  CA-2017-138688  2017-06-12  2017-06-16    Second Class    DV-13045   \n",
       "3       4  US-2016-108966  2016-10-11  2016-10-18  Standard Class    SO-20335   \n",
       "4       5  US-2016-108966  2016-10-11  2016-10-18  Standard Class    SO-20335   \n",
       "\n",
       "     customer_name    segment        country             city  ...  \\\n",
       "0      Claire Gute   Consumer  United States        Henderson  ...   \n",
       "1      Claire Gute   Consumer  United States        Henderson  ...   \n",
       "2  Darrin Van Huff  Corporate  United States      Los Angeles  ...   \n",
       "3   Sean O'Donnell   Consumer  United States  Fort Lauderdale  ...   \n",
       "4   Sean O'Donnell   Consumer  United States  Fort Lauderdale  ...   \n",
       "\n",
       "  postal_code  region       product_id         category sub_category  \\\n",
       "0     42420.0   South  FUR-BO-10001798        Furniture    Bookcases   \n",
       "1     42420.0   South  FUR-CH-10000454        Furniture       Chairs   \n",
       "2     90036.0    West  OFF-LA-10000240  Office Supplies       Labels   \n",
       "3     33311.0   South  FUR-TA-10000577        Furniture       Tables   \n",
       "4     33311.0   South  OFF-ST-10000760  Office Supplies      Storage   \n",
       "\n",
       "                                        product_name     sales  quantity  \\\n",
       "0                  Bush Somerset Collection Bookcase  261.9600         2   \n",
       "1  Hon Deluxe Fabric Upholstered Stacking Chairs,...  731.9400         3   \n",
       "2  Self-Adhesive Address Labels for Typewriters b...   14.6200         2   \n",
       "3      Bretford CR4500 Series Slim Rectangular Table  957.5775         5   \n",
       "4                     Eldon Fold 'N Roll Cart System   22.3680         2   \n",
       "\n",
       "   discount    profit  \n",
       "0      0.00   41.9136  \n",
       "1      0.00  219.5820  \n",
       "2      0.00    6.8714  \n",
       "3      0.45 -383.0310  \n",
       "4      0.20    2.5164  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(superstore_orders)\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>region</th>\n",
       "      <th>Central</th>\n",
       "      <th>East</th>\n",
       "      <th>South</th>\n",
       "      <th>West</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Furniture</th>\n",
       "      <td>163797.1638</td>\n",
       "      <td>208291.204</td>\n",
       "      <td>117298.684</td>\n",
       "      <td>252612.7435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Office Supplies</th>\n",
       "      <td>167026.4150</td>\n",
       "      <td>205516.055</td>\n",
       "      <td>125651.313</td>\n",
       "      <td>220853.2490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technology</th>\n",
       "      <td>170416.3120</td>\n",
       "      <td>264973.981</td>\n",
       "      <td>148771.908</td>\n",
       "      <td>251991.8320</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "region               Central        East       South         West\n",
       "category                                                         \n",
       "Furniture        163797.1638  208291.204  117298.684  252612.7435\n",
       "Office Supplies  167026.4150  205516.055  125651.313  220853.2490\n",
       "Technology       170416.3120  264973.981  148771.908  251991.8320"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.pivot_table(columns='region', index = 'category', values = 'sales', aggfunc='sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col0 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col1 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col2 {\n",
       "            background-color:  #bcd2f7;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col4 {\n",
       "            background-color:  #96b7ff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col5 {\n",
       "            background-color:  #cad8ef;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col6 {\n",
       "            background-color:  #7597f6;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col7 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col0 {\n",
       "            background-color:  #e6d7cf;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col1 {\n",
       "            background-color:  #f6a283;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col2 {\n",
       "            background-color:  #f6a283;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col3 {\n",
       "            background-color:  #94b6ff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col4 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col5 {\n",
       "            background-color:  #c43032;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col6 {\n",
       "            background-color:  #f29072;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col7 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col1 {\n",
       "            background-color:  #f2cab5;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col2 {\n",
       "            background-color:  #e3d9d3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col3 {\n",
       "            background-color:  #cdd9ec;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col4 {\n",
       "            background-color:  #7093f3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col5 {\n",
       "            background-color:  #98b9ff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col6 {\n",
       "            background-color:  #9bbcff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col7 {\n",
       "            background-color:  #9abbff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col0 {\n",
       "            background-color:  #3f53c6;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col3 {\n",
       "            background-color:  #6a8bef;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col4 {\n",
       "            background-color:  #d1dae9;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col5 {\n",
       "            background-color:  #bbd1f8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col6 {\n",
       "            background-color:  #f4987a;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col7 {\n",
       "            background-color:  #e8765c;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col0 {\n",
       "            background-color:  #4e68d8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col1 {\n",
       "            background-color:  #f7af91;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col2 {\n",
       "            background-color:  #edd2c3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col3 {\n",
       "            background-color:  #d5dbe5;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col4 {\n",
       "            background-color:  #94b6ff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col5 {\n",
       "            background-color:  #aac7fd;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col6 {\n",
       "            background-color:  #a9c6fd;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col7 {\n",
       "            background-color:  #9bbcff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col0 {\n",
       "            background-color:  #90b2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col1 {\n",
       "            background-color:  #d2dbe8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col2 {\n",
       "            background-color:  #b6cefa;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col3 {\n",
       "            background-color:  #799cf8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col4 {\n",
       "            background-color:  #4c66d6;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col5 {\n",
       "            background-color:  #4f69d9;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col6 {\n",
       "            background-color:  #506bda;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col7 {\n",
       "            background-color:  #5470de;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col0 {\n",
       "            background-color:  #688aef;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col1 {\n",
       "            background-color:  #ee8669;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col2 {\n",
       "            background-color:  #ead5c9;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col3 {\n",
       "            background-color:  #e46e56;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col4 {\n",
       "            background-color:  #f7b89c;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col5 {\n",
       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col6 {\n",
       "            background-color:  #f5c2aa;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col7 {\n",
       "            background-color:  #e8d6cc;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col0 {\n",
       "            background-color:  #9bbcff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col1 {\n",
       "            background-color:  #d2dbe8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col2 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col3 {\n",
       "            background-color:  #7093f3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col4 {\n",
       "            background-color:  #485fd1;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col5 {\n",
       "            background-color:  #455cce;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col6 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col7 {\n",
       "            background-color:  #445acc;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col0 {\n",
       "            background-color:  #80a3fa;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col1 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col2 {\n",
       "            background-color:  #a2c1ff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col3 {\n",
       "            background-color:  #5673e0;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col0 {\n",
       "            background-color:  #8fb1fe;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col1 {\n",
       "            background-color:  #cad8ef;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col2 {\n",
       "            background-color:  #b6cefa;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col3 {\n",
       "            background-color:  #779af7;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col4 {\n",
       "            background-color:  #4055c8;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col5 {\n",
       "            background-color:  #3f53c6;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col6 {\n",
       "            background-color:  #445acc;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col7 {\n",
       "            background-color:  #465ecf;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col0 {\n",
       "            background-color:  #ead4c8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col1 {\n",
       "            background-color:  #f7a889;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col2 {\n",
       "            background-color:  #f7b194;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col3 {\n",
       "            background-color:  #f7ba9f;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col4 {\n",
       "            background-color:  #7a9df8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col5 {\n",
       "            background-color:  #799cf8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col6 {\n",
       "            background-color:  #88abfd;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col7 {\n",
       "            background-color:  #8fb1fe;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col0 {\n",
       "            background-color:  #9fbfff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col1 {\n",
       "            background-color:  #f7af91;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col2 {\n",
       "            background-color:  #cedaeb;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col3 {\n",
       "            background-color:  #dadce0;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col4 {\n",
       "            background-color:  #e5d8d1;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col5 {\n",
       "            background-color:  #f7a98b;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col6 {\n",
       "            background-color:  #f3c8b2;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col7 {\n",
       "            background-color:  #f7b093;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col0 {\n",
       "            background-color:  #6f92f3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col1 {\n",
       "            background-color:  #b1cbfc;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col2 {\n",
       "            background-color:  #9ebeff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col3 {\n",
       "            background-color:  #5b7ae5;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col4 {\n",
       "            background-color:  #5a78e4;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col5 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col6 {\n",
       "            background-color:  #6485ec;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col7 {\n",
       "            background-color:  #7093f3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col0 {\n",
       "            background-color:  #edd1c2;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col1 {\n",
       "            background-color:  #ef886b;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col2 {\n",
       "            background-color:  #f39778;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col3 {\n",
       "            background-color:  #e0654f;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col4 {\n",
       "            background-color:  #bed2f6;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col5 {\n",
       "            background-color:  #cdd9ec;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col6 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col7 {\n",
       "            background-color:  #f1ccb8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col0 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col1 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col2 {\n",
       "            background-color:  #e6d7cf;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col3 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col4 {\n",
       "            background-color:  #cad8ef;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col5 {\n",
       "            background-color:  #e3d9d3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col6 {\n",
       "            background-color:  #6a8bef;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col7 {\n",
       "            background-color:  #d8dce2;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col0 {\n",
       "            background-color:  #6180e9;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col1 {\n",
       "            background-color:  #f5c0a7;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col2 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col3 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col4 {\n",
       "            background-color:  #a1c0ff;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col5 {\n",
       "            background-color:  #f7bca1;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col6 {\n",
       "            background-color:  #cf453c;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col7 {\n",
       "            background-color:  #c4d5f3;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col0 {\n",
       "            background-color:  #e8765c;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col1 {\n",
       "            background-color:  #e7745b;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col2 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col3 {\n",
       "            background-color:  #e0dbd8;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col4 {\n",
       "            background-color:  #e36c55;\n",
       "            color:  #000000;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col5 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col6 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col7 {\n",
       "            background-color:  #be242e;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9\" ><thead>    <tr>        <th class=\"blank\" ></th>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" colspan=4>profit</th>        <th class=\"col_heading level0 col4\" colspan=4>sales</th>    </tr>    <tr>        <th class=\"blank\" ></th>        <th class=\"index_name level1\" >region</th>        <th class=\"col_heading level1 col0\" >Central</th>        <th class=\"col_heading level1 col1\" >East</th>        <th class=\"col_heading level1 col2\" >South</th>        <th class=\"col_heading level1 col3\" >West</th>        <th class=\"col_heading level1 col4\" >Central</th>        <th class=\"col_heading level1 col5\" >East</th>        <th class=\"col_heading level1 col6\" >South</th>        <th class=\"col_heading level1 col7\" >West</th>    </tr>    <tr>        <th class=\"index_name level0\" >category</th>        <th class=\"index_name level1\" >sub_category</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level0_row0\" class=\"row_heading level0 row0\" rowspan=4>Furniture</th>\n",
       "                        <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row0\" class=\"row_heading level1 row0\" >Bookcases</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col0\" class=\"data row0 col0\" >-1997.9</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col1\" class=\"data row0 col1\" >-1167.63</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col2\" class=\"data row0 col2\" >1339.49</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col3\" class=\"data row0 col3\" >-1646.51</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col4\" class=\"data row0 col4\" >24157.2</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col5\" class=\"data row0 col5\" >43819.3</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col6\" class=\"data row0 col6\" >10899.4</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row0_col7\" class=\"data row0 col7\" >36004.1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row1\" class=\"row_heading level1 row1\" >Chairs</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col0\" class=\"data row1 col0\" >6592.72</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col1\" class=\"data row1 col1\" >9357.77</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col2\" class=\"data row1 col2\" >6612.09</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col3\" class=\"data row1 col3\" >4027.58</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col4\" class=\"data row1 col4\" >85230.6</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col5\" class=\"data row1 col5\" >96260.7</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col6\" class=\"data row1 col6\" >45176.4</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row1_col7\" class=\"data row1 col7\" >101781</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row2\" class=\"row_heading level1 row2\" >Furnishings</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col0\" class=\"data row2 col0\" >-3906.22</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col1\" class=\"data row2 col1\" >5881.41</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col2\" class=\"data row2 col2\" >3442.68</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col3\" class=\"data row2 col3\" >7641.27</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col4\" class=\"data row2 col4\" >15254.4</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col5\" class=\"data row2 col5\" >29071.4</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col6\" class=\"data row2 col6\" >17306.7</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row2_col7\" class=\"data row2 col7\" >30072.7</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row3\" class=\"row_heading level1 row3\" >Tables</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col0\" class=\"data row3 col0\" >-3559.65</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col1\" class=\"data row3 col1\" >-11025.4</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col2\" class=\"data row3 col2\" >-4623.06</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col3\" class=\"data row3 col3\" >1482.61</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col4\" class=\"data row3 col4\" >39155</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col5\" class=\"data row3 col5\" >39139.8</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col6\" class=\"data row3 col6\" >43916.2</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row3_col7\" class=\"data row3 col7\" >84754.6</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level0_row4\" class=\"row_heading level0 row4\" rowspan=9>Office Supplies</th>\n",
       "                        <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row4\" class=\"row_heading level1 row4\" >Appliances</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col0\" class=\"data row4 col0\" >-2638.62</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col1\" class=\"data row4 col1\" >8391.41</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col2\" class=\"data row4 col2\" >4123.94</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col3\" class=\"data row4 col3\" >8261.27</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col4\" class=\"data row4 col4\" >23582</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col5\" class=\"data row4 col5\" >34188.5</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col6\" class=\"data row4 col6\" >19525.3</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row4_col7\" class=\"data row4 col7\" >30236.3</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row5\" class=\"row_heading level1 row5\" >Art</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col0\" class=\"data row5 col0\" >1195.16</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col1\" class=\"data row5 col1\" >1899.94</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col2\" class=\"data row5 col2\" >1058.59</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col3\" class=\"data row5 col3\" >2374.1</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col4\" class=\"data row5 col4\" >5765.34</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col5\" class=\"data row5 col5\" >7485.76</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col6\" class=\"data row5 col6\" >4655.62</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row5_col7\" class=\"data row5 col7\" >9212.07</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row6\" class=\"row_heading level1 row6\" >Binders</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col0\" class=\"data row6 col0\" >-1043.64</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col1\" class=\"data row6 col1\" >11267.9</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col2\" class=\"data row6 col2\" >3900.66</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col3\" class=\"data row6 col3\" >16096.8</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col4\" class=\"data row6 col4\" >56923.3</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col5\" class=\"data row6 col5\" >53498</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col6\" class=\"data row6 col6\" >37030.3</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row6_col7\" class=\"data row6 col7\" >55961.1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row7\" class=\"row_heading level1 row7\" >Envelopes</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col0\" class=\"data row7 col0\" >1777.53</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col1\" class=\"data row7 col1\" >1812.41</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col2\" class=\"data row7 col2\" >1465.48</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col3\" class=\"data row7 col3\" >1908.76</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col4\" class=\"data row7 col4\" >4636.87</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col5\" class=\"data row7 col5\" >4375.87</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col6\" class=\"data row7 col6\" >3345.56</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row7_col7\" class=\"data row7 col7\" >4118.1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row8\" class=\"row_heading level1 row8\" >Fasteners</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col0\" class=\"data row8 col0\" >236.619</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col1\" class=\"data row8 col1\" >263.991</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col2\" class=\"data row8 col2\" >173.718</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col3\" class=\"data row8 col3\" >275.191</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col4\" class=\"data row8 col4\" >778.03</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col5\" class=\"data row8 col5\" >819.718</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col6\" class=\"data row8 col6\" >503.316</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row8_col7\" class=\"data row8 col7\" >923.216</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row9\" class=\"row_heading level1 row9\" >Labels</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col0\" class=\"data row9 col0\" >1073.08</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col1\" class=\"data row9 col1\" >1129.28</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col2\" class=\"data row9 col2\" >1040.77</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col3\" class=\"data row9 col3\" >2303.12</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col4\" class=\"data row9 col4\" >2451.47</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col5\" class=\"data row9 col5\" >2602.93</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col6\" class=\"data row9 col6\" >2353.18</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row9_col7\" class=\"data row9 col7\" >5078.73</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row10\" class=\"row_heading level1 row10\" >Paper</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col0\" class=\"data row10 col0\" >6971.9</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col1\" class=\"data row10 col1\" >9015.37</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col2\" class=\"data row10 col2\" >5947.06</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col3\" class=\"data row10 col3\" >12119.2</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col4\" class=\"data row10 col4\" >17491.9</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col5\" class=\"data row10 col5\" >20172.6</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col6\" class=\"data row10 col6\" >14151</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row10_col7\" class=\"data row10 col7\" >26663.7</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row11\" class=\"row_heading level1 row11\" >Storage</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col0\" class=\"data row11 col0\" >1969.84</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col1\" class=\"data row11 col1\" >8389.37</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col2\" class=\"data row11 col2\" >2274.3</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col3\" class=\"data row11 col3\" >8645.32</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col4\" class=\"data row11 col4\" >45930.1</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col5\" class=\"data row11 col5\" >71612.6</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col6\" class=\"data row11 col6\" >35768.1</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row11_col7\" class=\"data row11 col7\" >70532.9</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row12\" class=\"row_heading level1 row12\" >Supplies</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col0\" class=\"data row12 col0\" >-661.888</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col1\" class=\"data row12 col1\" >-1155.14</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col2\" class=\"data row12 col2\" >1.8773</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col3\" class=\"data row12 col3\" >626.046</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col4\" class=\"data row12 col4\" >9467.37</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col5\" class=\"data row12 col5\" >10760.1</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col6\" class=\"data row12 col6\" >8318.93</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row12_col7\" class=\"data row12 col7\" >18127.1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level0_row13\" class=\"row_heading level0 row13\" rowspan=4>Technology</th>\n",
       "                        <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row13\" class=\"row_heading level1 row13\" >Accessories</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col0\" class=\"data row13 col0\" >7251.63</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col1\" class=\"data row13 col1\" >11195.9</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col2\" class=\"data row13 col2\" >7004.54</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col3\" class=\"data row13 col3\" >16484.6</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col4\" class=\"data row13 col4\" >33956.1</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col5\" class=\"data row13 col5\" >45033.4</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col6\" class=\"data row13 col6\" >27276.8</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row13_col7\" class=\"data row13 col7\" >61114.1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row14\" class=\"row_heading level1 row14\" >Copiers</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col0\" class=\"data row14 col0\" >15608.8</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col1\" class=\"data row14 col1\" >17022.8</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col2\" class=\"data row14 col2\" >3658.91</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col3\" class=\"data row14 col3\" >19327.2</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col4\" class=\"data row14 col4\" >37259.6</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col5\" class=\"data row14 col5\" >53219.5</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col6\" class=\"data row14 col6\" >9299.76</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row14_col7\" class=\"data row14 col7\" >49749.2</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row15\" class=\"row_heading level1 row15\" >Machines</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col0\" class=\"data row15 col0\" >-1486.07</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col1\" class=\"data row15 col1\" >6928.64</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col2\" class=\"data row15 col2\" >-1438.89</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col3\" class=\"data row15 col3\" >-618.926</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col4\" class=\"data row15 col4\" >26797.4</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col5\" class=\"data row15 col5\" >66106.2</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col6\" class=\"data row15 col6\" >53891</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row15_col7\" class=\"data row15 col7\" >42444.1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <th id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9level1_row16\" class=\"row_heading level1 row16\" >Phones</th>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col0\" class=\"data row16 col0\" >12323</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col1\" class=\"data row16 col1\" >12314.7</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col2\" class=\"data row16 col2\" >10767.3</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col3\" class=\"data row16 col3\" >9110.74</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col4\" class=\"data row16 col4\" >72403.3</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col5\" class=\"data row16 col5\" >100615</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col6\" class=\"data row16 col6\" >58304.4</td>\n",
       "                        <td id=\"T_7d87f888_5e56_11eb_b499_a683e79d3fb9row16_col7\" class=\"data row16 col7\" >98684.4</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fa669a715f8>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.pivot_table(columns='region', index = ['category','sub_category'], values = ['sales','profit'], aggfunc='sum').style.background_gradient(cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.\tPandas cut method, continuous to categorical data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4898, 12)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fixed-acidity</th>\n",
       "      <th>volatile-acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.36</td>\n",
       "      <td>20.7</td>\n",
       "      <td>0.045</td>\n",
       "      <td>45.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1.0010</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.45</td>\n",
       "      <td>8.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.34</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.049</td>\n",
       "      <td>14.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.9940</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9.5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.9</td>\n",
       "      <td>0.050</td>\n",
       "      <td>30.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>0.9951</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.44</td>\n",
       "      <td>10.1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fixed-acidity  volatile-acidity  citric acid  residual sugar  chlorides  \\\n",
       "0            7.0              0.27         0.36            20.7      0.045   \n",
       "1            6.3              0.30         0.34             1.6      0.049   \n",
       "2            8.1              0.28         0.40             6.9      0.050   \n",
       "3            7.2              0.23         0.32             8.5      0.058   \n",
       "4            7.2              0.23         0.32             8.5      0.058   \n",
       "\n",
       "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "0                 45.0                 170.0   1.0010  3.00       0.45   \n",
       "1                 14.0                 132.0   0.9940  3.30       0.49   \n",
       "2                 30.0                  97.0   0.9951  3.26       0.44   \n",
       "3                 47.0                 186.0   0.9956  3.19       0.40   \n",
       "4                 47.0                 186.0   0.9956  3.19       0.40   \n",
       "\n",
       "   alcohol  quality  \n",
       "0      8.8        6  \n",
       "1      9.5        6  \n",
       "2     10.1        6  \n",
       "3      9.9        6  \n",
       "4      9.9        6  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(wine, delimiter=';')\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6    2198\n",
       "5    1457\n",
       "7     880\n",
       "8     175\n",
       "4     163\n",
       "3      20\n",
       "9       5\n",
       "Name: quality, dtype: int64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.quality.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['quality_cat'] = pd.cut(data.quality, bins=[0,5,7,10],labels = ['bad','good','premium'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fixed-acidity</th>\n",
       "      <th>volatile-acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "      <th>quality_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.36</td>\n",
       "      <td>20.70</td>\n",
       "      <td>0.045</td>\n",
       "      <td>45.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1.0010</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.45</td>\n",
       "      <td>8.8</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.34</td>\n",
       "      <td>1.60</td>\n",
       "      <td>0.049</td>\n",
       "      <td>14.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.9940</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9.5</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.90</td>\n",
       "      <td>0.050</td>\n",
       "      <td>30.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>0.9951</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.44</td>\n",
       "      <td>10.1</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.50</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.50</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.90</td>\n",
       "      <td>0.050</td>\n",
       "      <td>30.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>0.9951</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.44</td>\n",
       "      <td>10.1</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6.2</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.16</td>\n",
       "      <td>7.00</td>\n",
       "      <td>0.045</td>\n",
       "      <td>30.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>0.9949</td>\n",
       "      <td>3.18</td>\n",
       "      <td>0.47</td>\n",
       "      <td>9.6</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.36</td>\n",
       "      <td>20.70</td>\n",
       "      <td>0.045</td>\n",
       "      <td>45.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1.0010</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.45</td>\n",
       "      <td>8.8</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.34</td>\n",
       "      <td>1.60</td>\n",
       "      <td>0.049</td>\n",
       "      <td>14.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.9940</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9.5</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.43</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.044</td>\n",
       "      <td>28.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>0.9938</td>\n",
       "      <td>3.22</td>\n",
       "      <td>0.45</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.41</td>\n",
       "      <td>1.45</td>\n",
       "      <td>0.033</td>\n",
       "      <td>11.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>0.9908</td>\n",
       "      <td>2.99</td>\n",
       "      <td>0.56</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>8.6</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.40</td>\n",
       "      <td>4.20</td>\n",
       "      <td>0.035</td>\n",
       "      <td>17.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>0.9947</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.53</td>\n",
       "      <td>9.7</td>\n",
       "      <td>5</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>7.9</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.37</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.040</td>\n",
       "      <td>16.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.9920</td>\n",
       "      <td>3.18</td>\n",
       "      <td>0.63</td>\n",
       "      <td>10.8</td>\n",
       "      <td>5</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>6.6</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.40</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.044</td>\n",
       "      <td>48.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>0.9912</td>\n",
       "      <td>3.54</td>\n",
       "      <td>0.52</td>\n",
       "      <td>12.4</td>\n",
       "      <td>7</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8.3</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.62</td>\n",
       "      <td>19.25</td>\n",
       "      <td>0.040</td>\n",
       "      <td>41.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>1.0002</td>\n",
       "      <td>2.98</td>\n",
       "      <td>0.67</td>\n",
       "      <td>9.7</td>\n",
       "      <td>5</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>6.6</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.38</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.032</td>\n",
       "      <td>28.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>0.9914</td>\n",
       "      <td>3.25</td>\n",
       "      <td>0.55</td>\n",
       "      <td>11.4</td>\n",
       "      <td>7</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.04</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.046</td>\n",
       "      <td>30.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>0.9928</td>\n",
       "      <td>3.24</td>\n",
       "      <td>0.36</td>\n",
       "      <td>9.6</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>6.2</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.48</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.029</td>\n",
       "      <td>29.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.9892</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.39</td>\n",
       "      <td>12.8</td>\n",
       "      <td>8</td>\n",
       "      <td>premium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.42</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.033</td>\n",
       "      <td>17.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>0.9917</td>\n",
       "      <td>3.12</td>\n",
       "      <td>0.53</td>\n",
       "      <td>11.3</td>\n",
       "      <td>6</td>\n",
       "      <td>good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>6.5</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.14</td>\n",
       "      <td>7.50</td>\n",
       "      <td>0.044</td>\n",
       "      <td>34.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>0.9955</td>\n",
       "      <td>3.22</td>\n",
       "      <td>0.50</td>\n",
       "      <td>9.5</td>\n",
       "      <td>5</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    fixed-acidity  volatile-acidity  citric acid  residual sugar  chlorides  \\\n",
       "0             7.0              0.27         0.36           20.70      0.045   \n",
       "1             6.3              0.30         0.34            1.60      0.049   \n",
       "2             8.1              0.28         0.40            6.90      0.050   \n",
       "3             7.2              0.23         0.32            8.50      0.058   \n",
       "4             7.2              0.23         0.32            8.50      0.058   \n",
       "5             8.1              0.28         0.40            6.90      0.050   \n",
       "6             6.2              0.32         0.16            7.00      0.045   \n",
       "7             7.0              0.27         0.36           20.70      0.045   \n",
       "8             6.3              0.30         0.34            1.60      0.049   \n",
       "9             8.1              0.22         0.43            1.50      0.044   \n",
       "10            8.1              0.27         0.41            1.45      0.033   \n",
       "11            8.6              0.23         0.40            4.20      0.035   \n",
       "12            7.9              0.18         0.37            1.20      0.040   \n",
       "13            6.6              0.16         0.40            1.50      0.044   \n",
       "14            8.3              0.42         0.62           19.25      0.040   \n",
       "15            6.6              0.17         0.38            1.50      0.032   \n",
       "16            6.3              0.48         0.04            1.10      0.046   \n",
       "17            6.2              0.66         0.48            1.20      0.029   \n",
       "18            7.4              0.34         0.42            1.10      0.033   \n",
       "19            6.5              0.31         0.14            7.50      0.044   \n",
       "\n",
       "    free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "0                  45.0                 170.0   1.0010  3.00       0.45   \n",
       "1                  14.0                 132.0   0.9940  3.30       0.49   \n",
       "2                  30.0                  97.0   0.9951  3.26       0.44   \n",
       "3                  47.0                 186.0   0.9956  3.19       0.40   \n",
       "4                  47.0                 186.0   0.9956  3.19       0.40   \n",
       "5                  30.0                  97.0   0.9951  3.26       0.44   \n",
       "6                  30.0                 136.0   0.9949  3.18       0.47   \n",
       "7                  45.0                 170.0   1.0010  3.00       0.45   \n",
       "8                  14.0                 132.0   0.9940  3.30       0.49   \n",
       "9                  28.0                 129.0   0.9938  3.22       0.45   \n",
       "10                 11.0                  63.0   0.9908  2.99       0.56   \n",
       "11                 17.0                 109.0   0.9947  3.14       0.53   \n",
       "12                 16.0                  75.0   0.9920  3.18       0.63   \n",
       "13                 48.0                 143.0   0.9912  3.54       0.52   \n",
       "14                 41.0                 172.0   1.0002  2.98       0.67   \n",
       "15                 28.0                 112.0   0.9914  3.25       0.55   \n",
       "16                 30.0                  99.0   0.9928  3.24       0.36   \n",
       "17                 29.0                  75.0   0.9892  3.33       0.39   \n",
       "18                 17.0                 171.0   0.9917  3.12       0.53   \n",
       "19                 34.0                 133.0   0.9955  3.22       0.50   \n",
       "\n",
       "    alcohol  quality quality_cat  \n",
       "0       8.8        6        good  \n",
       "1       9.5        6        good  \n",
       "2      10.1        6        good  \n",
       "3       9.9        6        good  \n",
       "4       9.9        6        good  \n",
       "5      10.1        6        good  \n",
       "6       9.6        6        good  \n",
       "7       8.8        6        good  \n",
       "8       9.5        6        good  \n",
       "9      11.0        6        good  \n",
       "10     12.0        5         bad  \n",
       "11      9.7        5         bad  \n",
       "12     10.8        5         bad  \n",
       "13     12.4        7        good  \n",
       "14      9.7        5         bad  \n",
       "15     11.4        7        good  \n",
       "16      9.6        6        good  \n",
       "17     12.8        8     premium  \n",
       "18     11.3        6        good  \n",
       "19      9.5        5         bad  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.\tSplit strings to columns, expand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100, 8)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Author</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Synopsis</th>\n",
       "      <th>Genre</th>\n",
       "      <th>BookCategory</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>The Prisoner's Gold (The Hunters 3)</td>\n",
       "      <td>Chris Kuzneski</td>\n",
       "      <td>4.0 out of 5 stars</td>\n",
       "      <td>8 customer reviews</td>\n",
       "      <td>THE HUNTERS return in their third brilliant no...</td>\n",
       "      <td>Action &amp; Adventure (Books)</td>\n",
       "      <td>Action &amp; Adventure</td>\n",
       "      <td>220.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Guru Dutt: A Tragedy in Three Acts</td>\n",
       "      <td>Arun Khopkar</td>\n",
       "      <td>3.9 out of 5 stars</td>\n",
       "      <td>14 customer reviews</td>\n",
       "      <td>A layered portrait of a troubled genius for wh...</td>\n",
       "      <td>Cinema &amp; Broadcast (Books)</td>\n",
       "      <td>Biographies, Diaries &amp; True Accounts</td>\n",
       "      <td>202.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leviathan (Penguin Classics)</td>\n",
       "      <td>Thomas Hobbes</td>\n",
       "      <td>9.6 out of 10 stars</td>\n",
       "      <td>6 customer reviews</td>\n",
       "      <td>\"During the time men live without a common Pow...</td>\n",
       "      <td>International Relations</td>\n",
       "      <td>Humour</td>\n",
       "      <td>299.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A Pocket Full of Rye (Miss Marple)</td>\n",
       "      <td>Agatha Christie</td>\n",
       "      <td>8.2 out of 10 stars</td>\n",
       "      <td>13 customer reviews</td>\n",
       "      <td>A handful of grain is found in the pocket of a...</td>\n",
       "      <td>Contemporary Fiction (Books)</td>\n",
       "      <td>Crime, Thriller &amp; Mystery</td>\n",
       "      <td>180.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ChiRunning: A Revolutionary Approach to Effort...</td>\n",
       "      <td>Danny Dreyer</td>\n",
       "      <td>4.5 out of 5 stars</td>\n",
       "      <td>8 customer reviews</td>\n",
       "      <td>The revised edition of the bestselling ChiRunn...</td>\n",
       "      <td>Healthy Living &amp; Wellness (Books)</td>\n",
       "      <td>Sports</td>\n",
       "      <td>900.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Title           Author  \\\n",
       "0                The Prisoner's Gold (The Hunters 3)   Chris Kuzneski   \n",
       "1                 Guru Dutt: A Tragedy in Three Acts     Arun Khopkar   \n",
       "2                       Leviathan (Penguin Classics)    Thomas Hobbes   \n",
       "3                 A Pocket Full of Rye (Miss Marple)  Agatha Christie   \n",
       "4  ChiRunning: A Revolutionary Approach to Effort...     Danny Dreyer   \n",
       "\n",
       "               Reviews              Ratings  \\\n",
       "0   4.0 out of 5 stars   8 customer reviews   \n",
       "1   3.9 out of 5 stars  14 customer reviews   \n",
       "2  9.6 out of 10 stars   6 customer reviews   \n",
       "3  8.2 out of 10 stars  13 customer reviews   \n",
       "4   4.5 out of 5 stars   8 customer reviews   \n",
       "\n",
       "                                            Synopsis  \\\n",
       "0  THE HUNTERS return in their third brilliant no...   \n",
       "1  A layered portrait of a troubled genius for wh...   \n",
       "2  \"During the time men live without a common Pow...   \n",
       "3  A handful of grain is found in the pocket of a...   \n",
       "4  The revised edition of the bestselling ChiRunn...   \n",
       "\n",
       "                               Genre                          BookCategory  \\\n",
       "0         Action & Adventure (Books)                    Action & Adventure   \n",
       "1         Cinema & Broadcast (Books)  Biographies, Diaries & True Accounts   \n",
       "2            International Relations                                Humour   \n",
       "3       Contemporary Fiction (Books)             Crime, Thriller & Mystery   \n",
       "4  Healthy Living & Wellness (Books)                                Sports   \n",
       "\n",
       "    Price  \n",
       "0  220.00  \n",
       "1  202.93  \n",
       "2  299.00  \n",
       "3  180.00  \n",
       "4  900.00  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_excel(book_reviews)\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Author</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Synopsis</th>\n",
       "      <th>Genre</th>\n",
       "      <th>BookCategory</th>\n",
       "      <th>Price</th>\n",
       "      <th>Author_Firstname</th>\n",
       "      <th>Author_Lastname</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>The Prisoner's Gold (The Hunters 3)</td>\n",
       "      <td>Chris Kuzneski</td>\n",
       "      <td>4.0 out of 5 stars</td>\n",
       "      <td>8 customer reviews</td>\n",
       "      <td>THE HUNTERS return in their third brilliant no...</td>\n",
       "      <td>Action &amp; Adventure (Books)</td>\n",
       "      <td>Action &amp; Adventure</td>\n",
       "      <td>220.00</td>\n",
       "      <td>Chris</td>\n",
       "      <td>Kuzneski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Guru Dutt: A Tragedy in Three Acts</td>\n",
       "      <td>Arun Khopkar</td>\n",
       "      <td>3.9 out of 5 stars</td>\n",
       "      <td>14 customer reviews</td>\n",
       "      <td>A layered portrait of a troubled genius for wh...</td>\n",
       "      <td>Cinema &amp; Broadcast (Books)</td>\n",
       "      <td>Biographies, Diaries &amp; True Accounts</td>\n",
       "      <td>202.93</td>\n",
       "      <td>Arun</td>\n",
       "      <td>Khopkar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leviathan (Penguin Classics)</td>\n",
       "      <td>Thomas Hobbes</td>\n",
       "      <td>9.6 out of 10 stars</td>\n",
       "      <td>6 customer reviews</td>\n",
       "      <td>\"During the time men live without a common Pow...</td>\n",
       "      <td>International Relations</td>\n",
       "      <td>Humour</td>\n",
       "      <td>299.00</td>\n",
       "      <td>Thomas</td>\n",
       "      <td>Hobbes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A Pocket Full of Rye (Miss Marple)</td>\n",
       "      <td>Agatha Christie</td>\n",
       "      <td>8.2 out of 10 stars</td>\n",
       "      <td>13 customer reviews</td>\n",
       "      <td>A handful of grain is found in the pocket of a...</td>\n",
       "      <td>Contemporary Fiction (Books)</td>\n",
       "      <td>Crime, Thriller &amp; Mystery</td>\n",
       "      <td>180.00</td>\n",
       "      <td>Agatha</td>\n",
       "      <td>Christie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ChiRunning: A Revolutionary Approach to Effort...</td>\n",
       "      <td>Danny Dreyer</td>\n",
       "      <td>4.5 out of 5 stars</td>\n",
       "      <td>8 customer reviews</td>\n",
       "      <td>The revised edition of the bestselling ChiRunn...</td>\n",
       "      <td>Healthy Living &amp; Wellness (Books)</td>\n",
       "      <td>Sports</td>\n",
       "      <td>900.00</td>\n",
       "      <td>Danny</td>\n",
       "      <td>Dreyer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Title           Author  \\\n",
       "0                The Prisoner's Gold (The Hunters 3)   Chris Kuzneski   \n",
       "1                 Guru Dutt: A Tragedy in Three Acts     Arun Khopkar   \n",
       "2                       Leviathan (Penguin Classics)    Thomas Hobbes   \n",
       "3                 A Pocket Full of Rye (Miss Marple)  Agatha Christie   \n",
       "4  ChiRunning: A Revolutionary Approach to Effort...     Danny Dreyer   \n",
       "\n",
       "               Reviews              Ratings  \\\n",
       "0   4.0 out of 5 stars   8 customer reviews   \n",
       "1   3.9 out of 5 stars  14 customer reviews   \n",
       "2  9.6 out of 10 stars   6 customer reviews   \n",
       "3  8.2 out of 10 stars  13 customer reviews   \n",
       "4   4.5 out of 5 stars   8 customer reviews   \n",
       "\n",
       "                                            Synopsis  \\\n",
       "0  THE HUNTERS return in their third brilliant no...   \n",
       "1  A layered portrait of a troubled genius for wh...   \n",
       "2  \"During the time men live without a common Pow...   \n",
       "3  A handful of grain is found in the pocket of a...   \n",
       "4  The revised edition of the bestselling ChiRunn...   \n",
       "\n",
       "                               Genre                          BookCategory  \\\n",
       "0         Action & Adventure (Books)                    Action & Adventure   \n",
       "1         Cinema & Broadcast (Books)  Biographies, Diaries & True Accounts   \n",
       "2            International Relations                                Humour   \n",
       "3       Contemporary Fiction (Books)             Crime, Thriller & Mystery   \n",
       "4  Healthy Living & Wellness (Books)                                Sports   \n",
       "\n",
       "    Price Author_Firstname Author_Lastname  \n",
       "0  220.00            Chris        Kuzneski  \n",
       "1  202.93             Arun         Khopkar  \n",
       "2  299.00           Thomas          Hobbes  \n",
       "3  180.00           Agatha        Christie  \n",
       "4  900.00            Danny          Dreyer  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Author_Firstname'] = data.Author.str.split(\" \",n=1,expand=True)[0]\n",
    "data['Author_Lastname'] = data.Author.str.split(\" \",n=1,expand=True)[1]\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Reviews_percent'] = 100*data.Reviews.str.split(\" \",expand=True)[0].astype('float')/data.Reviews.str.split(\" \",expand=True)[3].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Author</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Synopsis</th>\n",
       "      <th>Genre</th>\n",
       "      <th>BookCategory</th>\n",
       "      <th>Price</th>\n",
       "      <th>Author_Firstname</th>\n",
       "      <th>Author_Lastname</th>\n",
       "      <th>Reviews_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>The Prisoner's Gold (The Hunters 3)</td>\n",
       "      <td>Chris Kuzneski</td>\n",
       "      <td>4.0 out of 5 stars</td>\n",
       "      <td>8 customer reviews</td>\n",
       "      <td>THE HUNTERS return in their third brilliant no...</td>\n",
       "      <td>Action &amp; Adventure (Books)</td>\n",
       "      <td>Action &amp; Adventure</td>\n",
       "      <td>220.00</td>\n",
       "      <td>Chris</td>\n",
       "      <td>Kuzneski</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Guru Dutt: A Tragedy in Three Acts</td>\n",
       "      <td>Arun Khopkar</td>\n",
       "      <td>3.9 out of 5 stars</td>\n",
       "      <td>14 customer reviews</td>\n",
       "      <td>A layered portrait of a troubled genius for wh...</td>\n",
       "      <td>Cinema &amp; Broadcast (Books)</td>\n",
       "      <td>Biographies, Diaries &amp; True Accounts</td>\n",
       "      <td>202.93</td>\n",
       "      <td>Arun</td>\n",
       "      <td>Khopkar</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leviathan (Penguin Classics)</td>\n",
       "      <td>Thomas Hobbes</td>\n",
       "      <td>9.6 out of 10 stars</td>\n",
       "      <td>6 customer reviews</td>\n",
       "      <td>\"During the time men live without a common Pow...</td>\n",
       "      <td>International Relations</td>\n",
       "      <td>Humour</td>\n",
       "      <td>299.00</td>\n",
       "      <td>Thomas</td>\n",
       "      <td>Hobbes</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A Pocket Full of Rye (Miss Marple)</td>\n",
       "      <td>Agatha Christie</td>\n",
       "      <td>8.2 out of 10 stars</td>\n",
       "      <td>13 customer reviews</td>\n",
       "      <td>A handful of grain is found in the pocket of a...</td>\n",
       "      <td>Contemporary Fiction (Books)</td>\n",
       "      <td>Crime, Thriller &amp; Mystery</td>\n",
       "      <td>180.00</td>\n",
       "      <td>Agatha</td>\n",
       "      <td>Christie</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ChiRunning: A Revolutionary Approach to Effort...</td>\n",
       "      <td>Danny Dreyer</td>\n",
       "      <td>4.5 out of 5 stars</td>\n",
       "      <td>8 customer reviews</td>\n",
       "      <td>The revised edition of the bestselling ChiRunn...</td>\n",
       "      <td>Healthy Living &amp; Wellness (Books)</td>\n",
       "      <td>Sports</td>\n",
       "      <td>900.00</td>\n",
       "      <td>Danny</td>\n",
       "      <td>Dreyer</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Title           Author  \\\n",
       "0                The Prisoner's Gold (The Hunters 3)   Chris Kuzneski   \n",
       "1                 Guru Dutt: A Tragedy in Three Acts     Arun Khopkar   \n",
       "2                       Leviathan (Penguin Classics)    Thomas Hobbes   \n",
       "3                 A Pocket Full of Rye (Miss Marple)  Agatha Christie   \n",
       "4  ChiRunning: A Revolutionary Approach to Effort...     Danny Dreyer   \n",
       "\n",
       "               Reviews              Ratings  \\\n",
       "0   4.0 out of 5 stars   8 customer reviews   \n",
       "1   3.9 out of 5 stars  14 customer reviews   \n",
       "2  9.6 out of 10 stars   6 customer reviews   \n",
       "3  8.2 out of 10 stars  13 customer reviews   \n",
       "4   4.5 out of 5 stars   8 customer reviews   \n",
       "\n",
       "                                            Synopsis  \\\n",
       "0  THE HUNTERS return in their third brilliant no...   \n",
       "1  A layered portrait of a troubled genius for wh...   \n",
       "2  \"During the time men live without a common Pow...   \n",
       "3  A handful of grain is found in the pocket of a...   \n",
       "4  The revised edition of the bestselling ChiRunn...   \n",
       "\n",
       "                               Genre                          BookCategory  \\\n",
       "0         Action & Adventure (Books)                    Action & Adventure   \n",
       "1         Cinema & Broadcast (Books)  Biographies, Diaries & True Accounts   \n",
       "2            International Relations                                Humour   \n",
       "3       Contemporary Fiction (Books)             Crime, Thriller & Mystery   \n",
       "4  Healthy Living & Wellness (Books)                                Sports   \n",
       "\n",
       "    Price Author_Firstname Author_Lastname  Reviews_percent  \n",
       "0  220.00            Chris        Kuzneski             80.0  \n",
       "1  202.93             Arun         Khopkar             78.0  \n",
       "2  299.00           Thomas          Hobbes             96.0  \n",
       "3  180.00           Agatha        Christie             82.0  \n",
       "4  900.00            Danny          Dreyer             90.0  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.\tRemove Outliers by  Filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(32, 12)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_model</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.620</td>\n",
       "      <td>16.46</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mazda RX4 Wag</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.875</td>\n",
       "      <td>17.02</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>108.0</td>\n",
       "      <td>93</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.320</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hornet 4 Drive</td>\n",
       "      <td>21.4</td>\n",
       "      <td>6</td>\n",
       "      <td>258.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.215</td>\n",
       "      <td>19.44</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hornet Sportabout</td>\n",
       "      <td>18.7</td>\n",
       "      <td>8</td>\n",
       "      <td>360.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.15</td>\n",
       "      <td>3.440</td>\n",
       "      <td>17.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           car_model   mpg  cyl   disp   hp  drat     wt   qsec  vs  am  gear  \\\n",
       "0          Mazda RX4  21.0    6  160.0  110  3.90  2.620  16.46   0   1     4   \n",
       "1      Mazda RX4 Wag  21.0    6  160.0  110  3.90  2.875  17.02   0   1     4   \n",
       "2         Datsun 710  22.8    4  108.0   93  3.85  2.320  18.61   1   1     4   \n",
       "3     Hornet 4 Drive  21.4    6  258.0  110  3.08  3.215  19.44   1   0     3   \n",
       "4  Hornet Sportabout  18.7    8  360.0  175  3.15  3.440  17.02   0   0     3   \n",
       "\n",
       "   carb  \n",
       "0     4  \n",
       "1     4  \n",
       "2     1  \n",
       "3     1  \n",
       "4     2  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(mtcars)\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_model</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.620</td>\n",
       "      <td>16.46</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mazda RX4 Wag</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.875</td>\n",
       "      <td>17.02</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>108.0</td>\n",
       "      <td>93</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.320</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hornet 4 Drive</td>\n",
       "      <td>21.4</td>\n",
       "      <td>6</td>\n",
       "      <td>258.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.215</td>\n",
       "      <td>19.44</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hornet Sportabout</td>\n",
       "      <td>18.7</td>\n",
       "      <td>8</td>\n",
       "      <td>360.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.15</td>\n",
       "      <td>3.440</td>\n",
       "      <td>17.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Valiant</td>\n",
       "      <td>18.1</td>\n",
       "      <td>6</td>\n",
       "      <td>225.0</td>\n",
       "      <td>105</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.460</td>\n",
       "      <td>20.22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Duster 360</td>\n",
       "      <td>14.3</td>\n",
       "      <td>8</td>\n",
       "      <td>360.0</td>\n",
       "      <td>245</td>\n",
       "      <td>3.21</td>\n",
       "      <td>3.570</td>\n",
       "      <td>15.84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Merc 240D</td>\n",
       "      <td>24.4</td>\n",
       "      <td>4</td>\n",
       "      <td>146.7</td>\n",
       "      <td>62</td>\n",
       "      <td>3.69</td>\n",
       "      <td>3.190</td>\n",
       "      <td>20.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Merc 230</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>140.8</td>\n",
       "      <td>95</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.150</td>\n",
       "      <td>22.90</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Merc 280</td>\n",
       "      <td>19.2</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.440</td>\n",
       "      <td>18.30</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Merc 280C</td>\n",
       "      <td>17.8</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.440</td>\n",
       "      <td>18.90</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Merc 450SE</td>\n",
       "      <td>16.4</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180</td>\n",
       "      <td>3.07</td>\n",
       "      <td>4.070</td>\n",
       "      <td>17.40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Merc 450SL</td>\n",
       "      <td>17.3</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180</td>\n",
       "      <td>3.07</td>\n",
       "      <td>3.730</td>\n",
       "      <td>17.60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Merc 450SLC</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180</td>\n",
       "      <td>3.07</td>\n",
       "      <td>3.780</td>\n",
       "      <td>18.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cadillac Fleetwood</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>472.0</td>\n",
       "      <td>205</td>\n",
       "      <td>2.93</td>\n",
       "      <td>5.250</td>\n",
       "      <td>17.98</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Lincoln Continental</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>460.0</td>\n",
       "      <td>215</td>\n",
       "      <td>3.00</td>\n",
       "      <td>5.424</td>\n",
       "      <td>17.82</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Chrysler Imperial</td>\n",
       "      <td>14.7</td>\n",
       "      <td>8</td>\n",
       "      <td>440.0</td>\n",
       "      <td>230</td>\n",
       "      <td>3.23</td>\n",
       "      <td>5.345</td>\n",
       "      <td>17.42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Fiat 128</td>\n",
       "      <td>32.4</td>\n",
       "      <td>4</td>\n",
       "      <td>78.7</td>\n",
       "      <td>66</td>\n",
       "      <td>4.08</td>\n",
       "      <td>2.200</td>\n",
       "      <td>19.47</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Honda Civic</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>75.7</td>\n",
       "      <td>52</td>\n",
       "      <td>4.93</td>\n",
       "      <td>1.615</td>\n",
       "      <td>18.52</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Toyota Corolla</td>\n",
       "      <td>33.9</td>\n",
       "      <td>4</td>\n",
       "      <td>71.1</td>\n",
       "      <td>65</td>\n",
       "      <td>4.22</td>\n",
       "      <td>1.835</td>\n",
       "      <td>19.90</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Toyota Corona</td>\n",
       "      <td>21.5</td>\n",
       "      <td>4</td>\n",
       "      <td>120.1</td>\n",
       "      <td>97</td>\n",
       "      <td>3.70</td>\n",
       "      <td>2.465</td>\n",
       "      <td>20.01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Dodge Challenger</td>\n",
       "      <td>15.5</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.520</td>\n",
       "      <td>16.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>AMC Javelin</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3.15</td>\n",
       "      <td>3.435</td>\n",
       "      <td>17.30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Camaro Z28</td>\n",
       "      <td>13.3</td>\n",
       "      <td>8</td>\n",
       "      <td>350.0</td>\n",
       "      <td>245</td>\n",
       "      <td>3.73</td>\n",
       "      <td>3.840</td>\n",
       "      <td>15.41</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Pontiac Firebird</td>\n",
       "      <td>19.2</td>\n",
       "      <td>8</td>\n",
       "      <td>400.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.845</td>\n",
       "      <td>17.05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Fiat X1-9</td>\n",
       "      <td>27.3</td>\n",
       "      <td>4</td>\n",
       "      <td>79.0</td>\n",
       "      <td>66</td>\n",
       "      <td>4.08</td>\n",
       "      <td>1.935</td>\n",
       "      <td>18.90</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Porsche 914-2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4</td>\n",
       "      <td>120.3</td>\n",
       "      <td>91</td>\n",
       "      <td>4.43</td>\n",
       "      <td>2.140</td>\n",
       "      <td>16.70</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lotus Europa</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>95.1</td>\n",
       "      <td>113</td>\n",
       "      <td>3.77</td>\n",
       "      <td>1.513</td>\n",
       "      <td>16.90</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Ford Pantera L</td>\n",
       "      <td>15.8</td>\n",
       "      <td>8</td>\n",
       "      <td>351.0</td>\n",
       "      <td>264</td>\n",
       "      <td>4.22</td>\n",
       "      <td>3.170</td>\n",
       "      <td>14.50</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Ferrari Dino</td>\n",
       "      <td>19.7</td>\n",
       "      <td>6</td>\n",
       "      <td>145.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.62</td>\n",
       "      <td>2.770</td>\n",
       "      <td>15.50</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Volvo 142E</td>\n",
       "      <td>21.4</td>\n",
       "      <td>4</td>\n",
       "      <td>121.0</td>\n",
       "      <td>109</td>\n",
       "      <td>4.11</td>\n",
       "      <td>2.780</td>\n",
       "      <td>18.60</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              car_model   mpg  cyl   disp   hp  drat     wt   qsec  vs  am  \\\n",
       "0             Mazda RX4  21.0    6  160.0  110  3.90  2.620  16.46   0   1   \n",
       "1         Mazda RX4 Wag  21.0    6  160.0  110  3.90  2.875  17.02   0   1   \n",
       "2            Datsun 710  22.8    4  108.0   93  3.85  2.320  18.61   1   1   \n",
       "3        Hornet 4 Drive  21.4    6  258.0  110  3.08  3.215  19.44   1   0   \n",
       "4     Hornet Sportabout  18.7    8  360.0  175  3.15  3.440  17.02   0   0   \n",
       "5               Valiant  18.1    6  225.0  105  2.76  3.460  20.22   1   0   \n",
       "6            Duster 360  14.3    8  360.0  245  3.21  3.570  15.84   0   0   \n",
       "7             Merc 240D  24.4    4  146.7   62  3.69  3.190  20.00   1   0   \n",
       "8              Merc 230  22.8    4  140.8   95  3.92  3.150  22.90   1   0   \n",
       "9              Merc 280  19.2    6  167.6  123  3.92  3.440  18.30   1   0   \n",
       "10            Merc 280C  17.8    6  167.6  123  3.92  3.440  18.90   1   0   \n",
       "11           Merc 450SE  16.4    8  275.8  180  3.07  4.070  17.40   0   0   \n",
       "12           Merc 450SL  17.3    8  275.8  180  3.07  3.730  17.60   0   0   \n",
       "13          Merc 450SLC  15.2    8  275.8  180  3.07  3.780  18.00   0   0   \n",
       "14   Cadillac Fleetwood  10.4    8  472.0  205  2.93  5.250  17.98   0   0   \n",
       "15  Lincoln Continental  10.4    8  460.0  215  3.00  5.424  17.82   0   0   \n",
       "16    Chrysler Imperial  14.7    8  440.0  230  3.23  5.345  17.42   0   0   \n",
       "17             Fiat 128  32.4    4   78.7   66  4.08  2.200  19.47   1   1   \n",
       "18          Honda Civic  30.4    4   75.7   52  4.93  1.615  18.52   1   1   \n",
       "19       Toyota Corolla  33.9    4   71.1   65  4.22  1.835  19.90   1   1   \n",
       "20        Toyota Corona  21.5    4  120.1   97  3.70  2.465  20.01   1   0   \n",
       "21     Dodge Challenger  15.5    8  318.0  150  2.76  3.520  16.87   0   0   \n",
       "22          AMC Javelin  15.2    8  304.0  150  3.15  3.435  17.30   0   0   \n",
       "23           Camaro Z28  13.3    8  350.0  245  3.73  3.840  15.41   0   0   \n",
       "24     Pontiac Firebird  19.2    8  400.0  175  3.08  3.845  17.05   0   0   \n",
       "25            Fiat X1-9  27.3    4   79.0   66  4.08  1.935  18.90   1   1   \n",
       "26        Porsche 914-2  26.0    4  120.3   91  4.43  2.140  16.70   0   1   \n",
       "27         Lotus Europa  30.4    4   95.1  113  3.77  1.513  16.90   1   1   \n",
       "28       Ford Pantera L  15.8    8  351.0  264  4.22  3.170  14.50   0   1   \n",
       "29         Ferrari Dino  19.7    6  145.0  175  3.62  2.770  15.50   0   1   \n",
       "31           Volvo 142E  21.4    4  121.0  109  4.11  2.780  18.60   1   1   \n",
       "\n",
       "    gear  carb  \n",
       "0      4     4  \n",
       "1      4     4  \n",
       "2      4     1  \n",
       "3      3     1  \n",
       "4      3     2  \n",
       "5      3     1  \n",
       "6      3     4  \n",
       "7      4     2  \n",
       "8      4     2  \n",
       "9      4     4  \n",
       "10     4     4  \n",
       "11     3     3  \n",
       "12     3     3  \n",
       "13     3     3  \n",
       "14     3     4  \n",
       "15     3     4  \n",
       "16     3     4  \n",
       "17     4     1  \n",
       "18     4     2  \n",
       "19     4     1  \n",
       "20     3     1  \n",
       "21     3     2  \n",
       "22     3     2  \n",
       "23     3     4  \n",
       "24     3     2  \n",
       "25     4     1  \n",
       "26     5     2  \n",
       "27     5     2  \n",
       "28     5     4  \n",
       "29     5     6  \n",
       "31     4     2  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[abs(stats.zscore(data.hp))<2.5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_model</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.620</td>\n",
       "      <td>16.46</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mazda RX4 Wag</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.875</td>\n",
       "      <td>17.02</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>108.0</td>\n",
       "      <td>93</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.320</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hornet 4 Drive</td>\n",
       "      <td>21.4</td>\n",
       "      <td>6</td>\n",
       "      <td>258.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.215</td>\n",
       "      <td>19.44</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hornet Sportabout</td>\n",
       "      <td>18.7</td>\n",
       "      <td>8</td>\n",
       "      <td>360.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.15</td>\n",
       "      <td>3.440</td>\n",
       "      <td>17.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Valiant</td>\n",
       "      <td>18.1</td>\n",
       "      <td>6</td>\n",
       "      <td>225.0</td>\n",
       "      <td>105</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.460</td>\n",
       "      <td>20.22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Duster 360</td>\n",
       "      <td>14.3</td>\n",
       "      <td>8</td>\n",
       "      <td>360.0</td>\n",
       "      <td>245</td>\n",
       "      <td>3.21</td>\n",
       "      <td>3.570</td>\n",
       "      <td>15.84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Merc 240D</td>\n",
       "      <td>24.4</td>\n",
       "      <td>4</td>\n",
       "      <td>146.7</td>\n",
       "      <td>62</td>\n",
       "      <td>3.69</td>\n",
       "      <td>3.190</td>\n",
       "      <td>20.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Merc 230</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>140.8</td>\n",
       "      <td>95</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.150</td>\n",
       "      <td>22.90</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Merc 280</td>\n",
       "      <td>19.2</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.440</td>\n",
       "      <td>18.30</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Merc 280C</td>\n",
       "      <td>17.8</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.440</td>\n",
       "      <td>18.90</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Merc 450SE</td>\n",
       "      <td>16.4</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180</td>\n",
       "      <td>3.07</td>\n",
       "      <td>4.070</td>\n",
       "      <td>17.40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Merc 450SL</td>\n",
       "      <td>17.3</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180</td>\n",
       "      <td>3.07</td>\n",
       "      <td>3.730</td>\n",
       "      <td>17.60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Merc 450SLC</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180</td>\n",
       "      <td>3.07</td>\n",
       "      <td>3.780</td>\n",
       "      <td>18.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cadillac Fleetwood</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>472.0</td>\n",
       "      <td>205</td>\n",
       "      <td>2.93</td>\n",
       "      <td>5.250</td>\n",
       "      <td>17.98</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Lincoln Continental</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>460.0</td>\n",
       "      <td>215</td>\n",
       "      <td>3.00</td>\n",
       "      <td>5.424</td>\n",
       "      <td>17.82</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Chrysler Imperial</td>\n",
       "      <td>14.7</td>\n",
       "      <td>8</td>\n",
       "      <td>440.0</td>\n",
       "      <td>230</td>\n",
       "      <td>3.23</td>\n",
       "      <td>5.345</td>\n",
       "      <td>17.42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Fiat 128</td>\n",
       "      <td>32.4</td>\n",
       "      <td>4</td>\n",
       "      <td>78.7</td>\n",
       "      <td>66</td>\n",
       "      <td>4.08</td>\n",
       "      <td>2.200</td>\n",
       "      <td>19.47</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Honda Civic</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>75.7</td>\n",
       "      <td>52</td>\n",
       "      <td>4.93</td>\n",
       "      <td>1.615</td>\n",
       "      <td>18.52</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Toyota Corolla</td>\n",
       "      <td>33.9</td>\n",
       "      <td>4</td>\n",
       "      <td>71.1</td>\n",
       "      <td>65</td>\n",
       "      <td>4.22</td>\n",
       "      <td>1.835</td>\n",
       "      <td>19.90</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Toyota Corona</td>\n",
       "      <td>21.5</td>\n",
       "      <td>4</td>\n",
       "      <td>120.1</td>\n",
       "      <td>97</td>\n",
       "      <td>3.70</td>\n",
       "      <td>2.465</td>\n",
       "      <td>20.01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Dodge Challenger</td>\n",
       "      <td>15.5</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.520</td>\n",
       "      <td>16.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>AMC Javelin</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3.15</td>\n",
       "      <td>3.435</td>\n",
       "      <td>17.30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Camaro Z28</td>\n",
       "      <td>13.3</td>\n",
       "      <td>8</td>\n",
       "      <td>350.0</td>\n",
       "      <td>245</td>\n",
       "      <td>3.73</td>\n",
       "      <td>3.840</td>\n",
       "      <td>15.41</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Pontiac Firebird</td>\n",
       "      <td>19.2</td>\n",
       "      <td>8</td>\n",
       "      <td>400.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.845</td>\n",
       "      <td>17.05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Fiat X1-9</td>\n",
       "      <td>27.3</td>\n",
       "      <td>4</td>\n",
       "      <td>79.0</td>\n",
       "      <td>66</td>\n",
       "      <td>4.08</td>\n",
       "      <td>1.935</td>\n",
       "      <td>18.90</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Porsche 914-2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4</td>\n",
       "      <td>120.3</td>\n",
       "      <td>91</td>\n",
       "      <td>4.43</td>\n",
       "      <td>2.140</td>\n",
       "      <td>16.70</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lotus Europa</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>95.1</td>\n",
       "      <td>113</td>\n",
       "      <td>3.77</td>\n",
       "      <td>1.513</td>\n",
       "      <td>16.90</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Ford Pantera L</td>\n",
       "      <td>15.8</td>\n",
       "      <td>8</td>\n",
       "      <td>351.0</td>\n",
       "      <td>264</td>\n",
       "      <td>4.22</td>\n",
       "      <td>3.170</td>\n",
       "      <td>14.50</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Ferrari Dino</td>\n",
       "      <td>19.7</td>\n",
       "      <td>6</td>\n",
       "      <td>145.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.62</td>\n",
       "      <td>2.770</td>\n",
       "      <td>15.50</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Volvo 142E</td>\n",
       "      <td>21.4</td>\n",
       "      <td>4</td>\n",
       "      <td>121.0</td>\n",
       "      <td>109</td>\n",
       "      <td>4.11</td>\n",
       "      <td>2.780</td>\n",
       "      <td>18.60</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              car_model   mpg  cyl   disp   hp  drat     wt   qsec  vs  am  \\\n",
       "0             Mazda RX4  21.0    6  160.0  110  3.90  2.620  16.46   0   1   \n",
       "1         Mazda RX4 Wag  21.0    6  160.0  110  3.90  2.875  17.02   0   1   \n",
       "2            Datsun 710  22.8    4  108.0   93  3.85  2.320  18.61   1   1   \n",
       "3        Hornet 4 Drive  21.4    6  258.0  110  3.08  3.215  19.44   1   0   \n",
       "4     Hornet Sportabout  18.7    8  360.0  175  3.15  3.440  17.02   0   0   \n",
       "5               Valiant  18.1    6  225.0  105  2.76  3.460  20.22   1   0   \n",
       "6            Duster 360  14.3    8  360.0  245  3.21  3.570  15.84   0   0   \n",
       "7             Merc 240D  24.4    4  146.7   62  3.69  3.190  20.00   1   0   \n",
       "8              Merc 230  22.8    4  140.8   95  3.92  3.150  22.90   1   0   \n",
       "9              Merc 280  19.2    6  167.6  123  3.92  3.440  18.30   1   0   \n",
       "10            Merc 280C  17.8    6  167.6  123  3.92  3.440  18.90   1   0   \n",
       "11           Merc 450SE  16.4    8  275.8  180  3.07  4.070  17.40   0   0   \n",
       "12           Merc 450SL  17.3    8  275.8  180  3.07  3.730  17.60   0   0   \n",
       "13          Merc 450SLC  15.2    8  275.8  180  3.07  3.780  18.00   0   0   \n",
       "14   Cadillac Fleetwood  10.4    8  472.0  205  2.93  5.250  17.98   0   0   \n",
       "15  Lincoln Continental  10.4    8  460.0  215  3.00  5.424  17.82   0   0   \n",
       "16    Chrysler Imperial  14.7    8  440.0  230  3.23  5.345  17.42   0   0   \n",
       "17             Fiat 128  32.4    4   78.7   66  4.08  2.200  19.47   1   1   \n",
       "18          Honda Civic  30.4    4   75.7   52  4.93  1.615  18.52   1   1   \n",
       "19       Toyota Corolla  33.9    4   71.1   65  4.22  1.835  19.90   1   1   \n",
       "20        Toyota Corona  21.5    4  120.1   97  3.70  2.465  20.01   1   0   \n",
       "21     Dodge Challenger  15.5    8  318.0  150  2.76  3.520  16.87   0   0   \n",
       "22          AMC Javelin  15.2    8  304.0  150  3.15  3.435  17.30   0   0   \n",
       "23           Camaro Z28  13.3    8  350.0  245  3.73  3.840  15.41   0   0   \n",
       "24     Pontiac Firebird  19.2    8  400.0  175  3.08  3.845  17.05   0   0   \n",
       "25            Fiat X1-9  27.3    4   79.0   66  4.08  1.935  18.90   1   1   \n",
       "26        Porsche 914-2  26.0    4  120.3   91  4.43  2.140  16.70   0   1   \n",
       "27         Lotus Europa  30.4    4   95.1  113  3.77  1.513  16.90   1   1   \n",
       "28       Ford Pantera L  15.8    8  351.0  264  4.22  3.170  14.50   0   1   \n",
       "29         Ferrari Dino  19.7    6  145.0  175  3.62  2.770  15.50   0   1   \n",
       "31           Volvo 142E  21.4    4  121.0  109  4.11  2.780  18.60   1   1   \n",
       "\n",
       "    gear  carb  \n",
       "0      4     4  \n",
       "1      4     4  \n",
       "2      4     1  \n",
       "3      3     1  \n",
       "4      3     2  \n",
       "5      3     1  \n",
       "6      3     4  \n",
       "7      4     2  \n",
       "8      4     2  \n",
       "9      4     4  \n",
       "10     4     4  \n",
       "11     3     3  \n",
       "12     3     3  \n",
       "13     3     3  \n",
       "14     3     4  \n",
       "15     3     4  \n",
       "16     3     4  \n",
       "17     4     1  \n",
       "18     4     2  \n",
       "19     4     1  \n",
       "20     3     1  \n",
       "21     3     2  \n",
       "22     3     2  \n",
       "23     3     4  \n",
       "24     3     2  \n",
       "25     4     1  \n",
       "26     5     2  \n",
       "27     5     2  \n",
       "28     5     4  \n",
       "29     5     6  \n",
       "31     4     2  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(abs(stats.zscore(data.iloc[:,1:])<3)).all(axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Handle missing values with dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_model</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160</td>\n",
       "      <td>110.0</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.62</td>\n",
       "      <td>16.46</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mazda RX4 Wag</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>$</td>\n",
       "      <td>110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.875</td>\n",
       "      <td>*</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>108</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.85</td>\n",
       "      <td>?</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hornet 4 Drive</td>\n",
       "      <td>999.0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.215</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.32</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        car_model    mpg  cyl disp     hp  drat     wt   qsec  vs  am  gear  \\\n",
       "0       Mazda RX4   21.0    6  160  110.0  3.90   2.62  16.46   0   1     4   \n",
       "1   Mazda RX4 Wag   21.0    6    $  110.0   NaN  2.875      *   0   1     4   \n",
       "2      Datsun 710    NaN    4  108    NaN  3.85      ?  18.61   1   1     4   \n",
       "3  Hornet 4 Drive  999.0    6  NaN    NaN  3.08  3.215      -   1   0     3   \n",
       "4      Datsun 710   22.8    4  NaN   93.0  3.85   2.32  18.61   1   1     4   \n",
       "\n",
       "   carb  \n",
       "0     4  \n",
       "1     4  \n",
       "2     1  \n",
       "3     1  \n",
       "4     1  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(mtcars_missing)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 32 entries, 0 to 31\n",
      "Data columns (total 12 columns):\n",
      "car_model    32 non-null object\n",
      "mpg          31 non-null float64\n",
      "cyl          32 non-null int64\n",
      "disp         25 non-null object\n",
      "hp           30 non-null float64\n",
      "drat         31 non-null float64\n",
      "wt           28 non-null object\n",
      "qsec         20 non-null object\n",
      "vs           32 non-null int64\n",
      "am           32 non-null int64\n",
      "gear         32 non-null int64\n",
      "carb         32 non-null int64\n",
      "dtypes: float64(3), int64(5), object(4)\n",
      "memory usage: 3.1+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1         *\n",
       "3         -\n",
       "28     14.5\n",
       "6     15.84\n",
       "0     16.46\n",
       "26     16.7\n",
       "21    16.87\n",
       "27     16.9\n",
       "22     17.3\n",
       "11     17.4\n",
       "16    17.42\n",
       "12     17.6\n",
       "13       18\n",
       "18    18.52\n",
       "2     18.61\n",
       "4     18.61\n",
       "10     18.9\n",
       "19     19.9\n",
       "5     20.22\n",
       "7     20.22\n",
       "8       NaN\n",
       "9       NaN\n",
       "14      NaN\n",
       "15      NaN\n",
       "17      NaN\n",
       "20      NaN\n",
       "23      NaN\n",
       "24      NaN\n",
       "25      NaN\n",
       "29      NaN\n",
       "30      NaN\n",
       "31      NaN\n",
       "Name: qsec, dtype: object"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.qsec.sort_values(ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.replace(['$','?','*','-'],np.nan, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_model</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160</td>\n",
       "      <td>110.0</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.62</td>\n",
       "      <td>16.46</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mazda RX4 Wag</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>108</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hornet 4 Drive</td>\n",
       "      <td>999.0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.215</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.32</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        car_model    mpg  cyl disp     hp  drat     wt   qsec  vs  am  gear  \\\n",
       "0       Mazda RX4   21.0    6  160  110.0  3.90   2.62  16.46   0   1     4   \n",
       "1   Mazda RX4 Wag   21.0    6  NaN  110.0   NaN  2.875    NaN   0   1     4   \n",
       "2      Datsun 710    NaN    4  108    NaN  3.85    NaN  18.61   1   1     4   \n",
       "3  Hornet 4 Drive  999.0    6  NaN    NaN  3.08  3.215    NaN   1   0     3   \n",
       "4      Datsun 710   22.8    4  NaN   93.0  3.85   2.32  18.61   1   1     4   \n",
       "\n",
       "   carb  \n",
       "0     4  \n",
       "1     4  \n",
       "2     1  \n",
       "3     1  \n",
       "4     1  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "car_model     0\n",
       "mpg           1\n",
       "cyl           0\n",
       "disp          9\n",
       "hp            2\n",
       "drat          1\n",
       "wt            6\n",
       "qsec         14\n",
       "vs            0\n",
       "am            0\n",
       "gear          0\n",
       "carb          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_model</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160</td>\n",
       "      <td>110.0</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.62</td>\n",
       "      <td>16.46</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.32</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Valiant</td>\n",
       "      <td>18.1</td>\n",
       "      <td>6</td>\n",
       "      <td>225</td>\n",
       "      <td>105.0</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.46</td>\n",
       "      <td>20.22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Duster 360</td>\n",
       "      <td>14.3</td>\n",
       "      <td>8</td>\n",
       "      <td>360</td>\n",
       "      <td>245.0</td>\n",
       "      <td>3.21</td>\n",
       "      <td>3.57</td>\n",
       "      <td>15.84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Valiant 2</td>\n",
       "      <td>18.1</td>\n",
       "      <td>6</td>\n",
       "      <td>225</td>\n",
       "      <td>105.0</td>\n",
       "      <td>2.76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Valiant</td>\n",
       "      <td>18.1</td>\n",
       "      <td>6</td>\n",
       "      <td>225</td>\n",
       "      <td>105.0</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Merc 280</td>\n",
       "      <td>19.2</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123.0</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.44</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Merc 280C</td>\n",
       "      <td>17.8</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123.0</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.44</td>\n",
       "      <td>18.9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Merc 450SE</td>\n",
       "      <td>16.4</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180.0</td>\n",
       "      <td>3.07</td>\n",
       "      <td>4.07</td>\n",
       "      <td>17.4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Merc 450SL</td>\n",
       "      <td>17.3</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180.0</td>\n",
       "      <td>3.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Merc 450SLC</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180.0</td>\n",
       "      <td>3.07</td>\n",
       "      <td>3.78</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cadillac Fleetwood</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>205.0</td>\n",
       "      <td>2.93</td>\n",
       "      <td>5.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Lincoln Continental</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>460</td>\n",
       "      <td>215.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>5.424</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Chrysler Imperial</td>\n",
       "      <td>14.7</td>\n",
       "      <td>8</td>\n",
       "      <td>440</td>\n",
       "      <td>230.0</td>\n",
       "      <td>3.23</td>\n",
       "      <td>5.345</td>\n",
       "      <td>17.42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Fiat 128</td>\n",
       "      <td>32.4</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66.0</td>\n",
       "      <td>4.08</td>\n",
       "      <td>2.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Honda Civic</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>75.7</td>\n",
       "      <td>52.0</td>\n",
       "      <td>4.93</td>\n",
       "      <td>1.615</td>\n",
       "      <td>18.52</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Toyota Corolla</td>\n",
       "      <td>33.9</td>\n",
       "      <td>4</td>\n",
       "      <td>71.1</td>\n",
       "      <td>65.0</td>\n",
       "      <td>4.22</td>\n",
       "      <td>1.835</td>\n",
       "      <td>19.9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Toyota Corona</td>\n",
       "      <td>21.5</td>\n",
       "      <td>4</td>\n",
       "      <td>120.1</td>\n",
       "      <td>97.0</td>\n",
       "      <td>3.70</td>\n",
       "      <td>2.465</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Dodge Challenger</td>\n",
       "      <td>15.5</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>2.76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>AMC Javelin</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>304</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3.15</td>\n",
       "      <td>3.435</td>\n",
       "      <td>17.3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Camaro Z28</td>\n",
       "      <td>13.3</td>\n",
       "      <td>8</td>\n",
       "      <td>350</td>\n",
       "      <td>245.0</td>\n",
       "      <td>3.73</td>\n",
       "      <td>3.84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Pontiac Firebird</td>\n",
       "      <td>19.2</td>\n",
       "      <td>8</td>\n",
       "      <td>400</td>\n",
       "      <td>175.0</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.845</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Porsche 914-2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4</td>\n",
       "      <td>120.3</td>\n",
       "      <td>91.0</td>\n",
       "      <td>4.43</td>\n",
       "      <td>2.14</td>\n",
       "      <td>16.7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lotus Europa</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>95.1</td>\n",
       "      <td>113.0</td>\n",
       "      <td>3.77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Ford Pantera L</td>\n",
       "      <td>15.8</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>264.0</td>\n",
       "      <td>4.22</td>\n",
       "      <td>3.17</td>\n",
       "      <td>14.5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Ferrari Dino</td>\n",
       "      <td>19.7</td>\n",
       "      <td>6</td>\n",
       "      <td>145</td>\n",
       "      <td>175.0</td>\n",
       "      <td>3.62</td>\n",
       "      <td>2.77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Maserati Bora</td>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>335.0</td>\n",
       "      <td>3.54</td>\n",
       "      <td>3.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Volvo 142E</td>\n",
       "      <td>21.4</td>\n",
       "      <td>4</td>\n",
       "      <td>121</td>\n",
       "      <td>109.0</td>\n",
       "      <td>4.11</td>\n",
       "      <td>2.78</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              car_model   mpg  cyl   disp     hp  drat     wt   qsec  vs  am  \\\n",
       "0             Mazda RX4  21.0    6    160  110.0  3.90   2.62  16.46   0   1   \n",
       "4            Datsun 710  22.8    4    NaN   93.0  3.85   2.32  18.61   1   1   \n",
       "5               Valiant  18.1    6    225  105.0  2.76   3.46  20.22   1   0   \n",
       "6            Duster 360  14.3    8    360  245.0  3.21   3.57  15.84   0   0   \n",
       "7             Valiant 2  18.1    6    225  105.0  2.76    NaN  20.22   1   0   \n",
       "8               Valiant  18.1    6    225  105.0  2.76   3.46    NaN   1   0   \n",
       "9              Merc 280  19.2    6  167.6  123.0  3.92   3.44    NaN   1   0   \n",
       "10            Merc 280C  17.8    6  167.6  123.0  3.92   3.44   18.9   1   0   \n",
       "11           Merc 450SE  16.4    8  275.8  180.0  3.07   4.07   17.4   0   0   \n",
       "12           Merc 450SL  17.3    8  275.8  180.0  3.07    NaN   17.6   0   0   \n",
       "13          Merc 450SLC  15.2    8  275.8  180.0  3.07   3.78     18   0   0   \n",
       "14   Cadillac Fleetwood  10.4    8    NaN  205.0  2.93   5.25    NaN   0   0   \n",
       "15  Lincoln Continental  10.4    8    460  215.0  3.00  5.424    NaN   0   0   \n",
       "16    Chrysler Imperial  14.7    8    440  230.0  3.23  5.345  17.42   0   0   \n",
       "17             Fiat 128  32.4    4    NaN   66.0  4.08    2.2    NaN   1   1   \n",
       "18          Honda Civic  30.4    4   75.7   52.0  4.93  1.615  18.52   1   1   \n",
       "19       Toyota Corolla  33.9    4   71.1   65.0  4.22  1.835   19.9   1   1   \n",
       "20        Toyota Corona  21.5    4  120.1   97.0  3.70  2.465    NaN   1   0   \n",
       "21     Dodge Challenger  15.5    8    NaN  150.0  2.76    NaN  16.87   0   0   \n",
       "22          AMC Javelin  15.2    8    304  150.0  3.15  3.435   17.3   0   0   \n",
       "23           Camaro Z28  13.3    8    350  245.0  3.73   3.84    NaN   0   0   \n",
       "24     Pontiac Firebird  19.2    8    400  175.0  3.08  3.845    NaN   0   0   \n",
       "26        Porsche 914-2  26.0    4  120.3   91.0  4.43   2.14   16.7   0   1   \n",
       "27         Lotus Europa  30.4    4   95.1  113.0  3.77    NaN   16.9   1   1   \n",
       "28       Ford Pantera L  15.8    8    NaN  264.0  4.22   3.17   14.5   0   1   \n",
       "29         Ferrari Dino  19.7    6    145  175.0  3.62   2.77    NaN   0   1   \n",
       "30        Maserati Bora  15.0    8    NaN  335.0  3.54   3.57    NaN   0   1   \n",
       "31           Volvo 142E  21.4    4    121  109.0  4.11   2.78    NaN   1   1   \n",
       "\n",
       "    gear  carb  \n",
       "0      4     4  \n",
       "4      4     1  \n",
       "5      3     1  \n",
       "6      3     4  \n",
       "7      3     1  \n",
       "8      3     1  \n",
       "9      4     4  \n",
       "10     4     4  \n",
       "11     3     3  \n",
       "12     3     3  \n",
       "13     3     3  \n",
       "14     3     4  \n",
       "15     3     4  \n",
       "16     3     4  \n",
       "17     4     1  \n",
       "18     4     2  \n",
       "19     4     1  \n",
       "20     3     1  \n",
       "21     3     2  \n",
       "22     3     2  \n",
       "23     3     4  \n",
       "24     3     2  \n",
       "26     5     2  \n",
       "27     5     2  \n",
       "28     5     4  \n",
       "29     5     6  \n",
       "30     5     8  \n",
       "31     4     2  "
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dropna(thresh=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19.2"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)*0.6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_model</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160</td>\n",
       "      <td>110.0</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.62</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mazda RX4 Wag</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.875</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>108</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hornet 4 Drive</td>\n",
       "      <td>999.0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.215</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.32</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Valiant</td>\n",
       "      <td>18.1</td>\n",
       "      <td>6</td>\n",
       "      <td>225</td>\n",
       "      <td>105.0</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.46</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Duster 360</td>\n",
       "      <td>14.3</td>\n",
       "      <td>8</td>\n",
       "      <td>360</td>\n",
       "      <td>245.0</td>\n",
       "      <td>3.21</td>\n",
       "      <td>3.57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Valiant 2</td>\n",
       "      <td>18.1</td>\n",
       "      <td>6</td>\n",
       "      <td>225</td>\n",
       "      <td>105.0</td>\n",
       "      <td>2.76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Valiant</td>\n",
       "      <td>18.1</td>\n",
       "      <td>6</td>\n",
       "      <td>225</td>\n",
       "      <td>105.0</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.46</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Merc 280</td>\n",
       "      <td>19.2</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123.0</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.44</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Merc 280C</td>\n",
       "      <td>17.8</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123.0</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.44</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Merc 450SE</td>\n",
       "      <td>16.4</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180.0</td>\n",
       "      <td>3.07</td>\n",
       "      <td>4.07</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Merc 450SL</td>\n",
       "      <td>17.3</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180.0</td>\n",
       "      <td>3.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Merc 450SLC</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180.0</td>\n",
       "      <td>3.07</td>\n",
       "      <td>3.78</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cadillac Fleetwood</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>205.0</td>\n",
       "      <td>2.93</td>\n",
       "      <td>5.25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Lincoln Continental</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>460</td>\n",
       "      <td>215.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>5.424</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Chrysler Imperial</td>\n",
       "      <td>14.7</td>\n",
       "      <td>8</td>\n",
       "      <td>440</td>\n",
       "      <td>230.0</td>\n",
       "      <td>3.23</td>\n",
       "      <td>5.345</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Fiat 128</td>\n",
       "      <td>32.4</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66.0</td>\n",
       "      <td>4.08</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Honda Civic</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>75.7</td>\n",
       "      <td>52.0</td>\n",
       "      <td>4.93</td>\n",
       "      <td>1.615</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Toyota Corolla</td>\n",
       "      <td>33.9</td>\n",
       "      <td>4</td>\n",
       "      <td>71.1</td>\n",
       "      <td>65.0</td>\n",
       "      <td>4.22</td>\n",
       "      <td>1.835</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Toyota Corona</td>\n",
       "      <td>21.5</td>\n",
       "      <td>4</td>\n",
       "      <td>120.1</td>\n",
       "      <td>97.0</td>\n",
       "      <td>3.70</td>\n",
       "      <td>2.465</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Dodge Challenger</td>\n",
       "      <td>15.5</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>2.76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>AMC Javelin</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>304</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3.15</td>\n",
       "      <td>3.435</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Camaro Z28</td>\n",
       "      <td>13.3</td>\n",
       "      <td>8</td>\n",
       "      <td>350</td>\n",
       "      <td>245.0</td>\n",
       "      <td>3.73</td>\n",
       "      <td>3.84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Pontiac Firebird</td>\n",
       "      <td>19.2</td>\n",
       "      <td>8</td>\n",
       "      <td>400</td>\n",
       "      <td>175.0</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.845</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Fiat X1-9</td>\n",
       "      <td>27.3</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66.0</td>\n",
       "      <td>4.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Porsche 914-2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4</td>\n",
       "      <td>120.3</td>\n",
       "      <td>91.0</td>\n",
       "      <td>4.43</td>\n",
       "      <td>2.14</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lotus Europa</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>95.1</td>\n",
       "      <td>113.0</td>\n",
       "      <td>3.77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Ford Pantera L</td>\n",
       "      <td>15.8</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>264.0</td>\n",
       "      <td>4.22</td>\n",
       "      <td>3.17</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Ferrari Dino</td>\n",
       "      <td>19.7</td>\n",
       "      <td>6</td>\n",
       "      <td>145</td>\n",
       "      <td>175.0</td>\n",
       "      <td>3.62</td>\n",
       "      <td>2.77</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Maserati Bora</td>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>335.0</td>\n",
       "      <td>3.54</td>\n",
       "      <td>3.57</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Volvo 142E</td>\n",
       "      <td>21.4</td>\n",
       "      <td>4</td>\n",
       "      <td>121</td>\n",
       "      <td>109.0</td>\n",
       "      <td>4.11</td>\n",
       "      <td>2.78</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              car_model    mpg  cyl   disp     hp  drat     wt  vs  am  gear  \\\n",
       "0             Mazda RX4   21.0    6    160  110.0  3.90   2.62   0   1     4   \n",
       "1         Mazda RX4 Wag   21.0    6    NaN  110.0   NaN  2.875   0   1     4   \n",
       "2            Datsun 710    NaN    4    108    NaN  3.85    NaN   1   1     4   \n",
       "3        Hornet 4 Drive  999.0    6    NaN    NaN  3.08  3.215   1   0     3   \n",
       "4            Datsun 710   22.8    4    NaN   93.0  3.85   2.32   1   1     4   \n",
       "5               Valiant   18.1    6    225  105.0  2.76   3.46   1   0     3   \n",
       "6            Duster 360   14.3    8    360  245.0  3.21   3.57   0   0     3   \n",
       "7             Valiant 2   18.1    6    225  105.0  2.76    NaN   1   0     3   \n",
       "8               Valiant   18.1    6    225  105.0  2.76   3.46   1   0     3   \n",
       "9              Merc 280   19.2    6  167.6  123.0  3.92   3.44   1   0     4   \n",
       "10            Merc 280C   17.8    6  167.6  123.0  3.92   3.44   1   0     4   \n",
       "11           Merc 450SE   16.4    8  275.8  180.0  3.07   4.07   0   0     3   \n",
       "12           Merc 450SL   17.3    8  275.8  180.0  3.07    NaN   0   0     3   \n",
       "13          Merc 450SLC   15.2    8  275.8  180.0  3.07   3.78   0   0     3   \n",
       "14   Cadillac Fleetwood   10.4    8    NaN  205.0  2.93   5.25   0   0     3   \n",
       "15  Lincoln Continental   10.4    8    460  215.0  3.00  5.424   0   0     3   \n",
       "16    Chrysler Imperial   14.7    8    440  230.0  3.23  5.345   0   0     3   \n",
       "17             Fiat 128   32.4    4    NaN   66.0  4.08    2.2   1   1     4   \n",
       "18          Honda Civic   30.4    4   75.7   52.0  4.93  1.615   1   1     4   \n",
       "19       Toyota Corolla   33.9    4   71.1   65.0  4.22  1.835   1   1     4   \n",
       "20        Toyota Corona   21.5    4  120.1   97.0  3.70  2.465   1   0     3   \n",
       "21     Dodge Challenger   15.5    8    NaN  150.0  2.76    NaN   0   0     3   \n",
       "22          AMC Javelin   15.2    8    304  150.0  3.15  3.435   0   0     3   \n",
       "23           Camaro Z28   13.3    8    350  245.0  3.73   3.84   0   0     3   \n",
       "24     Pontiac Firebird   19.2    8    400  175.0  3.08  3.845   0   0     3   \n",
       "25            Fiat X1-9   27.3    4    NaN   66.0  4.08    NaN   1   1     4   \n",
       "26        Porsche 914-2   26.0    4  120.3   91.0  4.43   2.14   0   1     5   \n",
       "27         Lotus Europa   30.4    4   95.1  113.0  3.77    NaN   1   1     5   \n",
       "28       Ford Pantera L   15.8    8    NaN  264.0  4.22   3.17   0   1     5   \n",
       "29         Ferrari Dino   19.7    6    145  175.0  3.62   2.77   0   1     5   \n",
       "30        Maserati Bora   15.0    8    NaN  335.0  3.54   3.57   0   1     5   \n",
       "31           Volvo 142E   21.4    4    121  109.0  4.11   2.78   1   1     4   \n",
       "\n",
       "    carb  \n",
       "0      4  \n",
       "1      4  \n",
       "2      1  \n",
       "3      1  \n",
       "4      1  \n",
       "5      1  \n",
       "6      4  \n",
       "7      1  \n",
       "8      1  \n",
       "9      4  \n",
       "10     4  \n",
       "11     3  \n",
       "12     3  \n",
       "13     3  \n",
       "14     4  \n",
       "15     4  \n",
       "16     4  \n",
       "17     1  \n",
       "18     2  \n",
       "19     1  \n",
       "20     1  \n",
       "21     2  \n",
       "22     2  \n",
       "23     4  \n",
       "24     2  \n",
       "25     1  \n",
       "26     2  \n",
       "27     2  \n",
       "28     4  \n",
       "29     6  \n",
       "30     8  \n",
       "31     2  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dropna(thresh=len(data)*0.6,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.\tPandas Apply Function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(13320, 9)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area_type</th>\n",
       "      <th>availability</th>\n",
       "      <th>location</th>\n",
       "      <th>size</th>\n",
       "      <th>society</th>\n",
       "      <th>total_sqft</th>\n",
       "      <th>bath</th>\n",
       "      <th>balcony</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>19-Dec</td>\n",
       "      <td>Electronic City Phase II</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>Coomee</td>\n",
       "      <td>1056</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>39.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Plot  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Chikka Tirupathi</td>\n",
       "      <td>4 Bedroom</td>\n",
       "      <td>Theanmp</td>\n",
       "      <td>2600</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>120.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Uttarahalli</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1440</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>62.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Lingadheeranahalli</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>Soiewre</td>\n",
       "      <td>1521</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>95.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Super built-up  Area</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>Kothanur</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1200</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>51.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              area_type   availability                  location       size  \\\n",
       "0  Super built-up  Area         19-Dec  Electronic City Phase II      2 BHK   \n",
       "1            Plot  Area  Ready To Move          Chikka Tirupathi  4 Bedroom   \n",
       "2        Built-up  Area  Ready To Move               Uttarahalli      3 BHK   \n",
       "3  Super built-up  Area  Ready To Move        Lingadheeranahalli      3 BHK   \n",
       "4  Super built-up  Area  Ready To Move                  Kothanur      2 BHK   \n",
       "\n",
       "   society total_sqft  bath  balcony   price  \n",
       "0  Coomee        1056   2.0      1.0   39.07  \n",
       "1  Theanmp       2600   5.0      3.0  120.00  \n",
       "2      NaN       1440   2.0      3.0   62.00  \n",
       "3  Soiewre       1521   3.0      1.0   95.00  \n",
       "4      NaN       1200   2.0      1.0   51.00  "
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(house_price_bangalore)\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.fillna(method='ffill',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[:,['area_type','location','society']] = data.loc[:,['area_type','location','society']].apply(LabelEncoder().fit_transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area_type</th>\n",
       "      <th>availability</th>\n",
       "      <th>location</th>\n",
       "      <th>size</th>\n",
       "      <th>society</th>\n",
       "      <th>total_sqft</th>\n",
       "      <th>bath</th>\n",
       "      <th>balcony</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>19-Dec</td>\n",
       "      <td>419</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>464</td>\n",
       "      <td>1056</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>39.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>317</td>\n",
       "      <td>4 Bedroom</td>\n",
       "      <td>2439</td>\n",
       "      <td>2600</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>120.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>1179</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>2439</td>\n",
       "      <td>1440</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>62.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>757</td>\n",
       "      <td>3 BHK</td>\n",
       "      <td>2186</td>\n",
       "      <td>1521</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>95.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>Ready To Move</td>\n",
       "      <td>716</td>\n",
       "      <td>2 BHK</td>\n",
       "      <td>2186</td>\n",
       "      <td>1200</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>51.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   area_type   availability  location       size  society total_sqft  bath  \\\n",
       "0          3         19-Dec       419      2 BHK      464       1056   2.0   \n",
       "1          2  Ready To Move       317  4 Bedroom     2439       2600   5.0   \n",
       "2          0  Ready To Move      1179      3 BHK     2439       1440   2.0   \n",
       "3          3  Ready To Move       757      3 BHK     2186       1521   3.0   \n",
       "4          3  Ready To Move       716      2 BHK     2186       1200   2.0   \n",
       "\n",
       "   balcony   price  \n",
       "0      1.0   39.07  \n",
       "1      3.0  120.00  \n",
       "2      3.0   62.00  \n",
       "3      1.0   95.00  \n",
       "4      1.0   51.00  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8. Pandas set_option for formating, change default max_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(569, 31)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean radius</th>\n",
       "      <th>mean texture</th>\n",
       "      <th>mean perimeter</th>\n",
       "      <th>mean area</th>\n",
       "      <th>mean smoothness</th>\n",
       "      <th>mean compactness</th>\n",
       "      <th>mean concavity</th>\n",
       "      <th>mean concave points</th>\n",
       "      <th>mean symmetry</th>\n",
       "      <th>mean fractal dimension</th>\n",
       "      <th>radius error</th>\n",
       "      <th>texture error</th>\n",
       "      <th>perimeter error</th>\n",
       "      <th>area error</th>\n",
       "      <th>smoothness error</th>\n",
       "      <th>compactness error</th>\n",
       "      <th>concavity error</th>\n",
       "      <th>concave points error</th>\n",
       "      <th>symmetry error</th>\n",
       "      <th>fractal dimension error</th>\n",
       "      <th>worst radius</th>\n",
       "      <th>worst texture</th>\n",
       "      <th>worst perimeter</th>\n",
       "      <th>worst area</th>\n",
       "      <th>worst smoothness</th>\n",
       "      <th>worst compactness</th>\n",
       "      <th>worst concavity</th>\n",
       "      <th>worst concave points</th>\n",
       "      <th>worst symmetry</th>\n",
       "      <th>worst fractal dimension</th>\n",
       "      <th>outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>1.0950</td>\n",
       "      <td>0.9053</td>\n",
       "      <td>8.589</td>\n",
       "      <td>153.40</td>\n",
       "      <td>0.006399</td>\n",
       "      <td>0.04904</td>\n",
       "      <td>0.05373</td>\n",
       "      <td>0.01587</td>\n",
       "      <td>0.03003</td>\n",
       "      <td>0.006193</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.7339</td>\n",
       "      <td>3.398</td>\n",
       "      <td>74.08</td>\n",
       "      <td>0.005225</td>\n",
       "      <td>0.01308</td>\n",
       "      <td>0.01860</td>\n",
       "      <td>0.01340</td>\n",
       "      <td>0.01389</td>\n",
       "      <td>0.003532</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>0.7456</td>\n",
       "      <td>0.7869</td>\n",
       "      <td>4.585</td>\n",
       "      <td>94.03</td>\n",
       "      <td>0.006150</td>\n",
       "      <td>0.04006</td>\n",
       "      <td>0.03832</td>\n",
       "      <td>0.02058</td>\n",
       "      <td>0.02250</td>\n",
       "      <td>0.004571</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>0.4956</td>\n",
       "      <td>1.1560</td>\n",
       "      <td>3.445</td>\n",
       "      <td>27.23</td>\n",
       "      <td>0.009110</td>\n",
       "      <td>0.07458</td>\n",
       "      <td>0.05661</td>\n",
       "      <td>0.01867</td>\n",
       "      <td>0.05963</td>\n",
       "      <td>0.009208</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>0.7572</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>5.438</td>\n",
       "      <td>94.44</td>\n",
       "      <td>0.011490</td>\n",
       "      <td>0.02461</td>\n",
       "      <td>0.05688</td>\n",
       "      <td>0.01885</td>\n",
       "      <td>0.01756</td>\n",
       "      <td>0.005115</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       "0        17.99         10.38          122.80     1001.0          0.11840   \n",
       "1        20.57         17.77          132.90     1326.0          0.08474   \n",
       "2        19.69         21.25          130.00     1203.0          0.10960   \n",
       "3        11.42         20.38           77.58      386.1          0.14250   \n",
       "4        20.29         14.34          135.10     1297.0          0.10030   \n",
       "\n",
       "   mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       "0           0.27760          0.3001              0.14710         0.2419   \n",
       "1           0.07864          0.0869              0.07017         0.1812   \n",
       "2           0.15990          0.1974              0.12790         0.2069   \n",
       "3           0.28390          0.2414              0.10520         0.2597   \n",
       "4           0.13280          0.1980              0.10430         0.1809   \n",
       "\n",
       "   mean fractal dimension  radius error  texture error  perimeter error  \\\n",
       "0                 0.07871        1.0950         0.9053            8.589   \n",
       "1                 0.05667        0.5435         0.7339            3.398   \n",
       "2                 0.05999        0.7456         0.7869            4.585   \n",
       "3                 0.09744        0.4956         1.1560            3.445   \n",
       "4                 0.05883        0.7572         0.7813            5.438   \n",
       "\n",
       "   area error  smoothness error  compactness error  concavity error  \\\n",
       "0      153.40          0.006399            0.04904          0.05373   \n",
       "1       74.08          0.005225            0.01308          0.01860   \n",
       "2       94.03          0.006150            0.04006          0.03832   \n",
       "3       27.23          0.009110            0.07458          0.05661   \n",
       "4       94.44          0.011490            0.02461          0.05688   \n",
       "\n",
       "   concave points error  symmetry error  fractal dimension error  \\\n",
       "0               0.01587         0.03003                 0.006193   \n",
       "1               0.01340         0.01389                 0.003532   \n",
       "2               0.02058         0.02250                 0.004571   \n",
       "3               0.01867         0.05963                 0.009208   \n",
       "4               0.01885         0.01756                 0.005115   \n",
       "\n",
       "   worst radius  worst texture  worst perimeter  worst area  worst smoothness  \\\n",
       "0         25.38          17.33           184.60      2019.0            0.1622   \n",
       "1         24.99          23.41           158.80      1956.0            0.1238   \n",
       "2         23.57          25.53           152.50      1709.0            0.1444   \n",
       "3         14.91          26.50            98.87       567.7            0.2098   \n",
       "4         22.54          16.67           152.20      1575.0            0.1374   \n",
       "\n",
       "   worst compactness  worst concavity  worst concave points  worst symmetry  \\\n",
       "0             0.6656           0.7119                0.2654          0.4601   \n",
       "1             0.1866           0.2416                0.1860          0.2750   \n",
       "2             0.4245           0.4504                0.2430          0.3613   \n",
       "3             0.8663           0.6869                0.2575          0.6638   \n",
       "4             0.2050           0.4000                0.1625          0.2364   \n",
       "\n",
       "   worst fractal dimension  outcome  \n",
       "0                  0.11890        1  \n",
       "1                  0.08902        1  \n",
       "2                  0.08758        1  \n",
       "3                  0.17300        1  \n",
       "4                  0.07678        1  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data= pd.read_csv(breast_cancer)\n",
    "print(data.shape)\n",
    "data.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns',50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean radius</th>\n",
       "      <th>mean texture</th>\n",
       "      <th>mean perimeter</th>\n",
       "      <th>mean area</th>\n",
       "      <th>mean smoothness</th>\n",
       "      <th>mean compactness</th>\n",
       "      <th>mean concavity</th>\n",
       "      <th>mean concave points</th>\n",
       "      <th>mean symmetry</th>\n",
       "      <th>mean fractal dimension</th>\n",
       "      <th>radius error</th>\n",
       "      <th>texture error</th>\n",
       "      <th>perimeter error</th>\n",
       "      <th>area error</th>\n",
       "      <th>smoothness error</th>\n",
       "      <th>compactness error</th>\n",
       "      <th>concavity error</th>\n",
       "      <th>concave points error</th>\n",
       "      <th>symmetry error</th>\n",
       "      <th>fractal dimension error</th>\n",
       "      <th>worst radius</th>\n",
       "      <th>worst texture</th>\n",
       "      <th>worst perimeter</th>\n",
       "      <th>worst area</th>\n",
       "      <th>worst smoothness</th>\n",
       "      <th>worst compactness</th>\n",
       "      <th>worst concavity</th>\n",
       "      <th>worst concave points</th>\n",
       "      <th>worst symmetry</th>\n",
       "      <th>worst fractal dimension</th>\n",
       "      <th>outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>1.0950</td>\n",
       "      <td>0.9053</td>\n",
       "      <td>8.589</td>\n",
       "      <td>153.40</td>\n",
       "      <td>0.006399</td>\n",
       "      <td>0.04904</td>\n",
       "      <td>0.05373</td>\n",
       "      <td>0.01587</td>\n",
       "      <td>0.03003</td>\n",
       "      <td>0.006193</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.7339</td>\n",
       "      <td>3.398</td>\n",
       "      <td>74.08</td>\n",
       "      <td>0.005225</td>\n",
       "      <td>0.01308</td>\n",
       "      <td>0.01860</td>\n",
       "      <td>0.01340</td>\n",
       "      <td>0.01389</td>\n",
       "      <td>0.003532</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>0.7456</td>\n",
       "      <td>0.7869</td>\n",
       "      <td>4.585</td>\n",
       "      <td>94.03</td>\n",
       "      <td>0.006150</td>\n",
       "      <td>0.04006</td>\n",
       "      <td>0.03832</td>\n",
       "      <td>0.02058</td>\n",
       "      <td>0.02250</td>\n",
       "      <td>0.004571</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>0.4956</td>\n",
       "      <td>1.1560</td>\n",
       "      <td>3.445</td>\n",
       "      <td>27.23</td>\n",
       "      <td>0.009110</td>\n",
       "      <td>0.07458</td>\n",
       "      <td>0.05661</td>\n",
       "      <td>0.01867</td>\n",
       "      <td>0.05963</td>\n",
       "      <td>0.009208</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>0.7572</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>5.438</td>\n",
       "      <td>94.44</td>\n",
       "      <td>0.011490</td>\n",
       "      <td>0.02461</td>\n",
       "      <td>0.05688</td>\n",
       "      <td>0.01885</td>\n",
       "      <td>0.01756</td>\n",
       "      <td>0.005115</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       "0        17.99         10.38          122.80     1001.0          0.11840   \n",
       "1        20.57         17.77          132.90     1326.0          0.08474   \n",
       "2        19.69         21.25          130.00     1203.0          0.10960   \n",
       "3        11.42         20.38           77.58      386.1          0.14250   \n",
       "4        20.29         14.34          135.10     1297.0          0.10030   \n",
       "\n",
       "   mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       "0           0.27760          0.3001              0.14710         0.2419   \n",
       "1           0.07864          0.0869              0.07017         0.1812   \n",
       "2           0.15990          0.1974              0.12790         0.2069   \n",
       "3           0.28390          0.2414              0.10520         0.2597   \n",
       "4           0.13280          0.1980              0.10430         0.1809   \n",
       "\n",
       "   mean fractal dimension  radius error  texture error  perimeter error  \\\n",
       "0                 0.07871        1.0950         0.9053            8.589   \n",
       "1                 0.05667        0.5435         0.7339            3.398   \n",
       "2                 0.05999        0.7456         0.7869            4.585   \n",
       "3                 0.09744        0.4956         1.1560            3.445   \n",
       "4                 0.05883        0.7572         0.7813            5.438   \n",
       "\n",
       "   area error  smoothness error  compactness error  concavity error  \\\n",
       "0      153.40          0.006399            0.04904          0.05373   \n",
       "1       74.08          0.005225            0.01308          0.01860   \n",
       "2       94.03          0.006150            0.04006          0.03832   \n",
       "3       27.23          0.009110            0.07458          0.05661   \n",
       "4       94.44          0.011490            0.02461          0.05688   \n",
       "\n",
       "   concave points error  symmetry error  fractal dimension error  \\\n",
       "0               0.01587         0.03003                 0.006193   \n",
       "1               0.01340         0.01389                 0.003532   \n",
       "2               0.02058         0.02250                 0.004571   \n",
       "3               0.01867         0.05963                 0.009208   \n",
       "4               0.01885         0.01756                 0.005115   \n",
       "\n",
       "   worst radius  worst texture  worst perimeter  worst area  worst smoothness  \\\n",
       "0         25.38          17.33           184.60      2019.0            0.1622   \n",
       "1         24.99          23.41           158.80      1956.0            0.1238   \n",
       "2         23.57          25.53           152.50      1709.0            0.1444   \n",
       "3         14.91          26.50            98.87       567.7            0.2098   \n",
       "4         22.54          16.67           152.20      1575.0            0.1374   \n",
       "\n",
       "   worst compactness  worst concavity  worst concave points  worst symmetry  \\\n",
       "0             0.6656           0.7119                0.2654          0.4601   \n",
       "1             0.1866           0.2416                0.1860          0.2750   \n",
       "2             0.4245           0.4504                0.2430          0.3613   \n",
       "3             0.8663           0.6869                0.2575          0.6638   \n",
       "4             0.2050           0.4000                0.1625          0.2364   \n",
       "\n",
       "   worst fractal dimension  outcome  \n",
       "0                  0.11890        1  \n",
       "1                  0.08902        1  \n",
       "2                  0.08758        1  \n",
       "3                  0.17300        1  \n",
       "4                  0.07678        1  "
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9. Extracting Month & Year as separate columns from Pandas Date column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(9994, 21)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>row_id</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_date</th>\n",
       "      <th>ship_date</th>\n",
       "      <th>ship_mode</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>customer_name</th>\n",
       "      <th>segment</th>\n",
       "      <th>country</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>postal_code</th>\n",
       "      <th>region</th>\n",
       "      <th>product_id</th>\n",
       "      <th>category</th>\n",
       "      <th>sub_category</th>\n",
       "      <th>product_name</th>\n",
       "      <th>sales</th>\n",
       "      <th>quantity</th>\n",
       "      <th>discount</th>\n",
       "      <th>profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>CA-2017-152156</td>\n",
       "      <td>2017-11-08</td>\n",
       "      <td>2017-11-11</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>CG-12520</td>\n",
       "      <td>Claire Gute</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>42420.0</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-BO-10001798</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Bookcases</td>\n",
       "      <td>Bush Somerset Collection Bookcase</td>\n",
       "      <td>261.9600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.9136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>CA-2017-152156</td>\n",
       "      <td>2017-11-08</td>\n",
       "      <td>2017-11-11</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>CG-12520</td>\n",
       "      <td>Claire Gute</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>42420.0</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-CH-10000454</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Chairs</td>\n",
       "      <td>Hon Deluxe Fabric Upholstered Stacking Chairs,...</td>\n",
       "      <td>731.9400</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>219.5820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>CA-2017-138688</td>\n",
       "      <td>2017-06-12</td>\n",
       "      <td>2017-06-16</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>DV-13045</td>\n",
       "      <td>Darrin Van Huff</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036.0</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-LA-10000240</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Labels</td>\n",
       "      <td>Self-Adhesive Address Labels for Typewriters b...</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.8714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>US-2016-108966</td>\n",
       "      <td>2016-10-11</td>\n",
       "      <td>2016-10-18</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SO-20335</td>\n",
       "      <td>Sean O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>Florida</td>\n",
       "      <td>33311.0</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-TA-10000577</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Tables</td>\n",
       "      <td>Bretford CR4500 Series Slim Rectangular Table</td>\n",
       "      <td>957.5775</td>\n",
       "      <td>5</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-383.0310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>US-2016-108966</td>\n",
       "      <td>2016-10-11</td>\n",
       "      <td>2016-10-18</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SO-20335</td>\n",
       "      <td>Sean O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>Florida</td>\n",
       "      <td>33311.0</td>\n",
       "      <td>South</td>\n",
       "      <td>OFF-ST-10000760</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Eldon Fold 'N Roll Cart System</td>\n",
       "      <td>22.3680</td>\n",
       "      <td>2</td>\n",
       "      <td>0.20</td>\n",
       "      <td>2.5164</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   row_id        order_id order_date  ship_date       ship_mode customer_id  \\\n",
       "0       1  CA-2017-152156 2017-11-08 2017-11-11    Second Class    CG-12520   \n",
       "1       2  CA-2017-152156 2017-11-08 2017-11-11    Second Class    CG-12520   \n",
       "2       3  CA-2017-138688 2017-06-12 2017-06-16    Second Class    DV-13045   \n",
       "3       4  US-2016-108966 2016-10-11 2016-10-18  Standard Class    SO-20335   \n",
       "4       5  US-2016-108966 2016-10-11 2016-10-18  Standard Class    SO-20335   \n",
       "\n",
       "     customer_name    segment        country             city       state  \\\n",
       "0      Claire Gute   Consumer  United States        Henderson    Kentucky   \n",
       "1      Claire Gute   Consumer  United States        Henderson    Kentucky   \n",
       "2  Darrin Van Huff  Corporate  United States      Los Angeles  California   \n",
       "3   Sean O'Donnell   Consumer  United States  Fort Lauderdale     Florida   \n",
       "4   Sean O'Donnell   Consumer  United States  Fort Lauderdale     Florida   \n",
       "\n",
       "   postal_code region       product_id         category sub_category  \\\n",
       "0      42420.0  South  FUR-BO-10001798        Furniture    Bookcases   \n",
       "1      42420.0  South  FUR-CH-10000454        Furniture       Chairs   \n",
       "2      90036.0   West  OFF-LA-10000240  Office Supplies       Labels   \n",
       "3      33311.0  South  FUR-TA-10000577        Furniture       Tables   \n",
       "4      33311.0  South  OFF-ST-10000760  Office Supplies      Storage   \n",
       "\n",
       "                                        product_name     sales  quantity  \\\n",
       "0                  Bush Somerset Collection Bookcase  261.9600         2   \n",
       "1  Hon Deluxe Fabric Upholstered Stacking Chairs,...  731.9400         3   \n",
       "2  Self-Adhesive Address Labels for Typewriters b...   14.6200         2   \n",
       "3      Bretford CR4500 Series Slim Rectangular Table  957.5775         5   \n",
       "4                     Eldon Fold 'N Roll Cart System   22.3680         2   \n",
       "\n",
       "   discount    profit  \n",
       "0      0.00   41.9136  \n",
       "1      0.00  219.5820  \n",
       "2      0.00    6.8714  \n",
       "3      0.45 -383.0310  \n",
       "4      0.20    2.5164  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(superstore_orders, parse_dates=['order_date','ship_date'])\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.order_date[0].year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>row_id</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_date</th>\n",
       "      <th>ship_date</th>\n",
       "      <th>ship_mode</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>customer_name</th>\n",
       "      <th>segment</th>\n",
       "      <th>country</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>postal_code</th>\n",
       "      <th>region</th>\n",
       "      <th>product_id</th>\n",
       "      <th>category</th>\n",
       "      <th>sub_category</th>\n",
       "      <th>product_name</th>\n",
       "      <th>sales</th>\n",
       "      <th>quantity</th>\n",
       "      <th>discount</th>\n",
       "      <th>profit</th>\n",
       "      <th>orderyear</th>\n",
       "      <th>ordermonth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>CA-2017-152156</td>\n",
       "      <td>2017-11-08</td>\n",
       "      <td>2017-11-11</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>CG-12520</td>\n",
       "      <td>Claire Gute</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>42420.0</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-BO-10001798</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Bookcases</td>\n",
       "      <td>Bush Somerset Collection Bookcase</td>\n",
       "      <td>261.9600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.9136</td>\n",
       "      <td>2017</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>CA-2017-152156</td>\n",
       "      <td>2017-11-08</td>\n",
       "      <td>2017-11-11</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>CG-12520</td>\n",
       "      <td>Claire Gute</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>42420.0</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-CH-10000454</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Chairs</td>\n",
       "      <td>Hon Deluxe Fabric Upholstered Stacking Chairs,...</td>\n",
       "      <td>731.9400</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>219.5820</td>\n",
       "      <td>2017</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>CA-2017-138688</td>\n",
       "      <td>2017-06-12</td>\n",
       "      <td>2017-06-16</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>DV-13045</td>\n",
       "      <td>Darrin Van Huff</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036.0</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-LA-10000240</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Labels</td>\n",
       "      <td>Self-Adhesive Address Labels for Typewriters b...</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.8714</td>\n",
       "      <td>2017</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>US-2016-108966</td>\n",
       "      <td>2016-10-11</td>\n",
       "      <td>2016-10-18</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SO-20335</td>\n",
       "      <td>Sean O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>Florida</td>\n",
       "      <td>33311.0</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-TA-10000577</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Tables</td>\n",
       "      <td>Bretford CR4500 Series Slim Rectangular Table</td>\n",
       "      <td>957.5775</td>\n",
       "      <td>5</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-383.0310</td>\n",
       "      <td>2016</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>US-2016-108966</td>\n",
       "      <td>2016-10-11</td>\n",
       "      <td>2016-10-18</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SO-20335</td>\n",
       "      <td>Sean O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>Florida</td>\n",
       "      <td>33311.0</td>\n",
       "      <td>South</td>\n",
       "      <td>OFF-ST-10000760</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Eldon Fold 'N Roll Cart System</td>\n",
       "      <td>22.3680</td>\n",
       "      <td>2</td>\n",
       "      <td>0.20</td>\n",
       "      <td>2.5164</td>\n",
       "      <td>2016</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   row_id        order_id order_date  ship_date       ship_mode customer_id  \\\n",
       "0       1  CA-2017-152156 2017-11-08 2017-11-11    Second Class    CG-12520   \n",
       "1       2  CA-2017-152156 2017-11-08 2017-11-11    Second Class    CG-12520   \n",
       "2       3  CA-2017-138688 2017-06-12 2017-06-16    Second Class    DV-13045   \n",
       "3       4  US-2016-108966 2016-10-11 2016-10-18  Standard Class    SO-20335   \n",
       "4       5  US-2016-108966 2016-10-11 2016-10-18  Standard Class    SO-20335   \n",
       "\n",
       "     customer_name    segment        country             city       state  \\\n",
       "0      Claire Gute   Consumer  United States        Henderson    Kentucky   \n",
       "1      Claire Gute   Consumer  United States        Henderson    Kentucky   \n",
       "2  Darrin Van Huff  Corporate  United States      Los Angeles  California   \n",
       "3   Sean O'Donnell   Consumer  United States  Fort Lauderdale     Florida   \n",
       "4   Sean O'Donnell   Consumer  United States  Fort Lauderdale     Florida   \n",
       "\n",
       "   postal_code region       product_id         category sub_category  \\\n",
       "0      42420.0  South  FUR-BO-10001798        Furniture    Bookcases   \n",
       "1      42420.0  South  FUR-CH-10000454        Furniture       Chairs   \n",
       "2      90036.0   West  OFF-LA-10000240  Office Supplies       Labels   \n",
       "3      33311.0  South  FUR-TA-10000577        Furniture       Tables   \n",
       "4      33311.0  South  OFF-ST-10000760  Office Supplies      Storage   \n",
       "\n",
       "                                        product_name     sales  quantity  \\\n",
       "0                  Bush Somerset Collection Bookcase  261.9600         2   \n",
       "1  Hon Deluxe Fabric Upholstered Stacking Chairs,...  731.9400         3   \n",
       "2  Self-Adhesive Address Labels for Typewriters b...   14.6200         2   \n",
       "3      Bretford CR4500 Series Slim Rectangular Table  957.5775         5   \n",
       "4                     Eldon Fold 'N Roll Cart System   22.3680         2   \n",
       "\n",
       "   discount    profit  orderyear  ordermonth  \n",
       "0      0.00   41.9136       2017          11  \n",
       "1      0.00  219.5820       2017          11  \n",
       "2      0.00    6.8714       2017           6  \n",
       "3      0.45 -383.0310       2016          10  \n",
       "4      0.20    2.5164       2016          10  "
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['orderyear'] = data.order_date.apply(lambda x: x.year)\n",
    "data['ordermonth'] = data.order_date.apply(lambda x: x.month)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>orderyear</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Furniture</th>\n",
       "      <td>157192.8531</td>\n",
       "      <td>170518.237</td>\n",
       "      <td>198901.436</td>\n",
       "      <td>215387.2692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Office Supplies</th>\n",
       "      <td>151776.4120</td>\n",
       "      <td>137233.463</td>\n",
       "      <td>183939.982</td>\n",
       "      <td>246097.1750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technology</th>\n",
       "      <td>175278.2330</td>\n",
       "      <td>162780.809</td>\n",
       "      <td>226364.180</td>\n",
       "      <td>271730.8110</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "orderyear               2015        2016        2017         2018\n",
       "category                                                         \n",
       "Furniture        157192.8531  170518.237  198901.436  215387.2692\n",
       "Office Supplies  151776.4120  137233.463  183939.982  246097.1750\n",
       "Technology       175278.2330  162780.809  226364.180  271730.8110"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.pivot_table(columns='orderyear',index=\"category\",values=\"sales\",aggfunc='sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 10.\tPercentage change function in Pandas DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">profit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orderyear</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Furniture</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-44.753489</td>\n",
       "      <td>130.828682</td>\n",
       "      <td>-56.632017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Office Supplies</th>\n",
       "      <td>NaN</td>\n",
       "      <td>11.092248</td>\n",
       "      <td>39.688767</td>\n",
       "      <td>13.334936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technology</th>\n",
       "      <td>NaN</td>\n",
       "      <td>55.883907</td>\n",
       "      <td>18.714631</td>\n",
       "      <td>27.430650</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                profit                                  \n",
       "orderyear         2015       2016        2017       2018\n",
       "category                                                \n",
       "Furniture          NaN -44.753489  130.828682 -56.632017\n",
       "Office Supplies    NaN  11.092248   39.688767  13.334936\n",
       "Technology         NaN  55.883907   18.714631  27.430650"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.pivot_table(columns='orderyear',index=\"category\",values=['profit'],aggfunc='sum').pct_change(axis=1)*100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PART - 2 (11 to 20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 11.\tCorrelation Matrix Plot Pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean radius</th>\n",
       "      <th>mean texture</th>\n",
       "      <th>mean perimeter</th>\n",
       "      <th>mean area</th>\n",
       "      <th>mean smoothness</th>\n",
       "      <th>mean compactness</th>\n",
       "      <th>mean concavity</th>\n",
       "      <th>mean concave points</th>\n",
       "      <th>mean symmetry</th>\n",
       "      <th>mean fractal dimension</th>\n",
       "      <th>radius error</th>\n",
       "      <th>texture error</th>\n",
       "      <th>perimeter error</th>\n",
       "      <th>area error</th>\n",
       "      <th>smoothness error</th>\n",
       "      <th>compactness error</th>\n",
       "      <th>concavity error</th>\n",
       "      <th>concave points error</th>\n",
       "      <th>symmetry error</th>\n",
       "      <th>fractal dimension error</th>\n",
       "      <th>worst radius</th>\n",
       "      <th>worst texture</th>\n",
       "      <th>worst perimeter</th>\n",
       "      <th>worst area</th>\n",
       "      <th>worst smoothness</th>\n",
       "      <th>worst compactness</th>\n",
       "      <th>worst concavity</th>\n",
       "      <th>worst concave points</th>\n",
       "      <th>worst symmetry</th>\n",
       "      <th>worst fractal dimension</th>\n",
       "      <th>outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>1.0950</td>\n",
       "      <td>0.9053</td>\n",
       "      <td>8.589</td>\n",
       "      <td>153.40</td>\n",
       "      <td>0.006399</td>\n",
       "      <td>0.04904</td>\n",
       "      <td>0.05373</td>\n",
       "      <td>0.01587</td>\n",
       "      <td>0.03003</td>\n",
       "      <td>0.006193</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.7339</td>\n",
       "      <td>3.398</td>\n",
       "      <td>74.08</td>\n",
       "      <td>0.005225</td>\n",
       "      <td>0.01308</td>\n",
       "      <td>0.01860</td>\n",
       "      <td>0.01340</td>\n",
       "      <td>0.01389</td>\n",
       "      <td>0.003532</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>0.7456</td>\n",
       "      <td>0.7869</td>\n",
       "      <td>4.585</td>\n",
       "      <td>94.03</td>\n",
       "      <td>0.006150</td>\n",
       "      <td>0.04006</td>\n",
       "      <td>0.03832</td>\n",
       "      <td>0.02058</td>\n",
       "      <td>0.02250</td>\n",
       "      <td>0.004571</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>0.4956</td>\n",
       "      <td>1.1560</td>\n",
       "      <td>3.445</td>\n",
       "      <td>27.23</td>\n",
       "      <td>0.009110</td>\n",
       "      <td>0.07458</td>\n",
       "      <td>0.05661</td>\n",
       "      <td>0.01867</td>\n",
       "      <td>0.05963</td>\n",
       "      <td>0.009208</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>0.7572</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>5.438</td>\n",
       "      <td>94.44</td>\n",
       "      <td>0.011490</td>\n",
       "      <td>0.02461</td>\n",
       "      <td>0.05688</td>\n",
       "      <td>0.01885</td>\n",
       "      <td>0.01756</td>\n",
       "      <td>0.005115</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       "0        17.99         10.38          122.80     1001.0          0.11840   \n",
       "1        20.57         17.77          132.90     1326.0          0.08474   \n",
       "2        19.69         21.25          130.00     1203.0          0.10960   \n",
       "3        11.42         20.38           77.58      386.1          0.14250   \n",
       "4        20.29         14.34          135.10     1297.0          0.10030   \n",
       "\n",
       "   mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       "0           0.27760          0.3001              0.14710         0.2419   \n",
       "1           0.07864          0.0869              0.07017         0.1812   \n",
       "2           0.15990          0.1974              0.12790         0.2069   \n",
       "3           0.28390          0.2414              0.10520         0.2597   \n",
       "4           0.13280          0.1980              0.10430         0.1809   \n",
       "\n",
       "   mean fractal dimension  radius error  texture error  perimeter error  \\\n",
       "0                 0.07871        1.0950         0.9053            8.589   \n",
       "1                 0.05667        0.5435         0.7339            3.398   \n",
       "2                 0.05999        0.7456         0.7869            4.585   \n",
       "3                 0.09744        0.4956         1.1560            3.445   \n",
       "4                 0.05883        0.7572         0.7813            5.438   \n",
       "\n",
       "   area error  smoothness error  compactness error  concavity error  \\\n",
       "0      153.40          0.006399            0.04904          0.05373   \n",
       "1       74.08          0.005225            0.01308          0.01860   \n",
       "2       94.03          0.006150            0.04006          0.03832   \n",
       "3       27.23          0.009110            0.07458          0.05661   \n",
       "4       94.44          0.011490            0.02461          0.05688   \n",
       "\n",
       "   concave points error  symmetry error  fractal dimension error  \\\n",
       "0               0.01587         0.03003                 0.006193   \n",
       "1               0.01340         0.01389                 0.003532   \n",
       "2               0.02058         0.02250                 0.004571   \n",
       "3               0.01867         0.05963                 0.009208   \n",
       "4               0.01885         0.01756                 0.005115   \n",
       "\n",
       "   worst radius  worst texture  worst perimeter  worst area  worst smoothness  \\\n",
       "0         25.38          17.33           184.60      2019.0            0.1622   \n",
       "1         24.99          23.41           158.80      1956.0            0.1238   \n",
       "2         23.57          25.53           152.50      1709.0            0.1444   \n",
       "3         14.91          26.50            98.87       567.7            0.2098   \n",
       "4         22.54          16.67           152.20      1575.0            0.1374   \n",
       "\n",
       "   worst compactness  worst concavity  worst concave points  worst symmetry  \\\n",
       "0             0.6656           0.7119                0.2654          0.4601   \n",
       "1             0.1866           0.2416                0.1860          0.2750   \n",
       "2             0.4245           0.4504                0.2430          0.3613   \n",
       "3             0.8663           0.6869                0.2575          0.6638   \n",
       "4             0.2050           0.4000                0.1625          0.2364   \n",
       "\n",
       "   worst fractal dimension  outcome  \n",
       "0                  0.11890        1  \n",
       "1                  0.08902        1  \n",
       "2                  0.08758        1  \n",
       "3                  0.17300        1  \n",
       "4                  0.07678        1  "
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(breast_cancer)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col0 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col1 {\n",
       "            background-color:  #b7cff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col2 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col3 {\n",
       "            background-color:  #b70d28;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col4 {\n",
       "            background-color:  #779af7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col5 {\n",
       "            background-color:  #d8dce2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col6 {\n",
       "            background-color:  #f6bda2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col7 {\n",
       "            background-color:  #ea7b60;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col8 {\n",
       "            background-color:  #5470de;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col10 {\n",
       "            background-color:  #f7b497;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col11 {\n",
       "            background-color:  #4358cb;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col12 {\n",
       "            background-color:  #f7b99e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col13 {\n",
       "            background-color:  #f39778;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col14 {\n",
       "            background-color:  #3c4ec2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col15 {\n",
       "            background-color:  #506bda;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col16 {\n",
       "            background-color:  #5a78e4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col17 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col18 {\n",
       "            background-color:  #4055c8;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col19 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col20 {\n",
       "            background-color:  #bd1f2d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col21 {\n",
       "            background-color:  #aec9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col22 {\n",
       "            background-color:  #be242e;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col23 {\n",
       "            background-color:  #c53334;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col24 {\n",
       "            background-color:  #7597f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col25 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col26 {\n",
       "            background-color:  #ead4c8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col27 {\n",
       "            background-color:  #f29072;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col28 {\n",
       "            background-color:  #90b2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col29 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col30 {\n",
       "            background-color:  #f49a7b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col0 {\n",
       "            background-color:  #d9dce1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col1 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col2 {\n",
       "            background-color:  #d4dbe6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col3 {\n",
       "            background-color:  #d5dbe5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col5 {\n",
       "            background-color:  #7b9ff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col6 {\n",
       "            background-color:  #8badfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col7 {\n",
       "            background-color:  #97b8ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col9 {\n",
       "            background-color:  #7396f5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col10 {\n",
       "            background-color:  #96b7ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col11 {\n",
       "            background-color:  #d1dae9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col12 {\n",
       "            background-color:  #8db0fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col13 {\n",
       "            background-color:  #a6c4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col14 {\n",
       "            background-color:  #799cf8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col15 {\n",
       "            background-color:  #4b64d5;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col16 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col17 {\n",
       "            background-color:  #5470de;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col18 {\n",
       "            background-color:  #6180e9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col19 {\n",
       "            background-color:  #5673e0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col20 {\n",
       "            background-color:  #d8dce2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col21 {\n",
       "            background-color:  #d0473d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col22 {\n",
       "            background-color:  #d5dbe5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col23 {\n",
       "            background-color:  #d4dbe6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col24 {\n",
       "            background-color:  #6788ee;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col25 {\n",
       "            background-color:  #abc8fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col26 {\n",
       "            background-color:  #aec9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col27 {\n",
       "            background-color:  #b6cefa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col28 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col29 {\n",
       "            background-color:  #6c8ff1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col30 {\n",
       "            background-color:  #cfdaea;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col0 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col1 {\n",
       "            background-color:  #b9d0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col2 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col3 {\n",
       "            background-color:  #b70d28;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col4 {\n",
       "            background-color:  #84a7fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col5 {\n",
       "            background-color:  #e6d7cf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col6 {\n",
       "            background-color:  #f7af91;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col7 {\n",
       "            background-color:  #e36c55;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col8 {\n",
       "            background-color:  #5f7fe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col9 {\n",
       "            background-color:  #455cce;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col10 {\n",
       "            background-color:  #f7af91;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col11 {\n",
       "            background-color:  #455cce;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col12 {\n",
       "            background-color:  #f7b396;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col13 {\n",
       "            background-color:  #f29274;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col14 {\n",
       "            background-color:  #4055c8;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col15 {\n",
       "            background-color:  #6282ea;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col16 {\n",
       "            background-color:  #6788ee;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col17 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col18 {\n",
       "            background-color:  #465ecf;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col19 {\n",
       "            background-color:  #455cce;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col20 {\n",
       "            background-color:  #bd1f2d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col21 {\n",
       "            background-color:  #b1cbfc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col22 {\n",
       "            background-color:  #bd1f2d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col23 {\n",
       "            background-color:  #c53334;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col24 {\n",
       "            background-color:  #7ea1fa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col25 {\n",
       "            background-color:  #dddcdc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col26 {\n",
       "            background-color:  #f1cdba;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col27 {\n",
       "            background-color:  #ee8669;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col28 {\n",
       "            background-color:  #98b9ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col29 {\n",
       "            background-color:  #5673e0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col30 {\n",
       "            background-color:  #f39577;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col0 {\n",
       "            background-color:  #b70d28;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col1 {\n",
       "            background-color:  #b6cefa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col2 {\n",
       "            background-color:  #b70d28;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col3 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col4 {\n",
       "            background-color:  #7a9df8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col5 {\n",
       "            background-color:  #d6dce4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col6 {\n",
       "            background-color:  #f7ba9f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col7 {\n",
       "            background-color:  #ea7b60;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col8 {\n",
       "            background-color:  #5572df;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col9 {\n",
       "            background-color:  #4055c8;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col10 {\n",
       "            background-color:  #f5a081;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col11 {\n",
       "            background-color:  #4b64d5;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col12 {\n",
       "            background-color:  #f7a688;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col13 {\n",
       "            background-color:  #ea7b60;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col14 {\n",
       "            background-color:  #4a63d3;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col15 {\n",
       "            background-color:  #536edd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col16 {\n",
       "            background-color:  #5f7fe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col17 {\n",
       "            background-color:  #a3c2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col18 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col19 {\n",
       "            background-color:  #4055c8;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col20 {\n",
       "            background-color:  #be242e;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col21 {\n",
       "            background-color:  #abc8fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col22 {\n",
       "            background-color:  #c0282f;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col23 {\n",
       "            background-color:  #c0282f;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col24 {\n",
       "            background-color:  #7699f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col25 {\n",
       "            background-color:  #cdd9ec;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col26 {\n",
       "            background-color:  #e8d6cc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col27 {\n",
       "            background-color:  #f4987a;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col28 {\n",
       "            background-color:  #89acfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col29 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col30 {\n",
       "            background-color:  #f6a283;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col0 {\n",
       "            background-color:  #b6cefa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col1 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col2 {\n",
       "            background-color:  #b7cff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col3 {\n",
       "            background-color:  #b2ccfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col4 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col5 {\n",
       "            background-color:  #f6bfa6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col6 {\n",
       "            background-color:  #d8dce2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col7 {\n",
       "            background-color:  #e8d6cc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col8 {\n",
       "            background-color:  #e3d9d3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col9 {\n",
       "            background-color:  #f7b396;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col10 {\n",
       "            background-color:  #9fbfff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col11 {\n",
       "            background-color:  #7295f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col12 {\n",
       "            background-color:  #93b5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col13 {\n",
       "            background-color:  #a2c1ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col14 {\n",
       "            background-color:  #d2dbe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col15 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col16 {\n",
       "            background-color:  #6f92f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col17 {\n",
       "            background-color:  #a6c4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col18 {\n",
       "            background-color:  #9bbcff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col19 {\n",
       "            background-color:  #a3c2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col20 {\n",
       "            background-color:  #b7cff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col21 {\n",
       "            background-color:  #5a78e4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col22 {\n",
       "            background-color:  #b7cff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col23 {\n",
       "            background-color:  #b2ccfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col24 {\n",
       "            background-color:  #ea7b60;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col25 {\n",
       "            background-color:  #e1dad6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col26 {\n",
       "            background-color:  #d5dbe5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col27 {\n",
       "            background-color:  #ead4c8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col28 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col29 {\n",
       "            background-color:  #e2dad5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col30 {\n",
       "            background-color:  #c0d4f5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col0 {\n",
       "            background-color:  #f4c5ad;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col1 {\n",
       "            background-color:  #9bbcff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col2 {\n",
       "            background-color:  #f6bda2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col3 {\n",
       "            background-color:  #f2c9b4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col4 {\n",
       "            background-color:  #f7b89c;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col5 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col6 {\n",
       "            background-color:  #de614d;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col7 {\n",
       "            background-color:  #e9785d;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col8 {\n",
       "            background-color:  #edd1c2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col9 {\n",
       "            background-color:  #f7b79b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col10 {\n",
       "            background-color:  #dcdddd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col11 {\n",
       "            background-color:  #6b8df0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col12 {\n",
       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col13 {\n",
       "            background-color:  #dddcdc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col14 {\n",
       "            background-color:  #9ebeff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col15 {\n",
       "            background-color:  #f7af91;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col16 {\n",
       "            background-color:  #e2dad5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col17 {\n",
       "            background-color:  #f2c9b4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col18 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col19 {\n",
       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col20 {\n",
       "            background-color:  #f5c2aa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col21 {\n",
       "            background-color:  #9fbfff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col22 {\n",
       "            background-color:  #f7b99e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col23 {\n",
       "            background-color:  #f2cab5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col24 {\n",
       "            background-color:  #f1ccb8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col25 {\n",
       "            background-color:  #dd5f4b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col26 {\n",
       "            background-color:  #e8765c;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col27 {\n",
       "            background-color:  #e7745b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col28 {\n",
       "            background-color:  #ecd3c5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col29 {\n",
       "            background-color:  #f7ac8e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col30 {\n",
       "            background-color:  #f4c5ad;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col0 {\n",
       "            background-color:  #f4987a;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col1 {\n",
       "            background-color:  #b1cbfc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col2 {\n",
       "            background-color:  #f18f71;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col3 {\n",
       "            background-color:  #f39778;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col4 {\n",
       "            background-color:  #e5d8d1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col5 {\n",
       "            background-color:  #dd5f4b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col6 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col7 {\n",
       "            background-color:  #d0473d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col8 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col9 {\n",
       "            background-color:  #dbdcde;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col10 {\n",
       "            background-color:  #f5c2aa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col11 {\n",
       "            background-color:  #7597f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col12 {\n",
       "            background-color:  #f6bea4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col13 {\n",
       "            background-color:  #f6bda2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col14 {\n",
       "            background-color:  #93b5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col15 {\n",
       "            background-color:  #f3c7b1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col16 {\n",
       "            background-color:  #f7ba9f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col17 {\n",
       "            background-color:  #f7bca1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col18 {\n",
       "            background-color:  #94b6ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col19 {\n",
       "            background-color:  #d5dbe5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col20 {\n",
       "            background-color:  #f4987a;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col21 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col22 {\n",
       "            background-color:  #f18d6f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col23 {\n",
       "            background-color:  #f59f80;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col24 {\n",
       "            background-color:  #d9dce1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col25 {\n",
       "            background-color:  #f18f71;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col26 {\n",
       "            background-color:  #d85646;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col27 {\n",
       "            background-color:  #dd5f4b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col28 {\n",
       "            background-color:  #d7dce3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col29 {\n",
       "            background-color:  #e6d7cf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col30 {\n",
       "            background-color:  #f7a688;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col0 {\n",
       "            background-color:  #e0654f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col1 {\n",
       "            background-color:  #adc9fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col2 {\n",
       "            background-color:  #dc5d4a;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col3 {\n",
       "            background-color:  #e16751;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col4 {\n",
       "            background-color:  #ecd3c5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col5 {\n",
       "            background-color:  #e97a5f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col6 {\n",
       "            background-color:  #d1493f;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col7 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col8 {\n",
       "            background-color:  #c6d6f1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col9 {\n",
       "            background-color:  #b5cdfa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col10 {\n",
       "            background-color:  #f7ad90;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col11 {\n",
       "            background-color:  #6384eb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col12 {\n",
       "            background-color:  #f7ad90;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col13 {\n",
       "            background-color:  #f7a688;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col14 {\n",
       "            background-color:  #7ea1fa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col15 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col16 {\n",
       "            background-color:  #b9d0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col17 {\n",
       "            background-color:  #efcfbf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col18 {\n",
       "            background-color:  #7a9df8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col19 {\n",
       "            background-color:  #9abbff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col20 {\n",
       "            background-color:  #e0654f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col21 {\n",
       "            background-color:  #adc9fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col22 {\n",
       "            background-color:  #dc5d4a;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col23 {\n",
       "            background-color:  #e46e56;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col24 {\n",
       "            background-color:  #dadce0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col25 {\n",
       "            background-color:  #f7ad90;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col26 {\n",
       "            background-color:  #f29274;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col27 {\n",
       "            background-color:  #d0473d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col28 {\n",
       "            background-color:  #cedaeb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col29 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col30 {\n",
       "            background-color:  #ef886b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col0 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col1 {\n",
       "            background-color:  #6687ed;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col2 {\n",
       "            background-color:  #b1cbfc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col3 {\n",
       "            background-color:  #abc8fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col4 {\n",
       "            background-color:  #edd2c3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col5 {\n",
       "            background-color:  #efcebd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col6 {\n",
       "            background-color:  #d2dbe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col7 {\n",
       "            background-color:  #cfdaea;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col8 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col9 {\n",
       "            background-color:  #f2cab5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col10 {\n",
       "            background-color:  #9fbfff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col11 {\n",
       "            background-color:  #85a8fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col12 {\n",
       "            background-color:  #9abbff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col13 {\n",
       "            background-color:  #9abbff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col14 {\n",
       "            background-color:  #abc8fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col15 {\n",
       "            background-color:  #a7c5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col16 {\n",
       "            background-color:  #93b5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col17 {\n",
       "            background-color:  #aac7fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col18 {\n",
       "            background-color:  #dfdbd9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col19 {\n",
       "            background-color:  #b2ccfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col20 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col21 {\n",
       "            background-color:  #6b8df0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col22 {\n",
       "            background-color:  #b2ccfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col23 {\n",
       "            background-color:  #aac7fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col24 {\n",
       "            background-color:  #d4dbe6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col25 {\n",
       "            background-color:  #e1dad6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col26 {\n",
       "            background-color:  #d5dbe5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col27 {\n",
       "            background-color:  #dadce0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col28 {\n",
       "            background-color:  #f5a081;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col29 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col30 {\n",
       "            background-color:  #b7cff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col4 {\n",
       "            background-color:  #f1ccb8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col5 {\n",
       "            background-color:  #e8d6cc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col6 {\n",
       "            background-color:  #98b9ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col7 {\n",
       "            background-color:  #6a8bef;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col8 {\n",
       "            background-color:  #ccd9ed;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col9 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col11 {\n",
       "            background-color:  #90b2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col13 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col14 {\n",
       "            background-color:  #e0dbd8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col15 {\n",
       "            background-color:  #d9dce1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col16 {\n",
       "            background-color:  #bbd1f8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col17 {\n",
       "            background-color:  #97b8ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col18 {\n",
       "            background-color:  #c6d6f1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col19 {\n",
       "            background-color:  #f7ac8e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col20 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col21 {\n",
       "            background-color:  #4257c9;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col22 {\n",
       "            background-color:  #3d50c3;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col23 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col24 {\n",
       "            background-color:  #e6d7cf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col25 {\n",
       "            background-color:  #dedcdb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col26 {\n",
       "            background-color:  #bcd2f7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col27 {\n",
       "            background-color:  #92b4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col28 {\n",
       "            background-color:  #c3d5f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col29 {\n",
       "            background-color:  #f18d6f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col30 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col0 {\n",
       "            background-color:  #f39778;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col1 {\n",
       "            background-color:  #a7c5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col2 {\n",
       "            background-color:  #f39778;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col3 {\n",
       "            background-color:  #ef886b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col4 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col5 {\n",
       "            background-color:  #d6dce4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col6 {\n",
       "            background-color:  #f2cbb7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col7 {\n",
       "            background-color:  #f7af91;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col8 {\n",
       "            background-color:  #8caffe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col9 {\n",
       "            background-color:  #88abfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col10 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col11 {\n",
       "            background-color:  #9fbfff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col12 {\n",
       "            background-color:  #be242e;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col13 {\n",
       "            background-color:  #c43032;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col14 {\n",
       "            background-color:  #a6c4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col15 {\n",
       "            background-color:  #8caffe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col16 {\n",
       "            background-color:  #90b2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col17 {\n",
       "            background-color:  #d4dbe6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col18 {\n",
       "            background-color:  #a7c5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col19 {\n",
       "            background-color:  #90b2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col20 {\n",
       "            background-color:  #f29072;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col21 {\n",
       "            background-color:  #8db0fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col22 {\n",
       "            background-color:  #f29072;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col23 {\n",
       "            background-color:  #ee8468;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col24 {\n",
       "            background-color:  #7b9ff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col25 {\n",
       "            background-color:  #aec9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col26 {\n",
       "            background-color:  #c6d6f1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col27 {\n",
       "            background-color:  #efcfbf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col28 {\n",
       "            background-color:  #7a9df8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col29 {\n",
       "            background-color:  #5673e0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col30 {\n",
       "            background-color:  #f1ccb8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col0 {\n",
       "            background-color:  #6e90f2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col1 {\n",
       "            background-color:  #cad8ef;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col2 {\n",
       "            background-color:  #6687ed;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col3 {\n",
       "            background-color:  #7093f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col4 {\n",
       "            background-color:  #5572df;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col8 {\n",
       "            background-color:  #4c66d6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col9 {\n",
       "            background-color:  #b3cdfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col10 {\n",
       "            background-color:  #80a3fa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col11 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col12 {\n",
       "            background-color:  #779af7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col13 {\n",
       "            background-color:  #7699f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col14 {\n",
       "            background-color:  #dfdbd9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col15 {\n",
       "            background-color:  #5a78e4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col16 {\n",
       "            background-color:  #5a78e4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col17 {\n",
       "            background-color:  #6c8ff1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col18 {\n",
       "            background-color:  #d7dce3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col19 {\n",
       "            background-color:  #a2c1ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col20 {\n",
       "            background-color:  #5d7ce6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col21 {\n",
       "            background-color:  #cfdaea;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col22 {\n",
       "            background-color:  #5875e1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col23 {\n",
       "            background-color:  #5f7fe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col24 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col25 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col26 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col27 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col28 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col29 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col30 {\n",
       "            background-color:  #4b64d5;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col0 {\n",
       "            background-color:  #f4987a;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col1 {\n",
       "            background-color:  #aac7fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col2 {\n",
       "            background-color:  #f39778;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col3 {\n",
       "            background-color:  #f08a6c;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col4 {\n",
       "            background-color:  #a2c1ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col5 {\n",
       "            background-color:  #e3d9d3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col6 {\n",
       "            background-color:  #f5c2aa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col7 {\n",
       "            background-color:  #f7aa8c;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col8 {\n",
       "            background-color:  #90b2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col9 {\n",
       "            background-color:  #93b5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col10 {\n",
       "            background-color:  #bd1f2d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col11 {\n",
       "            background-color:  #a2c1ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col12 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col13 {\n",
       "            background-color:  #c83836;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col14 {\n",
       "            background-color:  #a2c1ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col15 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col16 {\n",
       "            background-color:  #9bbcff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col17 {\n",
       "            background-color:  #e0dbd8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col18 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col19 {\n",
       "            background-color:  #96b7ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col20 {\n",
       "            background-color:  #f39577;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col21 {\n",
       "            background-color:  #90b2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col22 {\n",
       "            background-color:  #f29072;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col23 {\n",
       "            background-color:  #f08b6e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col24 {\n",
       "            background-color:  #779af7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col25 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col26 {\n",
       "            background-color:  #d1dae9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col27 {\n",
       "            background-color:  #f2cab5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col28 {\n",
       "            background-color:  #80a3fa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col29 {\n",
       "            background-color:  #6282ea;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col30 {\n",
       "            background-color:  #efcebd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col0 {\n",
       "            background-color:  #ee8468;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col1 {\n",
       "            background-color:  #a2c1ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col2 {\n",
       "            background-color:  #ee8468;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col3 {\n",
       "            background-color:  #e46e56;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col4 {\n",
       "            background-color:  #92b4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col5 {\n",
       "            background-color:  #c9d7f0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col6 {\n",
       "            background-color:  #efcebd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col7 {\n",
       "            background-color:  #f7b396;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col8 {\n",
       "            background-color:  #6f92f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col9 {\n",
       "            background-color:  #7093f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col10 {\n",
       "            background-color:  #c53334;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col11 {\n",
       "            background-color:  #80a3fa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col12 {\n",
       "            background-color:  #cb3e38;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col13 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col14 {\n",
       "            background-color:  #8caffe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col15 {\n",
       "            background-color:  #6f92f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col16 {\n",
       "            background-color:  #779af7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col17 {\n",
       "            background-color:  #b3cdfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col18 {\n",
       "            background-color:  #86a9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col19 {\n",
       "            background-color:  #6e90f2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col20 {\n",
       "            background-color:  #ec8165;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col21 {\n",
       "            background-color:  #8fb1fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col22 {\n",
       "            background-color:  #ed8366;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col23 {\n",
       "            background-color:  #e46e56;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col24 {\n",
       "            background-color:  #7699f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col25 {\n",
       "            background-color:  #aec9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col26 {\n",
       "            background-color:  #c7d7f0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col27 {\n",
       "            background-color:  #f0cdbb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col28 {\n",
       "            background-color:  #7396f5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col29 {\n",
       "            background-color:  #4c66d6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col30 {\n",
       "            background-color:  #eed0c0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col0 {\n",
       "            background-color:  #4f69d9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col1 {\n",
       "            background-color:  #516ddb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col2 {\n",
       "            background-color:  #485fd1;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col3 {\n",
       "            background-color:  #5673e0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col4 {\n",
       "            background-color:  #aec9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col5 {\n",
       "            background-color:  #5673e0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col6 {\n",
       "            background-color:  #4257c9;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col7 {\n",
       "            background-color:  #3c4ec2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col8 {\n",
       "            background-color:  #6180e9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col9 {\n",
       "            background-color:  #e8d6cc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col10 {\n",
       "            background-color:  #6f92f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col11 {\n",
       "            background-color:  #d4dbe6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col12 {\n",
       "            background-color:  #5e7de7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col13 {\n",
       "            background-color:  #6a8bef;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col14 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col15 {\n",
       "            background-color:  #84a7fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col16 {\n",
       "            background-color:  #7699f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col17 {\n",
       "            background-color:  #92b4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col18 {\n",
       "            background-color:  #d7dce3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col19 {\n",
       "            background-color:  #cfdaea;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col20 {\n",
       "            background-color:  #3f53c6;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col21 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col22 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col23 {\n",
       "            background-color:  #465ecf;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col24 {\n",
       "            background-color:  #b3cdfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col25 {\n",
       "            background-color:  #445acc;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col26 {\n",
       "            background-color:  #3d50c3;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col27 {\n",
       "            background-color:  #3f53c6;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col28 {\n",
       "            background-color:  #3f53c6;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col29 {\n",
       "            background-color:  #6788ee;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col30 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col0 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col1 {\n",
       "            background-color:  #8caffe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col2 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col3 {\n",
       "            background-color:  #bbd1f8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col4 {\n",
       "            background-color:  #aac7fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col5 {\n",
       "            background-color:  #f6a385;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col6 {\n",
       "            background-color:  #f6bfa6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col7 {\n",
       "            background-color:  #d7dce3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col8 {\n",
       "            background-color:  #b9d0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col9 {\n",
       "            background-color:  #f7b89c;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col10 {\n",
       "            background-color:  #b2ccfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col11 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col12 {\n",
       "            background-color:  #bed2f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col13 {\n",
       "            background-color:  #aec9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col14 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col15 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col16 {\n",
       "            background-color:  #f18d6f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col17 {\n",
       "            background-color:  #f6a586;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col18 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col19 {\n",
       "            background-color:  #ec7f63;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col20 {\n",
       "            background-color:  #b5cdfa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col21 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col22 {\n",
       "            background-color:  #bed2f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col23 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col24 {\n",
       "            background-color:  #97b8ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col25 {\n",
       "            background-color:  #f7aa8c;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col26 {\n",
       "            background-color:  #f7b99e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col27 {\n",
       "            background-color:  #e6d7cf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col28 {\n",
       "            background-color:  #b3cdfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col29 {\n",
       "            background-color:  #f2c9b4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col30 {\n",
       "            background-color:  #abc8fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col0 {\n",
       "            background-color:  #bbd1f8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col1 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col2 {\n",
       "            background-color:  #bcd2f7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col3 {\n",
       "            background-color:  #bad0f8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col4 {\n",
       "            background-color:  #92b4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col5 {\n",
       "            background-color:  #e9d5cb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col6 {\n",
       "            background-color:  #f7b89c;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col7 {\n",
       "            background-color:  #c9d7f0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col8 {\n",
       "            background-color:  #9bbcff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col9 {\n",
       "            background-color:  #eed0c0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col10 {\n",
       "            background-color:  #aac7fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col11 {\n",
       "            background-color:  #9abbff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col12 {\n",
       "            background-color:  #abc8fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col13 {\n",
       "            background-color:  #a9c6fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col14 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col15 {\n",
       "            background-color:  #f29274;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col16 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col17 {\n",
       "            background-color:  #f4987a;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col18 {\n",
       "            background-color:  #bcd2f7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col19 {\n",
       "            background-color:  #f59d7e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col20 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col21 {\n",
       "            background-color:  #6f92f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col22 {\n",
       "            background-color:  #b5cdfa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col23 {\n",
       "            background-color:  #adc9fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col24 {\n",
       "            background-color:  #84a7fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col25 {\n",
       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col26 {\n",
       "            background-color:  #f7b194;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col27 {\n",
       "            background-color:  #dddcdc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col28 {\n",
       "            background-color:  #9abbff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col29 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col30 {\n",
       "            background-color:  #9ebeff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col0 {\n",
       "            background-color:  #e3d9d3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col1 {\n",
       "            background-color:  #84a7fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col2 {\n",
       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col3 {\n",
       "            background-color:  #dfdbd9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col4 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col5 {\n",
       "            background-color:  #f4c5ad;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col6 {\n",
       "            background-color:  #f7ba9f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col7 {\n",
       "            background-color:  #f2c9b4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col8 {\n",
       "            background-color:  #aec9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col9 {\n",
       "            background-color:  #dcdddd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col10 {\n",
       "            background-color:  #e0dbd8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col11 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col12 {\n",
       "            background-color:  #e6d7cf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col13 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col14 {\n",
       "            background-color:  #d1dae9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col15 {\n",
       "            background-color:  #f7ac8e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col16 {\n",
       "            background-color:  #f49a7b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col17 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col18 {\n",
       "            background-color:  #bed2f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col19 {\n",
       "            background-color:  #f5c4ac;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col20 {\n",
       "            background-color:  #d9dce1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col21 {\n",
       "            background-color:  #6b8df0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col22 {\n",
       "            background-color:  #dddcdc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col23 {\n",
       "            background-color:  #d4dbe6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col24 {\n",
       "            background-color:  #93b5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col25 {\n",
       "            background-color:  #dcdddd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col26 {\n",
       "            background-color:  #efcfbf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col27 {\n",
       "            background-color:  #f6bea4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col28 {\n",
       "            background-color:  #89acfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col29 {\n",
       "            background-color:  #adc9fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col30 {\n",
       "            background-color:  #cdd9ec;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col0 {\n",
       "            background-color:  #6c8ff1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col1 {\n",
       "            background-color:  #536edd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col2 {\n",
       "            background-color:  #6788ee;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col3 {\n",
       "            background-color:  #6f92f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col4 {\n",
       "            background-color:  #82a6fb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col5 {\n",
       "            background-color:  #799cf8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col6 {\n",
       "            background-color:  #5d7ce6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col7 {\n",
       "            background-color:  #516ddb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col8 {\n",
       "            background-color:  #c3d5f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col9 {\n",
       "            background-color:  #dddcdc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col10 {\n",
       "            background-color:  #89acfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col11 {\n",
       "            background-color:  #d7dce3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col12 {\n",
       "            background-color:  #88abfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col13 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col14 {\n",
       "            background-color:  #e3d9d3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col15 {\n",
       "            background-color:  #9dbdff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col16 {\n",
       "            background-color:  #86a9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col17 {\n",
       "            background-color:  #8caffe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col18 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col19 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col20 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col21 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col22 {\n",
       "            background-color:  #5673e0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col23 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col24 {\n",
       "            background-color:  #4b64d5;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col25 {\n",
       "            background-color:  #6687ed;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col26 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col27 {\n",
       "            background-color:  #536edd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col28 {\n",
       "            background-color:  #d2dbe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col29 {\n",
       "            background-color:  #5f7fe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col30 {\n",
       "            background-color:  #4b64d5;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col0 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col1 {\n",
       "            background-color:  #6180e9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col2 {\n",
       "            background-color:  #7b9ff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col3 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col4 {\n",
       "            background-color:  #9ebeff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col5 {\n",
       "            background-color:  #d8dce2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col6 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col7 {\n",
       "            background-color:  #89acfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col8 {\n",
       "            background-color:  #97b8ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col9 {\n",
       "            background-color:  #f39475;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col10 {\n",
       "            background-color:  #85a8fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col11 {\n",
       "            background-color:  #b3cdfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col12 {\n",
       "            background-color:  #80a3fa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col13 {\n",
       "            background-color:  #7b9ff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col14 {\n",
       "            background-color:  #e5d8d1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col15 {\n",
       "            background-color:  #f29072;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col16 {\n",
       "            background-color:  #f7ad90;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col17 {\n",
       "            background-color:  #edd1c2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col18 {\n",
       "            background-color:  #ccd9ed;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col19 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col20 {\n",
       "            background-color:  #7295f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col21 {\n",
       "            background-color:  #4f69d9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col22 {\n",
       "            background-color:  #7396f5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col23 {\n",
       "            background-color:  #7093f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col24 {\n",
       "            background-color:  #85a8fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col25 {\n",
       "            background-color:  #cdd9ec;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col26 {\n",
       "            background-color:  #c6d6f1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col27 {\n",
       "            background-color:  #9ebeff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col28 {\n",
       "            background-color:  #80a3fa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col29 {\n",
       "            background-color:  #f2c9b4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col30 {\n",
       "            background-color:  #6485ec;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col0 {\n",
       "            background-color:  #bb1b2c;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col1 {\n",
       "            background-color:  #c0d4f5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col2 {\n",
       "            background-color:  #bd1f2d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col3 {\n",
       "            background-color:  #be242e;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col4 {\n",
       "            background-color:  #86a9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col5 {\n",
       "            background-color:  #e0dbd8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col6 {\n",
       "            background-color:  #f7b99e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col7 {\n",
       "            background-color:  #e9785d;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col8 {\n",
       "            background-color:  #6180e9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col9 {\n",
       "            background-color:  #485fd1;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col10 {\n",
       "            background-color:  #f7a688;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col11 {\n",
       "            background-color:  #3e51c5;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col12 {\n",
       "            background-color:  #f7b194;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col13 {\n",
       "            background-color:  #f18d6f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col14 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col15 {\n",
       "            background-color:  #506bda;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col16 {\n",
       "            background-color:  #5875e1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col17 {\n",
       "            background-color:  #9ebeff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col18 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col19 {\n",
       "            background-color:  #3c4ec2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col20 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col21 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col22 {\n",
       "            background-color:  #b50927;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col23 {\n",
       "            background-color:  #b8122a;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col24 {\n",
       "            background-color:  #94b6ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col25 {\n",
       "            background-color:  #e2dad5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col26 {\n",
       "            background-color:  #f2cbb7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col27 {\n",
       "            background-color:  #ec7f63;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col28 {\n",
       "            background-color:  #a9c6fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col29 {\n",
       "            background-color:  #6485ec;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col30 {\n",
       "            background-color:  #ef886b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col0 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col1 {\n",
       "            background-color:  #d0473d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col2 {\n",
       "            background-color:  #cedaeb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col3 {\n",
       "            background-color:  #cdd9ec;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col4 {\n",
       "            background-color:  #4b64d5;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col5 {\n",
       "            background-color:  #80a3fa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col6 {\n",
       "            background-color:  #89acfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col7 {\n",
       "            background-color:  #96b7ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col8 {\n",
       "            background-color:  #4055c8;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col9 {\n",
       "            background-color:  #7a9df8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col10 {\n",
       "            background-color:  #799cf8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col11 {\n",
       "            background-color:  #d6dce4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col12 {\n",
       "            background-color:  #6f92f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col13 {\n",
       "            background-color:  #92b4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col14 {\n",
       "            background-color:  #6282ea;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col15 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col16 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col17 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col18 {\n",
       "            background-color:  #485fd1;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col19 {\n",
       "            background-color:  #455cce;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col20 {\n",
       "            background-color:  #dadce0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col21 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col22 {\n",
       "            background-color:  #d7dce3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col23 {\n",
       "            background-color:  #d5dbe5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col24 {\n",
       "            background-color:  #97b8ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col25 {\n",
       "            background-color:  #c5d6f2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col26 {\n",
       "            background-color:  #c3d5f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col27 {\n",
       "            background-color:  #c9d7f0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col28 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col29 {\n",
       "            background-color:  #8db0fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col30 {\n",
       "            background-color:  #dadce0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col0 {\n",
       "            background-color:  #bd1f2d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col1 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col2 {\n",
       "            background-color:  #bd1f2d;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col3 {\n",
       "            background-color:  #c0282f;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col4 {\n",
       "            background-color:  #8fb1fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col5 {\n",
       "            background-color:  #edd1c2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col6 {\n",
       "            background-color:  #f7a98b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col7 {\n",
       "            background-color:  #e36b54;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col8 {\n",
       "            background-color:  #6c8ff1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col9 {\n",
       "            background-color:  #536edd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col10 {\n",
       "            background-color:  #f6a586;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col11 {\n",
       "            background-color:  #4055c8;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col12 {\n",
       "            background-color:  #f7a98b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col13 {\n",
       "            background-color:  #f18d6f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col14 {\n",
       "            background-color:  #3d50c3;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col15 {\n",
       "            background-color:  #6687ed;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col16 {\n",
       "            background-color:  #6687ed;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col17 {\n",
       "            background-color:  #abc8fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col18 {\n",
       "            background-color:  #4055c8;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col19 {\n",
       "            background-color:  #465ecf;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col20 {\n",
       "            background-color:  #b50927;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col21 {\n",
       "            background-color:  #c4d5f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col22 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col23 {\n",
       "            background-color:  #ba162b;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col24 {\n",
       "            background-color:  #9bbcff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col25 {\n",
       "            background-color:  #edd2c3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col26 {\n",
       "            background-color:  #f6bfa6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col27 {\n",
       "            background-color:  #e67259;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col28 {\n",
       "            background-color:  #b1cbfc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col29 {\n",
       "            background-color:  #7396f5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col30 {\n",
       "            background-color:  #ee8669;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col0 {\n",
       "            background-color:  #c43032;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col1 {\n",
       "            background-color:  #bcd2f7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col2 {\n",
       "            background-color:  #c43032;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col3 {\n",
       "            background-color:  #c0282f;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col4 {\n",
       "            background-color:  #84a7fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col5 {\n",
       "            background-color:  #d9dce1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col6 {\n",
       "            background-color:  #f6bda2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col7 {\n",
       "            background-color:  #ec8165;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col8 {\n",
       "            background-color:  #5e7de7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col9 {\n",
       "            background-color:  #4c66d6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col10 {\n",
       "            background-color:  #f4987a;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col11 {\n",
       "            background-color:  #465ecf;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col12 {\n",
       "            background-color:  #f6a586;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col13 {\n",
       "            background-color:  #e9785d;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col14 {\n",
       "            background-color:  #465ecf;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col15 {\n",
       "            background-color:  #4e68d8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col16 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col17 {\n",
       "            background-color:  #97b8ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col18 {\n",
       "            background-color:  #3f53c6;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col19 {\n",
       "            background-color:  #3f53c6;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col20 {\n",
       "            background-color:  #b8122a;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col21 {\n",
       "            background-color:  #bed2f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col22 {\n",
       "            background-color:  #ba162b;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col23 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col24 {\n",
       "            background-color:  #92b4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col25 {\n",
       "            background-color:  #d9dce1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col26 {\n",
       "            background-color:  #edd1c2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col27 {\n",
       "            background-color:  #f18f71;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col28 {\n",
       "            background-color:  #9ebeff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col29 {\n",
       "            background-color:  #5f7fe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col30 {\n",
       "            background-color:  #f4987a;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col0 {\n",
       "            background-color:  #a9c6fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col1 {\n",
       "            background-color:  #6788ee;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col2 {\n",
       "            background-color:  #a7c5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col3 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col4 {\n",
       "            background-color:  #ec7f63;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col5 {\n",
       "            background-color:  #e8d6cc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col6 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col7 {\n",
       "            background-color:  #ccd9ed;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col8 {\n",
       "            background-color:  #bad0f8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col9 {\n",
       "            background-color:  #f4c5ad;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col10 {\n",
       "            background-color:  #6788ee;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col11 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col12 {\n",
       "            background-color:  #5875e1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col13 {\n",
       "            background-color:  #7a9df8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col14 {\n",
       "            background-color:  #cdd9ec;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col15 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col16 {\n",
       "            background-color:  #516ddb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col17 {\n",
       "            background-color:  #6788ee;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col18 {\n",
       "            background-color:  #5a78e4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col19 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col20 {\n",
       "            background-color:  #b9d0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col21 {\n",
       "            background-color:  #97b8ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col22 {\n",
       "            background-color:  #b7cff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col23 {\n",
       "            background-color:  #b2ccfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col24 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col25 {\n",
       "            background-color:  #f2cab5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col26 {\n",
       "            background-color:  #e9d5cb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col27 {\n",
       "            background-color:  #f1ccb8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col28 {\n",
       "            background-color:  #ead5c9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col29 {\n",
       "            background-color:  #f5c1a9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col30 {\n",
       "            background-color:  #d2dbe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col0 {\n",
       "            background-color:  #ead5c9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col1 {\n",
       "            background-color:  #a9c6fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col2 {\n",
       "            background-color:  #edd2c3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col3 {\n",
       "            background-color:  #e3d9d3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col4 {\n",
       "            background-color:  #d9dce1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col5 {\n",
       "            background-color:  #e26952;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col6 {\n",
       "            background-color:  #f59f80;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col7 {\n",
       "            background-color:  #f7ba9f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col8 {\n",
       "            background-color:  #cad8ef;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col9 {\n",
       "            background-color:  #f0cdbb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col10 {\n",
       "            background-color:  #9abbff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col11 {\n",
       "            background-color:  #445acc;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col12 {\n",
       "            background-color:  #a3c2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col13 {\n",
       "            background-color:  #adc9fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col14 {\n",
       "            background-color:  #6788ee;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col15 {\n",
       "            background-color:  #f5c4ac;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col16 {\n",
       "            background-color:  #c9d7f0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col17 {\n",
       "            background-color:  #c0d4f5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col18 {\n",
       "            background-color:  #6f92f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col19 {\n",
       "            background-color:  #c5d6f2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col20 {\n",
       "            background-color:  #efcfbf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col21 {\n",
       "            background-color:  #c3d5f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col22 {\n",
       "            background-color:  #f3c7b1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col23 {\n",
       "            background-color:  #e8d6cc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col24 {\n",
       "            background-color:  #f2cbb7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col25 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col26 {\n",
       "            background-color:  #d65244;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col27 {\n",
       "            background-color:  #e97a5f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col28 {\n",
       "            background-color:  #f7ba9f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col29 {\n",
       "            background-color:  #ea7b60;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col30 {\n",
       "            background-color:  #f3c7b1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col0 {\n",
       "            background-color:  #f5c0a7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col1 {\n",
       "            background-color:  #afcafc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col2 {\n",
       "            background-color:  #f7bca1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col3 {\n",
       "            background-color:  #f4c6af;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col4 {\n",
       "            background-color:  #cedaeb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col5 {\n",
       "            background-color:  #ec8165;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col6 {\n",
       "            background-color:  #de614d;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col7 {\n",
       "            background-color:  #f49a7b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col8 {\n",
       "            background-color:  #bcd2f7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col9 {\n",
       "            background-color:  #dddcdc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col10 {\n",
       "            background-color:  #bad0f8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col11 {\n",
       "            background-color:  #4a63d3;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col12 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col13 {\n",
       "            background-color:  #cbd8ee;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col14 {\n",
       "            background-color:  #6687ed;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col15 {\n",
       "            background-color:  #efcfbf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col16 {\n",
       "            background-color:  #f4c5ad;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col17 {\n",
       "            background-color:  #dedcdb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col18 {\n",
       "            background-color:  #688aef;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col19 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col20 {\n",
       "            background-color:  #f7b99e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col21 {\n",
       "            background-color:  #c4d5f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col22 {\n",
       "            background-color:  #f7b194;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col23 {\n",
       "            background-color:  #f5c2aa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col24 {\n",
       "            background-color:  #ead5c9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col25 {\n",
       "            background-color:  #d65244;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col26 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col27 {\n",
       "            background-color:  #df634e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col28 {\n",
       "            background-color:  #efcebd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col29 {\n",
       "            background-color:  #f7ac8e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col30 {\n",
       "            background-color:  #f7b396;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col0 {\n",
       "            background-color:  #ec8165;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col1 {\n",
       "            background-color:  #aec9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col2 {\n",
       "            background-color:  #ea7b60;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col3 {\n",
       "            background-color:  #f08b6e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col4 {\n",
       "            background-color:  #e0dbd8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col5 {\n",
       "            background-color:  #ec8165;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col6 {\n",
       "            background-color:  #e36c55;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col7 {\n",
       "            background-color:  #d44e41;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col8 {\n",
       "            background-color:  #bbd1f8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col9 {\n",
       "            background-color:  #b7cff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col10 {\n",
       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col11 {\n",
       "            background-color:  #3c4ec2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col12 {\n",
       "            background-color:  #e6d7cf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col13 {\n",
       "            background-color:  #eed0c0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col14 {\n",
       "            background-color:  #5a78e4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col15 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col16 {\n",
       "            background-color:  #b9d0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col17 {\n",
       "            background-color:  #ecd3c5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col18 {\n",
       "            background-color:  #5572df;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col19 {\n",
       "            background-color:  #8caffe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col20 {\n",
       "            background-color:  #e8765c;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col21 {\n",
       "            background-color:  #c1d4f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col22 {\n",
       "            background-color:  #e36c55;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col23 {\n",
       "            background-color:  #ee8669;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col24 {\n",
       "            background-color:  #efcfbf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col25 {\n",
       "            background-color:  #ea7b60;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col26 {\n",
       "            background-color:  #e0654f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col27 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col28 {\n",
       "            background-color:  #ebd3c6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col29 {\n",
       "            background-color:  #e5d8d1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col30 {\n",
       "            background-color:  #ec8165;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col0 {\n",
       "            background-color:  #b3cdfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col1 {\n",
       "            background-color:  #7093f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col2 {\n",
       "            background-color:  #b2ccfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col3 {\n",
       "            background-color:  #aac7fd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col4 {\n",
       "            background-color:  #c3d5f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col5 {\n",
       "            background-color:  #d9dce1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col6 {\n",
       "            background-color:  #b3cdfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col7 {\n",
       "            background-color:  #b3cdfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col8 {\n",
       "            background-color:  #f7b497;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col9 {\n",
       "            background-color:  #dbdcde;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col10 {\n",
       "            background-color:  #5875e1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col12 {\n",
       "            background-color:  #506bda;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col13 {\n",
       "            background-color:  #6a8bef;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col14 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col15 {\n",
       "            background-color:  #6c8ff1;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col16 {\n",
       "            background-color:  #5b7ae5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col17 {\n",
       "            background-color:  #4c66d6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col18 {\n",
       "            background-color:  #d2dbe8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col19 {\n",
       "            background-color:  #688aef;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col20 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col21 {\n",
       "            background-color:  #9abbff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col22 {\n",
       "            background-color:  #c0d4f5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col23 {\n",
       "            background-color:  #b2ccfb;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col24 {\n",
       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col25 {\n",
       "            background-color:  #f6bea4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col26 {\n",
       "            background-color:  #ecd3c5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col27 {\n",
       "            background-color:  #ead4c8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col28 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col29 {\n",
       "            background-color:  #ead4c8;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col30 {\n",
       "            background-color:  #cfdaea;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col0 {\n",
       "            background-color:  #8badfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col1 {\n",
       "            background-color:  #7597f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col2 {\n",
       "            background-color:  #8caffe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col3 {\n",
       "            background-color:  #84a7fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col4 {\n",
       "            background-color:  #dfdbd9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col5 {\n",
       "            background-color:  #f7b599;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col6 {\n",
       "            background-color:  #d6dce4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col7 {\n",
       "            background-color:  #b1cbfc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col8 {\n",
       "            background-color:  #bfd3f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col9 {\n",
       "            background-color:  #e97a5f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col10 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col11 {\n",
       "            background-color:  #506bda;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col12 {\n",
       "            background-color:  #4961d2;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col13 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col14 {\n",
       "            background-color:  #94b6ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col15 {\n",
       "            background-color:  #e2dad5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col16 {\n",
       "            background-color:  #b9d0f9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col17 {\n",
       "            background-color:  #8badfd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col18 {\n",
       "            background-color:  #7597f6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col19 {\n",
       "            background-color:  #f2c9b4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col20 {\n",
       "            background-color:  #96b7ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col21 {\n",
       "            background-color:  #96b7ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col22 {\n",
       "            background-color:  #9bbcff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col23 {\n",
       "            background-color:  #8db0fe;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col24 {\n",
       "            background-color:  #f6bfa6;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col25 {\n",
       "            background-color:  #e9785d;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col26 {\n",
       "            background-color:  #f7aa8c;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col27 {\n",
       "            background-color:  #ecd3c5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col28 {\n",
       "            background-color:  #f1cdba;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col29 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col30 {\n",
       "            background-color:  #b5cdfa;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col0 {\n",
       "            background-color:  #ee8669;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col1 {\n",
       "            background-color:  #d1dae9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col2 {\n",
       "            background-color:  #ee8669;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col3 {\n",
       "            background-color:  #f29072;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col4 {\n",
       "            background-color:  #b7cff9;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col5 {\n",
       "            background-color:  #eed0c0;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col6 {\n",
       "            background-color:  #f7b79b;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col7 {\n",
       "            background-color:  #f29072;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col8 {\n",
       "            background-color:  #97b8ff;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col9 {\n",
       "            background-color:  #85a8fc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col10 {\n",
       "            background-color:  #edd2c3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col11 {\n",
       "            background-color:  #5b7ae5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col12 {\n",
       "            background-color:  #e6d7cf;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col13 {\n",
       "            background-color:  #efcebd;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col14 {\n",
       "            background-color:  #6485ec;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col15 {\n",
       "            background-color:  #7295f4;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col16 {\n",
       "            background-color:  #7093f3;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col17 {\n",
       "            background-color:  #b1cbfc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col18 {\n",
       "            background-color:  #5b7ae5;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col19 {\n",
       "            background-color:  #5e7de7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col20 {\n",
       "            background-color:  #e97a5f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col21 {\n",
       "            background-color:  #dbdcde;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col22 {\n",
       "            background-color:  #e97a5f;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col23 {\n",
       "            background-color:  #f08b6e;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col24 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col25 {\n",
       "            background-color:  #f5c4ac;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col26 {\n",
       "            background-color:  #f7b396;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col27 {\n",
       "            background-color:  #eb7d62;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col28 {\n",
       "            background-color:  #d8dce2;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col29 {\n",
       "            background-color:  #b1cbfc;\n",
       "            color:  #000000;\n",
       "        }    #T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col30 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >mean radius</th>        <th class=\"col_heading level0 col1\" >mean texture</th>        <th class=\"col_heading level0 col2\" >mean perimeter</th>        <th class=\"col_heading level0 col3\" >mean area</th>        <th class=\"col_heading level0 col4\" >mean smoothness</th>        <th class=\"col_heading level0 col5\" >mean compactness</th>        <th class=\"col_heading level0 col6\" >mean concavity</th>        <th class=\"col_heading level0 col7\" >mean concave points</th>        <th class=\"col_heading level0 col8\" >mean symmetry</th>        <th class=\"col_heading level0 col9\" >mean fractal dimension</th>        <th class=\"col_heading level0 col10\" >radius error</th>        <th class=\"col_heading level0 col11\" >texture error</th>        <th class=\"col_heading level0 col12\" >perimeter error</th>        <th class=\"col_heading level0 col13\" >area error</th>        <th class=\"col_heading level0 col14\" >smoothness error</th>        <th class=\"col_heading level0 col15\" >compactness error</th>        <th class=\"col_heading level0 col16\" >concavity error</th>        <th class=\"col_heading level0 col17\" >concave points error</th>        <th class=\"col_heading level0 col18\" >symmetry error</th>        <th class=\"col_heading level0 col19\" >fractal dimension error</th>        <th class=\"col_heading level0 col20\" >worst radius</th>        <th class=\"col_heading level0 col21\" >worst texture</th>        <th class=\"col_heading level0 col22\" >worst perimeter</th>        <th class=\"col_heading level0 col23\" >worst area</th>        <th class=\"col_heading level0 col24\" >worst smoothness</th>        <th class=\"col_heading level0 col25\" >worst compactness</th>        <th class=\"col_heading level0 col26\" >worst concavity</th>        <th class=\"col_heading level0 col27\" >worst concave points</th>        <th class=\"col_heading level0 col28\" >worst symmetry</th>        <th class=\"col_heading level0 col29\" >worst fractal dimension</th>        <th class=\"col_heading level0 col30\" >outcome</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row0\" class=\"row_heading level0 row0\" >mean radius</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col1\" class=\"data row0 col1\" >0.323782</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col2\" class=\"data row0 col2\" >0.997855</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col3\" class=\"data row0 col3\" >0.987357</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col4\" class=\"data row0 col4\" >0.170581</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col5\" class=\"data row0 col5\" >0.506124</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col6\" class=\"data row0 col6\" >0.676764</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col7\" class=\"data row0 col7\" >0.822529</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col8\" class=\"data row0 col8\" >0.147741</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col9\" class=\"data row0 col9\" >-0.311631</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col10\" class=\"data row0 col10\" >0.67909</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col11\" class=\"data row0 col11\" >-0.0973174</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col12\" class=\"data row0 col12\" >0.674172</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col13\" class=\"data row0 col13\" >0.735864</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col14\" class=\"data row0 col14\" >-0.2226</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col15\" class=\"data row0 col15\" >0.206</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col16\" class=\"data row0 col16\" >0.194204</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col17\" class=\"data row0 col17\" >0.376169</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col18\" class=\"data row0 col18\" >-0.104321</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col19\" class=\"data row0 col19\" >-0.0426413</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col20\" class=\"data row0 col20\" >0.969539</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col21\" class=\"data row0 col21\" >0.297008</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col22\" class=\"data row0 col22\" >0.965137</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col23\" class=\"data row0 col23\" >0.941082</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col24\" class=\"data row0 col24\" >0.119616</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col25\" class=\"data row0 col25\" >0.413463</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col26\" class=\"data row0 col26\" >0.526911</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col27\" class=\"data row0 col27\" >0.744214</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col28\" class=\"data row0 col28\" >0.163953</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col29\" class=\"data row0 col29\" >0.00706589</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row0_col30\" class=\"data row0 col30\" >0.730029</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row1\" class=\"row_heading level0 row1\" >mean texture</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col0\" class=\"data row1 col0\" >0.323782</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col1\" class=\"data row1 col1\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col2\" class=\"data row1 col2\" >0.329533</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col3\" class=\"data row1 col3\" >0.321086</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col4\" class=\"data row1 col4\" >-0.0233885</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col5\" class=\"data row1 col5\" >0.236702</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col6\" class=\"data row1 col6\" >0.302418</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col7\" class=\"data row1 col7\" >0.293464</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col8\" class=\"data row1 col8\" >0.071401</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col9\" class=\"data row1 col9\" >-0.0764372</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col10\" class=\"data row1 col10\" >0.275869</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col11\" class=\"data row1 col11\" >0.386358</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col12\" class=\"data row1 col12\" >0.281673</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col13\" class=\"data row1 col13\" >0.259845</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col14\" class=\"data row1 col14\" >0.00661378</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col15\" class=\"data row1 col15\" >0.191975</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col16\" class=\"data row1 col16\" >0.143293</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col17\" class=\"data row1 col17\" >0.163851</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col18\" class=\"data row1 col18\" >0.00912717</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col19\" class=\"data row1 col19\" >0.0544575</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col20\" class=\"data row1 col20\" >0.352573</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col21\" class=\"data row1 col21\" >0.912045</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col22\" class=\"data row1 col22\" >0.35804</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col23\" class=\"data row1 col23\" >0.343546</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col24\" class=\"data row1 col24\" >0.0775034</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col25\" class=\"data row1 col25\" >0.27783</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col26\" class=\"data row1 col26\" >0.301025</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col27\" class=\"data row1 col27\" >0.295316</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col28\" class=\"data row1 col28\" >0.105008</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col29\" class=\"data row1 col29\" >0.119205</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row1_col30\" class=\"data row1 col30\" >0.415185</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row2\" class=\"row_heading level0 row2\" >mean perimeter</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col0\" class=\"data row2 col0\" >0.997855</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col1\" class=\"data row2 col1\" >0.329533</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col2\" class=\"data row2 col2\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col3\" class=\"data row2 col3\" >0.986507</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col4\" class=\"data row2 col4\" >0.207278</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col5\" class=\"data row2 col5\" >0.556936</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col6\" class=\"data row2 col6\" >0.716136</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col7\" class=\"data row2 col7\" >0.850977</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col8\" class=\"data row2 col8\" >0.183027</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col9\" class=\"data row2 col9\" >-0.261477</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col10\" class=\"data row2 col10\" >0.691765</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col11\" class=\"data row2 col11\" >-0.0867611</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col12\" class=\"data row2 col12\" >0.693135</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col13\" class=\"data row2 col13\" >0.744983</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col14\" class=\"data row2 col14\" >-0.202694</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col15\" class=\"data row2 col15\" >0.250744</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col16\" class=\"data row2 col16\" >0.228082</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col17\" class=\"data row2 col17\" >0.407217</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col18\" class=\"data row2 col18\" >-0.0816293</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col19\" class=\"data row2 col19\" >-0.00552339</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col20\" class=\"data row2 col20\" >0.969476</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col21\" class=\"data row2 col21\" >0.303038</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col22\" class=\"data row2 col22\" >0.970387</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col23\" class=\"data row2 col23\" >0.94155</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col24\" class=\"data row2 col24\" >0.150549</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col25\" class=\"data row2 col25\" >0.455774</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col26\" class=\"data row2 col26\" >0.563879</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col27\" class=\"data row2 col27\" >0.771241</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col28\" class=\"data row2 col28\" >0.189115</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col29\" class=\"data row2 col29\" >0.0510185</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row2_col30\" class=\"data row2 col30\" >0.742636</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row3\" class=\"row_heading level0 row3\" >mean area</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col0\" class=\"data row3 col0\" >0.987357</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col1\" class=\"data row3 col1\" >0.321086</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col2\" class=\"data row3 col2\" >0.986507</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col3\" class=\"data row3 col3\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col4\" class=\"data row3 col4\" >0.177028</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col5\" class=\"data row3 col5\" >0.498502</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col6\" class=\"data row3 col6\" >0.685983</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col7\" class=\"data row3 col7\" >0.823269</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col8\" class=\"data row3 col8\" >0.151293</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col9\" class=\"data row3 col9\" >-0.28311</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col10\" class=\"data row3 col10\" >0.732562</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col11\" class=\"data row3 col11\" >-0.0662802</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col12\" class=\"data row3 col12\" >0.726628</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col13\" class=\"data row3 col13\" >0.800086</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col14\" class=\"data row3 col14\" >-0.166777</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col15\" class=\"data row3 col15\" >0.212583</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col16\" class=\"data row3 col16\" >0.20766</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col17\" class=\"data row3 col17\" >0.37232</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col18\" class=\"data row3 col18\" >-0.0724966</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col19\" class=\"data row3 col19\" >-0.019887</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col20\" class=\"data row3 col20\" >0.962746</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col21\" class=\"data row3 col21\" >0.287489</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col22\" class=\"data row3 col22\" >0.95912</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col23\" class=\"data row3 col23\" >0.959213</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col24\" class=\"data row3 col24\" >0.123523</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col25\" class=\"data row3 col25\" >0.39041</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col26\" class=\"data row3 col26\" >0.512606</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col27\" class=\"data row3 col27\" >0.722017</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col28\" class=\"data row3 col28\" >0.14357</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col29\" class=\"data row3 col29\" >0.0037376</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row3_col30\" class=\"data row3 col30\" >0.708984</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row4\" class=\"row_heading level0 row4\" >mean smoothness</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col0\" class=\"data row4 col0\" >0.170581</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col1\" class=\"data row4 col1\" >-0.0233885</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col2\" class=\"data row4 col2\" >0.207278</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col3\" class=\"data row4 col3\" >0.177028</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col4\" class=\"data row4 col4\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col5\" class=\"data row4 col5\" >0.659123</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col6\" class=\"data row4 col6\" >0.521984</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col7\" class=\"data row4 col7\" >0.553695</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col8\" class=\"data row4 col8\" >0.557775</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col9\" class=\"data row4 col9\" >0.584792</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col10\" class=\"data row4 col10\" >0.301467</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col11\" class=\"data row4 col11\" >0.0684064</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col12\" class=\"data row4 col12\" >0.296092</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col13\" class=\"data row4 col13\" >0.246552</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col14\" class=\"data row4 col14\" >0.332375</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col15\" class=\"data row4 col15\" >0.318943</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col16\" class=\"data row4 col16\" >0.248396</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col17\" class=\"data row4 col17\" >0.380676</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col18\" class=\"data row4 col18\" >0.200774</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col19\" class=\"data row4 col19\" >0.283607</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col20\" class=\"data row4 col20\" >0.21312</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col21\" class=\"data row4 col21\" >0.0360718</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col22\" class=\"data row4 col22\" >0.238853</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col23\" class=\"data row4 col23\" >0.206718</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col24\" class=\"data row4 col24\" >0.805324</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col25\" class=\"data row4 col25\" >0.472468</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col26\" class=\"data row4 col26\" >0.434926</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col27\" class=\"data row4 col27\" >0.503053</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col28\" class=\"data row4 col28\" >0.394309</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col29\" class=\"data row4 col29\" >0.499316</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row4_col30\" class=\"data row4 col30\" >0.35856</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row5\" class=\"row_heading level0 row5\" >mean compactness</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col0\" class=\"data row5 col0\" >0.506124</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col1\" class=\"data row5 col1\" >0.236702</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col2\" class=\"data row5 col2\" >0.556936</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col3\" class=\"data row5 col3\" >0.498502</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col4\" class=\"data row5 col4\" >0.659123</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col5\" class=\"data row5 col5\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col6\" class=\"data row5 col6\" >0.883121</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col7\" class=\"data row5 col7\" >0.831135</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col8\" class=\"data row5 col8\" >0.602641</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col9\" class=\"data row5 col9\" >0.565369</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col10\" class=\"data row5 col10\" >0.497473</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col11\" class=\"data row5 col11\" >0.0462048</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col12\" class=\"data row5 col12\" >0.548905</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col13\" class=\"data row5 col13\" >0.455653</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col14\" class=\"data row5 col14\" >0.135299</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col15\" class=\"data row5 col15\" >0.738722</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col16\" class=\"data row5 col16\" >0.570517</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col17\" class=\"data row5 col17\" >0.642262</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col18\" class=\"data row5 col18\" >0.229977</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col19\" class=\"data row5 col19\" >0.507318</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col20\" class=\"data row5 col20\" >0.535315</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col21\" class=\"data row5 col21\" >0.248133</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col22\" class=\"data row5 col22\" >0.59021</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col23\" class=\"data row5 col23\" >0.509604</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col24\" class=\"data row5 col24\" >0.565541</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col25\" class=\"data row5 col25\" >0.865809</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col26\" class=\"data row5 col26\" >0.816275</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col27\" class=\"data row5 col27\" >0.815573</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col28\" class=\"data row5 col28\" >0.510223</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col29\" class=\"data row5 col29\" >0.687382</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row5_col30\" class=\"data row5 col30\" >0.596534</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row6\" class=\"row_heading level0 row6\" >mean concavity</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col0\" class=\"data row6 col0\" >0.676764</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col1\" class=\"data row6 col1\" >0.302418</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col2\" class=\"data row6 col2\" >0.716136</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col3\" class=\"data row6 col3\" >0.685983</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col4\" class=\"data row6 col4\" >0.521984</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col5\" class=\"data row6 col5\" >0.883121</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col6\" class=\"data row6 col6\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col7\" class=\"data row6 col7\" >0.921391</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col8\" class=\"data row6 col8\" >0.500667</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col9\" class=\"data row6 col9\" >0.336783</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col10\" class=\"data row6 col10\" >0.631925</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col11\" class=\"data row6 col11\" >0.0762183</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col12\" class=\"data row6 col12\" >0.660391</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col13\" class=\"data row6 col13\" >0.617427</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col14\" class=\"data row6 col14\" >0.0985637</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col15\" class=\"data row6 col15\" >0.670279</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col16\" class=\"data row6 col16\" >0.69127</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col17\" class=\"data row6 col17\" >0.68326</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col18\" class=\"data row6 col18\" >0.178009</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col19\" class=\"data row6 col19\" >0.449301</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col20\" class=\"data row6 col20\" >0.688236</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col21\" class=\"data row6 col21\" >0.299879</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col22\" class=\"data row6 col22\" >0.729565</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col23\" class=\"data row6 col23\" >0.675987</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col24\" class=\"data row6 col24\" >0.448822</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col25\" class=\"data row6 col25\" >0.754968</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col26\" class=\"data row6 col26\" >0.884103</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col27\" class=\"data row6 col27\" >0.861323</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col28\" class=\"data row6 col28\" >0.409464</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col29\" class=\"data row6 col29\" >0.51493</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row6_col30\" class=\"data row6 col30\" >0.69636</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row7\" class=\"row_heading level0 row7\" >mean concave points</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col0\" class=\"data row7 col0\" >0.822529</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col1\" class=\"data row7 col1\" >0.293464</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col2\" class=\"data row7 col2\" >0.850977</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col3\" class=\"data row7 col3\" >0.823269</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col4\" class=\"data row7 col4\" >0.553695</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col5\" class=\"data row7 col5\" >0.831135</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col6\" class=\"data row7 col6\" >0.921391</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col7\" class=\"data row7 col7\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col8\" class=\"data row7 col8\" >0.462497</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col9\" class=\"data row7 col9\" >0.166917</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col10\" class=\"data row7 col10\" >0.69805</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col11\" class=\"data row7 col11\" >0.0214796</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col12\" class=\"data row7 col12\" >0.71065</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col13\" class=\"data row7 col13\" >0.690299</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col14\" class=\"data row7 col14\" >0.0276533</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col15\" class=\"data row7 col15\" >0.490424</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col16\" class=\"data row7 col16\" >0.439167</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col17\" class=\"data row7 col17\" >0.615634</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col18\" class=\"data row7 col18\" >0.0953508</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col19\" class=\"data row7 col19\" >0.257584</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col20\" class=\"data row7 col20\" >0.830318</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col21\" class=\"data row7 col21\" >0.292752</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col22\" class=\"data row7 col22\" >0.855923</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col23\" class=\"data row7 col23\" >0.80963</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col24\" class=\"data row7 col24\" >0.452753</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col25\" class=\"data row7 col25\" >0.667454</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col26\" class=\"data row7 col26\" >0.752399</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col27\" class=\"data row7 col27\" >0.910155</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col28\" class=\"data row7 col28\" >0.375744</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col29\" class=\"data row7 col29\" >0.368661</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row7_col30\" class=\"data row7 col30\" >0.776614</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row8\" class=\"row_heading level0 row8\" >mean symmetry</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col0\" class=\"data row8 col0\" >0.147741</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col1\" class=\"data row8 col1\" >0.071401</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col2\" class=\"data row8 col2\" >0.183027</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col3\" class=\"data row8 col3\" >0.151293</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col4\" class=\"data row8 col4\" >0.557775</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col5\" class=\"data row8 col5\" >0.602641</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col6\" class=\"data row8 col6\" >0.500667</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col7\" class=\"data row8 col7\" >0.462497</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col8\" class=\"data row8 col8\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col9\" class=\"data row8 col9\" >0.479921</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col10\" class=\"data row8 col10\" >0.303379</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col11\" class=\"data row8 col11\" >0.128053</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col12\" class=\"data row8 col12\" >0.313893</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col13\" class=\"data row8 col13\" >0.22397</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col14\" class=\"data row8 col14\" >0.187321</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col15\" class=\"data row8 col15\" >0.421659</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col16\" class=\"data row8 col16\" >0.342627</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col17\" class=\"data row8 col17\" >0.393298</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col18\" class=\"data row8 col18\" >0.449137</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col19\" class=\"data row8 col19\" >0.331786</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col20\" class=\"data row8 col20\" >0.185728</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col21\" class=\"data row8 col21\" >0.0906507</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col22\" class=\"data row8 col22\" >0.219169</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col23\" class=\"data row8 col23\" >0.177193</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col24\" class=\"data row8 col24\" >0.426675</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col25\" class=\"data row8 col25\" >0.4732</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col26\" class=\"data row8 col26\" >0.433721</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col27\" class=\"data row8 col27\" >0.430297</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col28\" class=\"data row8 col28\" >0.699826</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col29\" class=\"data row8 col29\" >0.438413</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row8_col30\" class=\"data row8 col30\" >0.330499</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row9\" class=\"row_heading level0 row9\" >mean fractal dimension</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col0\" class=\"data row9 col0\" >-0.311631</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col1\" class=\"data row9 col1\" >-0.0764372</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col2\" class=\"data row9 col2\" >-0.261477</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col3\" class=\"data row9 col3\" >-0.28311</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col4\" class=\"data row9 col4\" >0.584792</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col5\" class=\"data row9 col5\" >0.565369</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col6\" class=\"data row9 col6\" >0.336783</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col7\" class=\"data row9 col7\" >0.166917</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col8\" class=\"data row9 col8\" >0.479921</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col9\" class=\"data row9 col9\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col10\" class=\"data row9 col10\" >0.000110995</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col11\" class=\"data row9 col11\" >0.164174</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col12\" class=\"data row9 col12\" >0.0398299</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col13\" class=\"data row9 col13\" >-0.0901702</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col14\" class=\"data row9 col14\" >0.401964</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col15\" class=\"data row9 col15\" >0.559837</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col16\" class=\"data row9 col16\" >0.44663</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col17\" class=\"data row9 col17\" >0.341198</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col18\" class=\"data row9 col18\" >0.345007</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col19\" class=\"data row9 col19\" >0.688132</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col20\" class=\"data row9 col20\" >-0.253691</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col21\" class=\"data row9 col21\" >-0.0512692</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col22\" class=\"data row9 col22\" >-0.205151</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col23\" class=\"data row9 col23\" >-0.231854</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col24\" class=\"data row9 col24\" >0.504942</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col25\" class=\"data row9 col25\" >0.458798</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col26\" class=\"data row9 col26\" >0.346234</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col27\" class=\"data row9 col27\" >0.175325</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col28\" class=\"data row9 col28\" >0.334019</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col29\" class=\"data row9 col29\" >0.767297</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row9_col30\" class=\"data row9 col30\" >-0.0128376</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row10\" class=\"row_heading level0 row10\" >radius error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col0\" class=\"data row10 col0\" >0.67909</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col1\" class=\"data row10 col1\" >0.275869</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col2\" class=\"data row10 col2\" >0.691765</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col3\" class=\"data row10 col3\" >0.732562</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col4\" class=\"data row10 col4\" >0.301467</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col5\" class=\"data row10 col5\" >0.497473</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col6\" class=\"data row10 col6\" >0.631925</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col7\" class=\"data row10 col7\" >0.69805</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col8\" class=\"data row10 col8\" >0.303379</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col9\" class=\"data row10 col9\" >0.000110995</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col10\" class=\"data row10 col10\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col11\" class=\"data row10 col11\" >0.213247</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col12\" class=\"data row10 col12\" >0.972794</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col13\" class=\"data row10 col13\" >0.95183</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col14\" class=\"data row10 col14\" >0.164514</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col15\" class=\"data row10 col15\" >0.356065</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col16\" class=\"data row10 col16\" >0.332358</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col17\" class=\"data row10 col17\" >0.513346</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col18\" class=\"data row10 col18\" >0.240567</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col19\" class=\"data row10 col19\" >0.227754</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col20\" class=\"data row10 col20\" >0.715065</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col21\" class=\"data row10 col21\" >0.194799</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col22\" class=\"data row10 col22\" >0.719684</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col23\" class=\"data row10 col23\" >0.751548</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col24\" class=\"data row10 col24\" >0.141919</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col25\" class=\"data row10 col25\" >0.287103</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col26\" class=\"data row10 col26\" >0.380585</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col27\" class=\"data row10 col27\" >0.531062</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col28\" class=\"data row10 col28\" >0.0945428</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col29\" class=\"data row10 col29\" >0.0495594</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row10_col30\" class=\"data row10 col30\" >0.567134</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row11\" class=\"row_heading level0 row11\" >texture error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col0\" class=\"data row11 col0\" >-0.0973174</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col1\" class=\"data row11 col1\" >0.386358</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col2\" class=\"data row11 col2\" >-0.0867611</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col3\" class=\"data row11 col3\" >-0.0662802</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col4\" class=\"data row11 col4\" >0.0684064</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col5\" class=\"data row11 col5\" >0.0462048</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col6\" class=\"data row11 col6\" >0.0762183</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col7\" class=\"data row11 col7\" >0.0214796</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col8\" class=\"data row11 col8\" >0.128053</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col9\" class=\"data row11 col9\" >0.164174</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col10\" class=\"data row11 col10\" >0.213247</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col11\" class=\"data row11 col11\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col12\" class=\"data row11 col12\" >0.223171</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col13\" class=\"data row11 col13\" >0.111567</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col14\" class=\"data row11 col14\" >0.397243</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col15\" class=\"data row11 col15\" >0.2317</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col16\" class=\"data row11 col16\" >0.194998</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col17\" class=\"data row11 col17\" >0.230283</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col18\" class=\"data row11 col18\" >0.411621</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col19\" class=\"data row11 col19\" >0.279723</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col20\" class=\"data row11 col20\" >-0.11169</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col21\" class=\"data row11 col21\" >0.409003</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col22\" class=\"data row11 col22\" >-0.102242</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col23\" class=\"data row11 col23\" >-0.083195</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col24\" class=\"data row11 col24\" >-0.0736577</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col25\" class=\"data row11 col25\" >-0.0924394</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col26\" class=\"data row11 col26\" >-0.0689562</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col27\" class=\"data row11 col27\" >-0.119638</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col28\" class=\"data row11 col28\" >-0.128215</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col29\" class=\"data row11 col29\" >-0.0456546</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row11_col30\" class=\"data row11 col30\" >-0.00830333</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row12\" class=\"row_heading level0 row12\" >perimeter error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col0\" class=\"data row12 col0\" >0.674172</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col1\" class=\"data row12 col1\" >0.281673</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col2\" class=\"data row12 col2\" >0.693135</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col3\" class=\"data row12 col3\" >0.726628</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col4\" class=\"data row12 col4\" >0.296092</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col5\" class=\"data row12 col5\" >0.548905</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col6\" class=\"data row12 col6\" >0.660391</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col7\" class=\"data row12 col7\" >0.71065</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col8\" class=\"data row12 col8\" >0.313893</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col9\" class=\"data row12 col9\" >0.0398299</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col10\" class=\"data row12 col10\" >0.972794</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col11\" class=\"data row12 col11\" >0.223171</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col12\" class=\"data row12 col12\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col13\" class=\"data row12 col13\" >0.937655</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col14\" class=\"data row12 col14\" >0.151075</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col15\" class=\"data row12 col15\" >0.416322</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col16\" class=\"data row12 col16\" >0.362482</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col17\" class=\"data row12 col17\" >0.556264</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col18\" class=\"data row12 col18\" >0.266487</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col19\" class=\"data row12 col19\" >0.244143</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col20\" class=\"data row12 col20\" >0.697201</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col21\" class=\"data row12 col21\" >0.200371</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col22\" class=\"data row12 col22\" >0.721031</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col23\" class=\"data row12 col23\" >0.730713</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col24\" class=\"data row12 col24\" >0.130054</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col25\" class=\"data row12 col25\" >0.341919</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col26\" class=\"data row12 col26\" >0.418899</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col27\" class=\"data row12 col27\" >0.554897</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col28\" class=\"data row12 col28\" >0.10993</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col29\" class=\"data row12 col29\" >0.0854326</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row12_col30\" class=\"data row12 col30\" >0.556141</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row13\" class=\"row_heading level0 row13\" >area error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col0\" class=\"data row13 col0\" >0.735864</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col1\" class=\"data row13 col1\" >0.259845</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col2\" class=\"data row13 col2\" >0.744983</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col3\" class=\"data row13 col3\" >0.800086</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col4\" class=\"data row13 col4\" >0.246552</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col5\" class=\"data row13 col5\" >0.455653</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col6\" class=\"data row13 col6\" >0.617427</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col7\" class=\"data row13 col7\" >0.690299</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col8\" class=\"data row13 col8\" >0.22397</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col9\" class=\"data row13 col9\" >-0.0901702</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col10\" class=\"data row13 col10\" >0.95183</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col11\" class=\"data row13 col11\" >0.111567</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col12\" class=\"data row13 col12\" >0.937655</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col13\" class=\"data row13 col13\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col14\" class=\"data row13 col14\" >0.0751503</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col15\" class=\"data row13 col15\" >0.28484</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col16\" class=\"data row13 col16\" >0.270895</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col17\" class=\"data row13 col17\" >0.41573</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col18\" class=\"data row13 col18\" >0.134109</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col19\" class=\"data row13 col19\" >0.127071</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col20\" class=\"data row13 col20\" >0.757373</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col21\" class=\"data row13 col21\" >0.196497</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col22\" class=\"data row13 col22\" >0.761213</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col23\" class=\"data row13 col23\" >0.811408</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col24\" class=\"data row13 col24\" >0.125389</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col25\" class=\"data row13 col25\" >0.283257</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col26\" class=\"data row13 col26\" >0.3851</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col27\" class=\"data row13 col27\" >0.538166</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col28\" class=\"data row13 col28\" >0.0741263</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col29\" class=\"data row13 col29\" >0.0175393</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row13_col30\" class=\"data row13 col30\" >0.548236</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row14\" class=\"row_heading level0 row14\" >smoothness error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col0\" class=\"data row14 col0\" >-0.2226</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col1\" class=\"data row14 col1\" >0.00661378</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col2\" class=\"data row14 col2\" >-0.202694</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col3\" class=\"data row14 col3\" >-0.166777</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col4\" class=\"data row14 col4\" >0.332375</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col5\" class=\"data row14 col5\" >0.135299</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col6\" class=\"data row14 col6\" >0.0985637</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col7\" class=\"data row14 col7\" >0.0276533</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col8\" class=\"data row14 col8\" >0.187321</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col9\" class=\"data row14 col9\" >0.401964</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col10\" class=\"data row14 col10\" >0.164514</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col11\" class=\"data row14 col11\" >0.397243</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col12\" class=\"data row14 col12\" >0.151075</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col13\" class=\"data row14 col13\" >0.0751503</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col14\" class=\"data row14 col14\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col15\" class=\"data row14 col15\" >0.336696</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col16\" class=\"data row14 col16\" >0.268685</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col17\" class=\"data row14 col17\" >0.328429</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col18\" class=\"data row14 col18\" >0.413506</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col19\" class=\"data row14 col19\" >0.427374</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col20\" class=\"data row14 col20\" >-0.230691</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col21\" class=\"data row14 col21\" >-0.074743</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col22\" class=\"data row14 col22\" >-0.217304</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col23\" class=\"data row14 col23\" >-0.182195</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col24\" class=\"data row14 col24\" >0.314457</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col25\" class=\"data row14 col25\" >-0.0555581</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col26\" class=\"data row14 col26\" >-0.0582984</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col27\" class=\"data row14 col27\" >-0.102007</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col28\" class=\"data row14 col28\" >-0.107342</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col29\" class=\"data row14 col29\" >0.10148</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row14_col30\" class=\"data row14 col30\" >-0.067016</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row15\" class=\"row_heading level0 row15\" >compactness error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col0\" class=\"data row15 col0\" >0.206</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col1\" class=\"data row15 col1\" >0.191975</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col2\" class=\"data row15 col2\" >0.250744</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col3\" class=\"data row15 col3\" >0.212583</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col4\" class=\"data row15 col4\" >0.318943</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col5\" class=\"data row15 col5\" >0.738722</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col6\" class=\"data row15 col6\" >0.670279</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col7\" class=\"data row15 col7\" >0.490424</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col8\" class=\"data row15 col8\" >0.421659</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col9\" class=\"data row15 col9\" >0.559837</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col10\" class=\"data row15 col10\" >0.356065</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col11\" class=\"data row15 col11\" >0.2317</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col12\" class=\"data row15 col12\" >0.416322</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col13\" class=\"data row15 col13\" >0.28484</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col14\" class=\"data row15 col14\" >0.336696</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col15\" class=\"data row15 col15\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col16\" class=\"data row15 col16\" >0.801268</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col17\" class=\"data row15 col17\" >0.744083</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col18\" class=\"data row15 col18\" >0.394713</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col19\" class=\"data row15 col19\" >0.803269</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col20\" class=\"data row15 col20\" >0.204607</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col21\" class=\"data row15 col21\" >0.143003</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col22\" class=\"data row15 col22\" >0.260516</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col23\" class=\"data row15 col23\" >0.199371</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col24\" class=\"data row15 col24\" >0.227394</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col25\" class=\"data row15 col25\" >0.67878</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col26\" class=\"data row15 col26\" >0.639147</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col27\" class=\"data row15 col27\" >0.483208</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col28\" class=\"data row15 col28\" >0.277878</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col29\" class=\"data row15 col29\" >0.590973</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row15_col30\" class=\"data row15 col30\" >0.292999</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row16\" class=\"row_heading level0 row16\" >concavity error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col0\" class=\"data row16 col0\" >0.194204</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col1\" class=\"data row16 col1\" >0.143293</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col2\" class=\"data row16 col2\" >0.228082</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col3\" class=\"data row16 col3\" >0.20766</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col4\" class=\"data row16 col4\" >0.248396</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col5\" class=\"data row16 col5\" >0.570517</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col6\" class=\"data row16 col6\" >0.69127</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col7\" class=\"data row16 col7\" >0.439167</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col8\" class=\"data row16 col8\" >0.342627</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col9\" class=\"data row16 col9\" >0.44663</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col10\" class=\"data row16 col10\" >0.332358</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col11\" class=\"data row16 col11\" >0.194998</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col12\" class=\"data row16 col12\" >0.362482</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col13\" class=\"data row16 col13\" >0.270895</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col14\" class=\"data row16 col14\" >0.268685</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col15\" class=\"data row16 col15\" >0.801268</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col16\" class=\"data row16 col16\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col17\" class=\"data row16 col17\" >0.771804</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col18\" class=\"data row16 col18\" >0.309429</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col19\" class=\"data row16 col19\" >0.727372</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col20\" class=\"data row16 col20\" >0.186904</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col21\" class=\"data row16 col21\" >0.100241</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col22\" class=\"data row16 col22\" >0.22668</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col23\" class=\"data row16 col23\" >0.188353</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col24\" class=\"data row16 col24\" >0.168481</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col25\" class=\"data row16 col25\" >0.484858</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col26\" class=\"data row16 col26\" >0.662564</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col27\" class=\"data row16 col27\" >0.440472</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col28\" class=\"data row16 col28\" >0.197788</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col29\" class=\"data row16 col29\" >0.439329</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row16_col30\" class=\"data row16 col30\" >0.25373</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row17\" class=\"row_heading level0 row17\" >concave points error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col0\" class=\"data row17 col0\" >0.376169</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col1\" class=\"data row17 col1\" >0.163851</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col2\" class=\"data row17 col2\" >0.407217</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col3\" class=\"data row17 col3\" >0.37232</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col4\" class=\"data row17 col4\" >0.380676</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col5\" class=\"data row17 col5\" >0.642262</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col6\" class=\"data row17 col6\" >0.68326</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col7\" class=\"data row17 col7\" >0.615634</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col8\" class=\"data row17 col8\" >0.393298</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col9\" class=\"data row17 col9\" >0.341198</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col10\" class=\"data row17 col10\" >0.513346</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col11\" class=\"data row17 col11\" >0.230283</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col12\" class=\"data row17 col12\" >0.556264</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col13\" class=\"data row17 col13\" >0.41573</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col14\" class=\"data row17 col14\" >0.328429</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col15\" class=\"data row17 col15\" >0.744083</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col16\" class=\"data row17 col16\" >0.771804</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col17\" class=\"data row17 col17\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col18\" class=\"data row17 col18\" >0.31278</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col19\" class=\"data row17 col19\" >0.611044</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col20\" class=\"data row17 col20\" >0.358127</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col21\" class=\"data row17 col21\" >0.0867412</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col22\" class=\"data row17 col22\" >0.394999</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col23\" class=\"data row17 col23\" >0.342271</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col24\" class=\"data row17 col24\" >0.215351</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col25\" class=\"data row17 col25\" >0.452888</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col26\" class=\"data row17 col26\" >0.549592</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col27\" class=\"data row17 col27\" >0.60245</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col28\" class=\"data row17 col28\" >0.143116</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col29\" class=\"data row17 col29\" >0.310655</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row17_col30\" class=\"data row17 col30\" >0.408042</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row18\" class=\"row_heading level0 row18\" >symmetry error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col0\" class=\"data row18 col0\" >-0.104321</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col1\" class=\"data row18 col1\" >0.00912717</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col2\" class=\"data row18 col2\" >-0.0816293</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col3\" class=\"data row18 col3\" >-0.0724966</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col4\" class=\"data row18 col4\" >0.200774</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col5\" class=\"data row18 col5\" >0.229977</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col6\" class=\"data row18 col6\" >0.178009</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col7\" class=\"data row18 col7\" >0.0953508</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col8\" class=\"data row18 col8\" >0.449137</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col9\" class=\"data row18 col9\" >0.345007</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col10\" class=\"data row18 col10\" >0.240567</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col11\" class=\"data row18 col11\" >0.411621</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col12\" class=\"data row18 col12\" >0.266487</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col13\" class=\"data row18 col13\" >0.134109</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col14\" class=\"data row18 col14\" >0.413506</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col15\" class=\"data row18 col15\" >0.394713</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col16\" class=\"data row18 col16\" >0.309429</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col17\" class=\"data row18 col17\" >0.31278</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col18\" class=\"data row18 col18\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col19\" class=\"data row18 col19\" >0.369078</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col20\" class=\"data row18 col20\" >-0.128121</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col21\" class=\"data row18 col21\" >-0.0774734</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col22\" class=\"data row18 col22\" >-0.103753</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col23\" class=\"data row18 col23\" >-0.110343</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col24\" class=\"data row18 col24\" >-0.0126618</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col25\" class=\"data row18 col25\" >0.0602549</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col26\" class=\"data row18 col26\" >0.037119</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col27\" class=\"data row18 col27\" >-0.0304134</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col28\" class=\"data row18 col28\" >0.389402</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col29\" class=\"data row18 col29\" >0.0780795</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row18_col30\" class=\"data row18 col30\" >-0.00652176</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row19\" class=\"row_heading level0 row19\" >fractal dimension error</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col0\" class=\"data row19 col0\" >-0.0426413</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col1\" class=\"data row19 col1\" >0.0544575</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col2\" class=\"data row19 col2\" >-0.00552339</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col3\" class=\"data row19 col3\" >-0.019887</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col4\" class=\"data row19 col4\" >0.283607</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col5\" class=\"data row19 col5\" >0.507318</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col6\" class=\"data row19 col6\" >0.449301</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col7\" class=\"data row19 col7\" >0.257584</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col8\" class=\"data row19 col8\" >0.331786</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col9\" class=\"data row19 col9\" >0.688132</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col10\" class=\"data row19 col10\" >0.227754</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col11\" class=\"data row19 col11\" >0.279723</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col12\" class=\"data row19 col12\" >0.244143</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col13\" class=\"data row19 col13\" >0.127071</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col14\" class=\"data row19 col14\" >0.427374</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col15\" class=\"data row19 col15\" >0.803269</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col16\" class=\"data row19 col16\" >0.727372</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col17\" class=\"data row19 col17\" >0.611044</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col18\" class=\"data row19 col18\" >0.369078</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col19\" class=\"data row19 col19\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col20\" class=\"data row19 col20\" >-0.0374876</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col21\" class=\"data row19 col21\" >-0.00319503</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col22\" class=\"data row19 col22\" >-0.0010004</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col23\" class=\"data row19 col23\" >-0.0227361</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col24\" class=\"data row19 col24\" >0.170568</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col25\" class=\"data row19 col25\" >0.390159</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col26\" class=\"data row19 col26\" >0.379975</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col27\" class=\"data row19 col27\" >0.215204</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col28\" class=\"data row19 col28\" >0.111094</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col29\" class=\"data row19 col29\" >0.591328</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row19_col30\" class=\"data row19 col30\" >0.0779724</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row20\" class=\"row_heading level0 row20\" >worst radius</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col0\" class=\"data row20 col0\" >0.969539</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col1\" class=\"data row20 col1\" >0.352573</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col2\" class=\"data row20 col2\" >0.969476</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col3\" class=\"data row20 col3\" >0.962746</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col4\" class=\"data row20 col4\" >0.21312</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col5\" class=\"data row20 col5\" >0.535315</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col6\" class=\"data row20 col6\" >0.688236</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col7\" class=\"data row20 col7\" >0.830318</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col8\" class=\"data row20 col8\" >0.185728</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col9\" class=\"data row20 col9\" >-0.253691</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col10\" class=\"data row20 col10\" >0.715065</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col11\" class=\"data row20 col11\" >-0.11169</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col12\" class=\"data row20 col12\" >0.697201</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col13\" class=\"data row20 col13\" >0.757373</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col14\" class=\"data row20 col14\" >-0.230691</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col15\" class=\"data row20 col15\" >0.204607</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col16\" class=\"data row20 col16\" >0.186904</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col17\" class=\"data row20 col17\" >0.358127</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col18\" class=\"data row20 col18\" >-0.128121</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col19\" class=\"data row20 col19\" >-0.0374876</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col20\" class=\"data row20 col20\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col21\" class=\"data row20 col21\" >0.359921</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col22\" class=\"data row20 col22\" >0.993708</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col23\" class=\"data row20 col23\" >0.984015</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col24\" class=\"data row20 col24\" >0.216574</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col25\" class=\"data row20 col25\" >0.47582</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col26\" class=\"data row20 col26\" >0.573975</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col27\" class=\"data row20 col27\" >0.787424</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col28\" class=\"data row20 col28\" >0.243529</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col29\" class=\"data row20 col29\" >0.093492</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row20_col30\" class=\"data row20 col30\" >0.776454</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row21\" class=\"row_heading level0 row21\" >worst texture</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col0\" class=\"data row21 col0\" >0.297008</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col1\" class=\"data row21 col1\" >0.912045</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col2\" class=\"data row21 col2\" >0.303038</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col3\" class=\"data row21 col3\" >0.287489</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col4\" class=\"data row21 col4\" >0.0360718</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col5\" class=\"data row21 col5\" >0.248133</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col6\" class=\"data row21 col6\" >0.299879</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col7\" class=\"data row21 col7\" >0.292752</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col8\" class=\"data row21 col8\" >0.0906507</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col9\" class=\"data row21 col9\" >-0.0512692</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col10\" class=\"data row21 col10\" >0.194799</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col11\" class=\"data row21 col11\" >0.409003</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col12\" class=\"data row21 col12\" >0.200371</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col13\" class=\"data row21 col13\" >0.196497</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col14\" class=\"data row21 col14\" >-0.074743</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col15\" class=\"data row21 col15\" >0.143003</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col16\" class=\"data row21 col16\" >0.100241</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col17\" class=\"data row21 col17\" >0.0867412</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col18\" class=\"data row21 col18\" >-0.0774734</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col19\" class=\"data row21 col19\" >-0.00319503</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col20\" class=\"data row21 col20\" >0.359921</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col21\" class=\"data row21 col21\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col22\" class=\"data row21 col22\" >0.365098</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col23\" class=\"data row21 col23\" >0.345842</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col24\" class=\"data row21 col24\" >0.225429</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col25\" class=\"data row21 col25\" >0.360832</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col26\" class=\"data row21 col26\" >0.368366</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col27\" class=\"data row21 col27\" >0.359755</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col28\" class=\"data row21 col28\" >0.233027</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col29\" class=\"data row21 col29\" >0.219122</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row21_col30\" class=\"data row21 col30\" >0.456903</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row22\" class=\"row_heading level0 row22\" >worst perimeter</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col0\" class=\"data row22 col0\" >0.965137</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col1\" class=\"data row22 col1\" >0.35804</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col2\" class=\"data row22 col2\" >0.970387</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col3\" class=\"data row22 col3\" >0.95912</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col4\" class=\"data row22 col4\" >0.238853</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col5\" class=\"data row22 col5\" >0.59021</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col6\" class=\"data row22 col6\" >0.729565</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col7\" class=\"data row22 col7\" >0.855923</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col8\" class=\"data row22 col8\" >0.219169</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col9\" class=\"data row22 col9\" >-0.205151</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col10\" class=\"data row22 col10\" >0.719684</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col11\" class=\"data row22 col11\" >-0.102242</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col12\" class=\"data row22 col12\" >0.721031</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col13\" class=\"data row22 col13\" >0.761213</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col14\" class=\"data row22 col14\" >-0.217304</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col15\" class=\"data row22 col15\" >0.260516</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col16\" class=\"data row22 col16\" >0.22668</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col17\" class=\"data row22 col17\" >0.394999</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col18\" class=\"data row22 col18\" >-0.103753</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col19\" class=\"data row22 col19\" >-0.0010004</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col20\" class=\"data row22 col20\" >0.993708</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col21\" class=\"data row22 col21\" >0.365098</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col22\" class=\"data row22 col22\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col23\" class=\"data row22 col23\" >0.977578</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col24\" class=\"data row22 col24\" >0.236775</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col25\" class=\"data row22 col25\" >0.529408</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col26\" class=\"data row22 col26\" >0.618344</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col27\" class=\"data row22 col27\" >0.816322</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col28\" class=\"data row22 col28\" >0.269493</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col29\" class=\"data row22 col29\" >0.138957</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row22_col30\" class=\"data row22 col30\" >0.782914</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row23\" class=\"row_heading level0 row23\" >worst area</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col0\" class=\"data row23 col0\" >0.941082</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col1\" class=\"data row23 col1\" >0.343546</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col2\" class=\"data row23 col2\" >0.94155</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col3\" class=\"data row23 col3\" >0.959213</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col4\" class=\"data row23 col4\" >0.206718</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col5\" class=\"data row23 col5\" >0.509604</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col6\" class=\"data row23 col6\" >0.675987</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col7\" class=\"data row23 col7\" >0.80963</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col8\" class=\"data row23 col8\" >0.177193</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col9\" class=\"data row23 col9\" >-0.231854</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col10\" class=\"data row23 col10\" >0.751548</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col11\" class=\"data row23 col11\" >-0.083195</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col12\" class=\"data row23 col12\" >0.730713</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col13\" class=\"data row23 col13\" >0.811408</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col14\" class=\"data row23 col14\" >-0.182195</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col15\" class=\"data row23 col15\" >0.199371</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col16\" class=\"data row23 col16\" >0.188353</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col17\" class=\"data row23 col17\" >0.342271</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col18\" class=\"data row23 col18\" >-0.110343</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col19\" class=\"data row23 col19\" >-0.0227361</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col20\" class=\"data row23 col20\" >0.984015</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col21\" class=\"data row23 col21\" >0.345842</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col22\" class=\"data row23 col22\" >0.977578</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col23\" class=\"data row23 col23\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col24\" class=\"data row23 col24\" >0.209145</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col25\" class=\"data row23 col25\" >0.438296</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col26\" class=\"data row23 col26\" >0.543331</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col27\" class=\"data row23 col27\" >0.747419</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col28\" class=\"data row23 col28\" >0.209146</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col29\" class=\"data row23 col29\" >0.079647</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row23_col30\" class=\"data row23 col30\" >0.733825</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row24\" class=\"row_heading level0 row24\" >worst smoothness</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col0\" class=\"data row24 col0\" >0.119616</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col1\" class=\"data row24 col1\" >0.0775034</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col2\" class=\"data row24 col2\" >0.150549</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col3\" class=\"data row24 col3\" >0.123523</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col4\" class=\"data row24 col4\" >0.805324</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col5\" class=\"data row24 col5\" >0.565541</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col6\" class=\"data row24 col6\" >0.448822</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col7\" class=\"data row24 col7\" >0.452753</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col8\" class=\"data row24 col8\" >0.426675</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col9\" class=\"data row24 col9\" >0.504942</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col10\" class=\"data row24 col10\" >0.141919</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col11\" class=\"data row24 col11\" >-0.0736577</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col12\" class=\"data row24 col12\" >0.130054</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col13\" class=\"data row24 col13\" >0.125389</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col14\" class=\"data row24 col14\" >0.314457</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col15\" class=\"data row24 col15\" >0.227394</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col16\" class=\"data row24 col16\" >0.168481</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col17\" class=\"data row24 col17\" >0.215351</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col18\" class=\"data row24 col18\" >-0.0126618</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col19\" class=\"data row24 col19\" >0.170568</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col20\" class=\"data row24 col20\" >0.216574</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col21\" class=\"data row24 col21\" >0.225429</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col22\" class=\"data row24 col22\" >0.236775</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col23\" class=\"data row24 col23\" >0.209145</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col24\" class=\"data row24 col24\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col25\" class=\"data row24 col25\" >0.568187</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col26\" class=\"data row24 col26\" >0.518523</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col27\" class=\"data row24 col27\" >0.547691</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col28\" class=\"data row24 col28\" >0.493838</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col29\" class=\"data row24 col29\" >0.617624</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row24_col30\" class=\"data row24 col30\" >0.421465</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row25\" class=\"row_heading level0 row25\" >worst compactness</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col0\" class=\"data row25 col0\" >0.413463</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col1\" class=\"data row25 col1\" >0.27783</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col2\" class=\"data row25 col2\" >0.455774</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col3\" class=\"data row25 col3\" >0.39041</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col4\" class=\"data row25 col4\" >0.472468</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col5\" class=\"data row25 col5\" >0.865809</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col6\" class=\"data row25 col6\" >0.754968</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col7\" class=\"data row25 col7\" >0.667454</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col8\" class=\"data row25 col8\" >0.4732</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col9\" class=\"data row25 col9\" >0.458798</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col10\" class=\"data row25 col10\" >0.287103</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col11\" class=\"data row25 col11\" >-0.0924394</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col12\" class=\"data row25 col12\" >0.341919</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col13\" class=\"data row25 col13\" >0.283257</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col14\" class=\"data row25 col14\" >-0.0555581</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col15\" class=\"data row25 col15\" >0.67878</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col16\" class=\"data row25 col16\" >0.484858</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col17\" class=\"data row25 col17\" >0.452888</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col18\" class=\"data row25 col18\" >0.0602549</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col19\" class=\"data row25 col19\" >0.390159</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col20\" class=\"data row25 col20\" >0.47582</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col21\" class=\"data row25 col21\" >0.360832</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col22\" class=\"data row25 col22\" >0.529408</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col23\" class=\"data row25 col23\" >0.438296</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col24\" class=\"data row25 col24\" >0.568187</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col25\" class=\"data row25 col25\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col26\" class=\"data row25 col26\" >0.892261</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col27\" class=\"data row25 col27\" >0.80108</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col28\" class=\"data row25 col28\" >0.614441</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col29\" class=\"data row25 col29\" >0.810455</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row25_col30\" class=\"data row25 col30\" >0.590998</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row26\" class=\"row_heading level0 row26\" >worst concavity</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col0\" class=\"data row26 col0\" >0.526911</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col1\" class=\"data row26 col1\" >0.301025</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col2\" class=\"data row26 col2\" >0.563879</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col3\" class=\"data row26 col3\" >0.512606</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col4\" class=\"data row26 col4\" >0.434926</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col5\" class=\"data row26 col5\" >0.816275</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col6\" class=\"data row26 col6\" >0.884103</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col7\" class=\"data row26 col7\" >0.752399</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col8\" class=\"data row26 col8\" >0.433721</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col9\" class=\"data row26 col9\" >0.346234</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col10\" class=\"data row26 col10\" >0.380585</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col11\" class=\"data row26 col11\" >-0.0689562</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col12\" class=\"data row26 col12\" >0.418899</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col13\" class=\"data row26 col13\" >0.3851</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col14\" class=\"data row26 col14\" >-0.0582984</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col15\" class=\"data row26 col15\" >0.639147</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col16\" class=\"data row26 col16\" >0.662564</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col17\" class=\"data row26 col17\" >0.549592</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col18\" class=\"data row26 col18\" >0.037119</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col19\" class=\"data row26 col19\" >0.379975</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col20\" class=\"data row26 col20\" >0.573975</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col21\" class=\"data row26 col21\" >0.368366</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col22\" class=\"data row26 col22\" >0.618344</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col23\" class=\"data row26 col23\" >0.543331</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col24\" class=\"data row26 col24\" >0.518523</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col25\" class=\"data row26 col25\" >0.892261</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col26\" class=\"data row26 col26\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col27\" class=\"data row26 col27\" >0.855434</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col28\" class=\"data row26 col28\" >0.53252</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col29\" class=\"data row26 col29\" >0.686511</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row26_col30\" class=\"data row26 col30\" >0.65961</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row27\" class=\"row_heading level0 row27\" >worst concave points</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col0\" class=\"data row27 col0\" >0.744214</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col1\" class=\"data row27 col1\" >0.295316</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col2\" class=\"data row27 col2\" >0.771241</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col3\" class=\"data row27 col3\" >0.722017</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col4\" class=\"data row27 col4\" >0.503053</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col5\" class=\"data row27 col5\" >0.815573</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col6\" class=\"data row27 col6\" >0.861323</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col7\" class=\"data row27 col7\" >0.910155</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col8\" class=\"data row27 col8\" >0.430297</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col9\" class=\"data row27 col9\" >0.175325</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col10\" class=\"data row27 col10\" >0.531062</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col11\" class=\"data row27 col11\" >-0.119638</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col12\" class=\"data row27 col12\" >0.554897</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col13\" class=\"data row27 col13\" >0.538166</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col14\" class=\"data row27 col14\" >-0.102007</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col15\" class=\"data row27 col15\" >0.483208</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col16\" class=\"data row27 col16\" >0.440472</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col17\" class=\"data row27 col17\" >0.60245</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col18\" class=\"data row27 col18\" >-0.0304134</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col19\" class=\"data row27 col19\" >0.215204</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col20\" class=\"data row27 col20\" >0.787424</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col21\" class=\"data row27 col21\" >0.359755</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col22\" class=\"data row27 col22\" >0.816322</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col23\" class=\"data row27 col23\" >0.747419</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col24\" class=\"data row27 col24\" >0.547691</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col25\" class=\"data row27 col25\" >0.80108</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col26\" class=\"data row27 col26\" >0.855434</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col27\" class=\"data row27 col27\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col28\" class=\"data row27 col28\" >0.502528</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col29\" class=\"data row27 col29\" >0.511114</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row27_col30\" class=\"data row27 col30\" >0.793566</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row28\" class=\"row_heading level0 row28\" >worst symmetry</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col0\" class=\"data row28 col0\" >0.163953</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col1\" class=\"data row28 col1\" >0.105008</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col2\" class=\"data row28 col2\" >0.189115</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col3\" class=\"data row28 col3\" >0.14357</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col4\" class=\"data row28 col4\" >0.394309</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col5\" class=\"data row28 col5\" >0.510223</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col6\" class=\"data row28 col6\" >0.409464</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col7\" class=\"data row28 col7\" >0.375744</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col8\" class=\"data row28 col8\" >0.699826</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col9\" class=\"data row28 col9\" >0.334019</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col10\" class=\"data row28 col10\" >0.0945428</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col11\" class=\"data row28 col11\" >-0.128215</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col12\" class=\"data row28 col12\" >0.10993</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col13\" class=\"data row28 col13\" >0.0741263</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col14\" class=\"data row28 col14\" >-0.107342</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col15\" class=\"data row28 col15\" >0.277878</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col16\" class=\"data row28 col16\" >0.197788</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col17\" class=\"data row28 col17\" >0.143116</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col18\" class=\"data row28 col18\" >0.389402</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col19\" class=\"data row28 col19\" >0.111094</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col20\" class=\"data row28 col20\" >0.243529</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col21\" class=\"data row28 col21\" >0.233027</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col22\" class=\"data row28 col22\" >0.269493</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col23\" class=\"data row28 col23\" >0.209146</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col24\" class=\"data row28 col24\" >0.493838</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col25\" class=\"data row28 col25\" >0.614441</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col26\" class=\"data row28 col26\" >0.53252</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col27\" class=\"data row28 col27\" >0.502528</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col28\" class=\"data row28 col28\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col29\" class=\"data row28 col29\" >0.537848</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row28_col30\" class=\"data row28 col30\" >0.416294</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row29\" class=\"row_heading level0 row29\" >worst fractal dimension</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col0\" class=\"data row29 col0\" >0.00706589</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col1\" class=\"data row29 col1\" >0.119205</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col2\" class=\"data row29 col2\" >0.0510185</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col3\" class=\"data row29 col3\" >0.0037376</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col4\" class=\"data row29 col4\" >0.499316</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col5\" class=\"data row29 col5\" >0.687382</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col6\" class=\"data row29 col6\" >0.51493</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col7\" class=\"data row29 col7\" >0.368661</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col8\" class=\"data row29 col8\" >0.438413</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col9\" class=\"data row29 col9\" >0.767297</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col10\" class=\"data row29 col10\" >0.0495594</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col11\" class=\"data row29 col11\" >-0.0456546</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col12\" class=\"data row29 col12\" >0.0854326</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col13\" class=\"data row29 col13\" >0.0175393</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col14\" class=\"data row29 col14\" >0.10148</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col15\" class=\"data row29 col15\" >0.590973</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col16\" class=\"data row29 col16\" >0.439329</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col17\" class=\"data row29 col17\" >0.310655</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col18\" class=\"data row29 col18\" >0.0780795</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col19\" class=\"data row29 col19\" >0.591328</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col20\" class=\"data row29 col20\" >0.093492</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col21\" class=\"data row29 col21\" >0.219122</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col22\" class=\"data row29 col22\" >0.138957</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col23\" class=\"data row29 col23\" >0.079647</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col24\" class=\"data row29 col24\" >0.617624</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col25\" class=\"data row29 col25\" >0.810455</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col26\" class=\"data row29 col26\" >0.686511</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col27\" class=\"data row29 col27\" >0.511114</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col28\" class=\"data row29 col28\" >0.537848</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col29\" class=\"data row29 col29\" >1</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row29_col30\" class=\"data row29 col30\" >0.323872</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9level0_row30\" class=\"row_heading level0 row30\" >outcome</th>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col0\" class=\"data row30 col0\" >0.730029</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col1\" class=\"data row30 col1\" >0.415185</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col2\" class=\"data row30 col2\" >0.742636</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col3\" class=\"data row30 col3\" >0.708984</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col4\" class=\"data row30 col4\" >0.35856</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col5\" class=\"data row30 col5\" >0.596534</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col6\" class=\"data row30 col6\" >0.69636</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col7\" class=\"data row30 col7\" >0.776614</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col8\" class=\"data row30 col8\" >0.330499</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col9\" class=\"data row30 col9\" >-0.0128376</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col10\" class=\"data row30 col10\" >0.567134</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col11\" class=\"data row30 col11\" >-0.00830333</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col12\" class=\"data row30 col12\" >0.556141</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col13\" class=\"data row30 col13\" >0.548236</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col14\" class=\"data row30 col14\" >-0.067016</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col15\" class=\"data row30 col15\" >0.292999</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col16\" class=\"data row30 col16\" >0.25373</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col17\" class=\"data row30 col17\" >0.408042</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col18\" class=\"data row30 col18\" >-0.00652176</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col19\" class=\"data row30 col19\" >0.0779724</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col20\" class=\"data row30 col20\" >0.776454</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col21\" class=\"data row30 col21\" >0.456903</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col22\" class=\"data row30 col22\" >0.782914</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col23\" class=\"data row30 col23\" >0.733825</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col24\" class=\"data row30 col24\" >0.421465</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col25\" class=\"data row30 col25\" >0.590998</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col26\" class=\"data row30 col26\" >0.65961</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col27\" class=\"data row30 col27\" >0.793566</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col28\" class=\"data row30 col28\" >0.416294</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col29\" class=\"data row30 col29\" >0.323872</td>\n",
       "                        <td id=\"T_13c3854a_5e6d_11eb_b499_a683e79d3fb9row30_col30\" class=\"data row30 col30\" >1</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fa66f465b70>"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.corr().style.background_gradient('coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 12.\tImport number column as string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>row_id</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_date</th>\n",
       "      <th>ship_date</th>\n",
       "      <th>ship_mode</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>customer_name</th>\n",
       "      <th>segment</th>\n",
       "      <th>country</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>postal_code</th>\n",
       "      <th>region</th>\n",
       "      <th>product_id</th>\n",
       "      <th>category</th>\n",
       "      <th>sub_category</th>\n",
       "      <th>product_name</th>\n",
       "      <th>sales</th>\n",
       "      <th>quantity</th>\n",
       "      <th>discount</th>\n",
       "      <th>profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>CA-2017-152156</td>\n",
       "      <td>2017-11-08</td>\n",
       "      <td>2017-11-11</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>CG-12520</td>\n",
       "      <td>Claire Gute</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>42420</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-BO-10001798</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Bookcases</td>\n",
       "      <td>Bush Somerset Collection Bookcase</td>\n",
       "      <td>261.9600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.9136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>CA-2017-152156</td>\n",
       "      <td>2017-11-08</td>\n",
       "      <td>2017-11-11</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>CG-12520</td>\n",
       "      <td>Claire Gute</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>42420</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-CH-10000454</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Chairs</td>\n",
       "      <td>Hon Deluxe Fabric Upholstered Stacking Chairs,...</td>\n",
       "      <td>731.9400</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>219.5820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>CA-2017-138688</td>\n",
       "      <td>2017-06-12</td>\n",
       "      <td>2017-06-16</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>DV-13045</td>\n",
       "      <td>Darrin Van Huff</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-LA-10000240</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Labels</td>\n",
       "      <td>Self-Adhesive Address Labels for Typewriters b...</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.8714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>US-2016-108966</td>\n",
       "      <td>2016-10-11</td>\n",
       "      <td>2016-10-18</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SO-20335</td>\n",
       "      <td>Sean O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>Florida</td>\n",
       "      <td>33311</td>\n",
       "      <td>South</td>\n",
       "      <td>FUR-TA-10000577</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Tables</td>\n",
       "      <td>Bretford CR4500 Series Slim Rectangular Table</td>\n",
       "      <td>957.5775</td>\n",
       "      <td>5</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-383.0310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>US-2016-108966</td>\n",
       "      <td>2016-10-11</td>\n",
       "      <td>2016-10-18</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SO-20335</td>\n",
       "      <td>Sean O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>Florida</td>\n",
       "      <td>33311</td>\n",
       "      <td>South</td>\n",
       "      <td>OFF-ST-10000760</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Eldon Fold 'N Roll Cart System</td>\n",
       "      <td>22.3680</td>\n",
       "      <td>2</td>\n",
       "      <td>0.20</td>\n",
       "      <td>2.5164</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   row_id        order_id  order_date   ship_date       ship_mode customer_id  \\\n",
       "0       1  CA-2017-152156  2017-11-08  2017-11-11    Second Class    CG-12520   \n",
       "1       2  CA-2017-152156  2017-11-08  2017-11-11    Second Class    CG-12520   \n",
       "2       3  CA-2017-138688  2017-06-12  2017-06-16    Second Class    DV-13045   \n",
       "3       4  US-2016-108966  2016-10-11  2016-10-18  Standard Class    SO-20335   \n",
       "4       5  US-2016-108966  2016-10-11  2016-10-18  Standard Class    SO-20335   \n",
       "\n",
       "     customer_name    segment        country             city       state  \\\n",
       "0      Claire Gute   Consumer  United States        Henderson    Kentucky   \n",
       "1      Claire Gute   Consumer  United States        Henderson    Kentucky   \n",
       "2  Darrin Van Huff  Corporate  United States      Los Angeles  California   \n",
       "3   Sean O'Donnell   Consumer  United States  Fort Lauderdale     Florida   \n",
       "4   Sean O'Donnell   Consumer  United States  Fort Lauderdale     Florida   \n",
       "\n",
       "  postal_code region       product_id         category sub_category  \\\n",
       "0       42420  South  FUR-BO-10001798        Furniture    Bookcases   \n",
       "1       42420  South  FUR-CH-10000454        Furniture       Chairs   \n",
       "2       90036   West  OFF-LA-10000240  Office Supplies       Labels   \n",
       "3       33311  South  FUR-TA-10000577        Furniture       Tables   \n",
       "4       33311  South  OFF-ST-10000760  Office Supplies      Storage   \n",
       "\n",
       "                                        product_name     sales  quantity  \\\n",
       "0                  Bush Somerset Collection Bookcase  261.9600         2   \n",
       "1  Hon Deluxe Fabric Upholstered Stacking Chairs,...  731.9400         3   \n",
       "2  Self-Adhesive Address Labels for Typewriters b...   14.6200         2   \n",
       "3      Bretford CR4500 Series Slim Rectangular Table  957.5775         5   \n",
       "4                     Eldon Fold 'N Roll Cart System   22.3680         2   \n",
       "\n",
       "   discount    profit  \n",
       "0      0.00   41.9136  \n",
       "1      0.00  219.5820  \n",
       "2      0.00    6.8714  \n",
       "3      0.45 -383.0310  \n",
       "4      0.20    2.5164  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(superstore_orders, dtype= {'postal_code':'str'})\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 9994 entries, 0 to 9993\n",
      "Data columns (total 21 columns):\n",
      "row_id           9994 non-null int64\n",
      "order_id         9994 non-null object\n",
      "order_date       9994 non-null object\n",
      "ship_date        9994 non-null object\n",
      "ship_mode        9994 non-null object\n",
      "customer_id      9994 non-null object\n",
      "customer_name    9994 non-null object\n",
      "segment          9994 non-null object\n",
      "country          9994 non-null object\n",
      "city             9994 non-null object\n",
      "state            9994 non-null object\n",
      "postal_code      9983 non-null object\n",
      "region           9994 non-null object\n",
      "product_id       9994 non-null object\n",
      "category         9994 non-null object\n",
      "sub_category     9994 non-null object\n",
      "product_name     9994 non-null object\n",
      "sales            9994 non-null float64\n",
      "quantity         9994 non-null int64\n",
      "discount         9994 non-null float64\n",
      "profit           9994 non-null float64\n",
      "dtypes: float64(3), int64(2), object(16)\n",
      "memory usage: 1.6+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 13.\tRead date column from data as Index in DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-01</th>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-01</th>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04-01</th>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-01</th>\n",
       "      <td>180</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Sales\n",
       "Month            \n",
       "2016-01-01    266\n",
       "2016-02-01    146\n",
       "2016-03-01    183\n",
       "2016-04-01    119\n",
       "2016-05-01    180"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(car_sales,index_col='Month',parse_dates=['Month'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 14.\tRead data only specific columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>race</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>Private</td>\n",
       "      <td>11th</td>\n",
       "      <td>Black</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28</td>\n",
       "      <td>Private</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>Black</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age          workclass   education    race\n",
       "0   39          State-gov   Bachelors   White\n",
       "1   50   Self-emp-not-inc   Bachelors   White\n",
       "2   38            Private     HS-grad   White\n",
       "3   53            Private        11th   Black\n",
       "4   28            Private   Bachelors   Black"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(adult, usecols=['age','workclass','education','race'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 15.\tFind percentage of records with missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_model</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160</td>\n",
       "      <td>110.0</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.62</td>\n",
       "      <td>16.46</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mazda RX4 Wag</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>$</td>\n",
       "      <td>110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.875</td>\n",
       "      <td>*</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>108</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.85</td>\n",
       "      <td>?</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hornet 4 Drive</td>\n",
       "      <td>999.0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.215</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.32</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        car_model    mpg  cyl disp     hp  drat     wt   qsec  vs  am  gear  \\\n",
       "0       Mazda RX4   21.0    6  160  110.0  3.90   2.62  16.46   0   1     4   \n",
       "1   Mazda RX4 Wag   21.0    6    $  110.0   NaN  2.875      *   0   1     4   \n",
       "2      Datsun 710    NaN    4  108    NaN  3.85      ?  18.61   1   1     4   \n",
       "3  Hornet 4 Drive  999.0    6  NaN    NaN  3.08  3.215      -   1   0     3   \n",
       "4      Datsun 710   22.8    4  NaN   93.0  3.85   2.32  18.61   1   1     4   \n",
       "\n",
       "   carb  \n",
       "0     4  \n",
       "1     4  \n",
       "2     1  \n",
       "3     1  \n",
       "4     1  "
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(mtcars_missing)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_model</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160</td>\n",
       "      <td>110.0</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.62</td>\n",
       "      <td>16.46</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mazda RX4 Wag</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>108</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hornet 4 Drive</td>\n",
       "      <td>999.0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.215</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.32</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        car_model    mpg  cyl disp     hp  drat     wt   qsec  vs  am  gear  \\\n",
       "0       Mazda RX4   21.0    6  160  110.0  3.90   2.62  16.46   0   1     4   \n",
       "1   Mazda RX4 Wag   21.0    6  NaN  110.0   NaN  2.875    NaN   0   1     4   \n",
       "2      Datsun 710    NaN    4  108    NaN  3.85    NaN  18.61   1   1     4   \n",
       "3  Hornet 4 Drive  999.0    6  NaN    NaN  3.08  3.215    NaN   1   0     3   \n",
       "4      Datsun 710   22.8    4  NaN   93.0  3.85   2.32  18.61   1   1     4   \n",
       "\n",
       "   carb  \n",
       "0     4  \n",
       "1     4  \n",
       "2     1  \n",
       "3     1  \n",
       "4     1  "
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.replace(['$','*','-','?'],np.nan,inplace=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "car_model     0\n",
       "mpg           1\n",
       "cyl           0\n",
       "disp          9\n",
       "hp            2\n",
       "drat          1\n",
       "wt            6\n",
       "qsec         14\n",
       "vs            0\n",
       "am            0\n",
       "gear          0\n",
       "carb          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11, 12)"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dropna().shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65.625"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(data.shape[0]-data.dropna().shape[0])*100/data.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 16.\tReading Multiple Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IP</th>\n",
       "      <th>Time</th>\n",
       "      <th>URL</th>\n",
       "      <th>Staus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:38</td>\n",
       "      <td>GET /home.php HTTP/1.1</td>\n",
       "      <td>302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:38</td>\n",
       "      <td>GET /login.php HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /css/bootstrap.min.css HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.131.0.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /css/font-awesome.min.css HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /css/normalize.css HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           IP                  Time                                     URL  \\\n",
       "0  10.128.2.1  15/Feb/2018:03:10:38                  GET /home.php HTTP/1.1   \n",
       "1  10.128.2.1  15/Feb/2018:03:10:38                 GET /login.php HTTP/1.1   \n",
       "2  10.128.2.1  15/Feb/2018:03:10:39     GET /css/bootstrap.min.css HTTP/1.1   \n",
       "3  10.131.0.1  15/Feb/2018:03:10:39  GET /css/font-awesome.min.css HTTP/1.1   \n",
       "4  10.130.2.1  15/Feb/2018:03:10:39         GET /css/normalize.css HTTP/1.1   \n",
       "\n",
       "   Staus  \n",
       "0    302  \n",
       "1    200  \n",
       "2    200  \n",
       "3    200  \n",
       "4    200  "
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('log-15feb18.txt')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['log-15feb18.txt',\n",
       " 'log-16feb18.txt',\n",
       " 'log-17feb18.txt',\n",
       " 'log-18feb18.txt',\n",
       " 'log-19feb18.txt']"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from glob import glob\n",
    "files = glob(\"log*\")\n",
    "files.sort()\n",
    "files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(33, 4)"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('log-16feb18.txt')\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IP</th>\n",
       "      <th>Time</th>\n",
       "      <th>URL</th>\n",
       "      <th>Staus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:38</td>\n",
       "      <td>GET /home.php HTTP/1.1</td>\n",
       "      <td>302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:38</td>\n",
       "      <td>GET /login.php HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /css/bootstrap.min.css HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.131.0.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /css/font-awesome.min.css HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /css/normalize.css HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /css/main.css HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10.131.0.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /css/style.css HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /js/vendor/modernizr-2.8.3.min.js HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /js/vendor/jquery-1.12.0.min.js HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.131.0.1</td>\n",
       "      <td>15/Feb/2018:03:10:39</td>\n",
       "      <td>GET /bootstrap-3.3.7/js/bootstrap.min.js HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10.131.0.1</td>\n",
       "      <td>15/Feb/2018:03:10:41</td>\n",
       "      <td>GET /fonts/fontawesome-webfont.woff2?v=4.6.3 H...</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:42</td>\n",
       "      <td>GET /img/ruet.png HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>15/Feb/2018:03:10:42</td>\n",
       "      <td>GET / HTTP/1.1</td>\n",
       "      <td>302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>15/Feb/2018:13:22:04</td>\n",
       "      <td>GET /login.php HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:17:06:12</td>\n",
       "      <td>GET / HTTP/1.1</td>\n",
       "      <td>302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:17:06:12</td>\n",
       "      <td>GET /login.php HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:17:06:12</td>\n",
       "      <td>GET /img/ruet.png HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:22:19:51</td>\n",
       "      <td>GET /robots.txt HTTP/1.1</td>\n",
       "      <td>404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>15/Feb/2018:22:19:55</td>\n",
       "      <td>GET / HTTP/1.1</td>\n",
       "      <td>302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>15/Feb/2018:22:19:59</td>\n",
       "      <td>GET /login.php HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>16/Feb/2018:04:47:15</td>\n",
       "      <td>GET /robots.txt HTTP/1.1</td>\n",
       "      <td>404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>16/Feb/2018:11:37:22</td>\n",
       "      <td>GET /robots.txt HTTP/1.1</td>\n",
       "      <td>404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>10.128.2.1</td>\n",
       "      <td>16/Feb/2018:11:37:26</td>\n",
       "      <td>GET / HTTP/1.1</td>\n",
       "      <td>302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>16/Feb/2018:11:37:30</td>\n",
       "      <td>GET /login.php HTTP/1.1</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10.130.2.1</td>\n",
       "      <td>16/Feb/2018:11:40:26</td>\n",
       "      <td>GET /home.php HTTP/1.1</td>\n",
       "      <td>302</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            IP                  Time  \\\n",
       "0   10.128.2.1  15/Feb/2018:03:10:38   \n",
       "1   10.128.2.1  15/Feb/2018:03:10:38   \n",
       "2   10.128.2.1  15/Feb/2018:03:10:39   \n",
       "3   10.131.0.1  15/Feb/2018:03:10:39   \n",
       "4   10.130.2.1  15/Feb/2018:03:10:39   \n",
       "5   10.128.2.1  15/Feb/2018:03:10:39   \n",
       "6   10.131.0.1  15/Feb/2018:03:10:39   \n",
       "7   10.130.2.1  15/Feb/2018:03:10:39   \n",
       "8   10.130.2.1  15/Feb/2018:03:10:39   \n",
       "9   10.131.0.1  15/Feb/2018:03:10:39   \n",
       "10  10.131.0.1  15/Feb/2018:03:10:41   \n",
       "11  10.130.2.1  15/Feb/2018:03:10:42   \n",
       "12  10.130.2.1  15/Feb/2018:03:10:42   \n",
       "13  10.130.2.1  15/Feb/2018:13:22:04   \n",
       "14  10.128.2.1  15/Feb/2018:17:06:12   \n",
       "15  10.128.2.1  15/Feb/2018:17:06:12   \n",
       "16  10.128.2.1  15/Feb/2018:17:06:12   \n",
       "17  10.128.2.1  15/Feb/2018:22:19:51   \n",
       "18  10.128.2.1  15/Feb/2018:22:19:55   \n",
       "19  10.130.2.1  15/Feb/2018:22:19:59   \n",
       "20  10.130.2.1  16/Feb/2018:04:47:15   \n",
       "21  10.128.2.1  16/Feb/2018:11:37:22   \n",
       "22  10.128.2.1  16/Feb/2018:11:37:26   \n",
       "23  10.130.2.1  16/Feb/2018:11:37:30   \n",
       "24  10.130.2.1  16/Feb/2018:11:40:26   \n",
       "\n",
       "                                                  URL  Staus  \n",
       "0                              GET /home.php HTTP/1.1    302  \n",
       "1                             GET /login.php HTTP/1.1    200  \n",
       "2                 GET /css/bootstrap.min.css HTTP/1.1    200  \n",
       "3              GET /css/font-awesome.min.css HTTP/1.1    200  \n",
       "4                     GET /css/normalize.css HTTP/1.1    200  \n",
       "5                          GET /css/main.css HTTP/1.1    200  \n",
       "6                         GET /css/style.css HTTP/1.1    200  \n",
       "7      GET /js/vendor/modernizr-2.8.3.min.js HTTP/1.1    200  \n",
       "8        GET /js/vendor/jquery-1.12.0.min.js HTTP/1.1    200  \n",
       "9   GET /bootstrap-3.3.7/js/bootstrap.min.js HTTP/1.1    200  \n",
       "10  GET /fonts/fontawesome-webfont.woff2?v=4.6.3 H...    200  \n",
       "11                         GET /img/ruet.png HTTP/1.1    200  \n",
       "12                                     GET / HTTP/1.1    302  \n",
       "13                            GET /login.php HTTP/1.1    200  \n",
       "14                                     GET / HTTP/1.1    302  \n",
       "15                            GET /login.php HTTP/1.1    200  \n",
       "16                         GET /img/ruet.png HTTP/1.1    200  \n",
       "17                           GET /robots.txt HTTP/1.1    404  \n",
       "18                                     GET / HTTP/1.1    302  \n",
       "19                            GET /login.php HTTP/1.1    200  \n",
       "20                           GET /robots.txt HTTP/1.1    404  \n",
       "21                           GET /robots.txt HTTP/1.1    404  \n",
       "22                                     GET / HTTP/1.1    302  \n",
       "23                            GET /login.php HTTP/1.1    200  \n",
       "24                             GET /home.php HTTP/1.1    302  "
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.concat( (pd.read_csv(file) for file in files),ignore_index=True)\n",
    "data.head(25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(184, 4)"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 17.\tRearrange Numerical and Categorical Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>fnlwgt</th>\n",
       "      <th>education</th>\n",
       "      <th>educationNum</th>\n",
       "      <th>marital</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>sex</th>\n",
       "      <th>capGain</th>\n",
       "      <th>capLoss</th>\n",
       "      <th>HoursWeek</th>\n",
       "      <th>NativeCountry</th>\n",
       "      <th>category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>77516</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>83311</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>215646</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>Private</td>\n",
       "      <td>234721</td>\n",
       "      <td>11th</td>\n",
       "      <td>7</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28</td>\n",
       "      <td>Private</td>\n",
       "      <td>338409</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Wife</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>Cuba</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age          workclass  fnlwgt   education  educationNum  \\\n",
       "0   39          State-gov   77516   Bachelors            13   \n",
       "1   50   Self-emp-not-inc   83311   Bachelors            13   \n",
       "2   38            Private  215646     HS-grad             9   \n",
       "3   53            Private  234721        11th             7   \n",
       "4   28            Private  338409   Bachelors            13   \n",
       "\n",
       "               marital          occupation    relationship    race      sex  \\\n",
       "0        Never-married        Adm-clerical   Not-in-family   White     Male   \n",
       "1   Married-civ-spouse     Exec-managerial         Husband   White     Male   \n",
       "2             Divorced   Handlers-cleaners   Not-in-family   White     Male   \n",
       "3   Married-civ-spouse   Handlers-cleaners         Husband   Black     Male   \n",
       "4   Married-civ-spouse      Prof-specialty            Wife   Black   Female   \n",
       "\n",
       "   capGain  capLoss  HoursWeek   NativeCountry category  \n",
       "0     2174        0         40   United-States    <=50K  \n",
       "1        0        0         13   United-States    <=50K  \n",
       "2        0        0         40   United-States    <=50K  \n",
       "3        0        0         40   United-States    <=50K  \n",
       "4        0        0         40            Cuba    <=50K  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(adult)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>marital</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>sex</th>\n",
       "      <th>NativeCountry</th>\n",
       "      <th>category</th>\n",
       "      <th>age</th>\n",
       "      <th>fnlwgt</th>\n",
       "      <th>educationNum</th>\n",
       "      <th>capGain</th>\n",
       "      <th>capLoss</th>\n",
       "      <th>HoursWeek</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>State-gov</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>39</td>\n",
       "      <td>77516</td>\n",
       "      <td>13</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>50</td>\n",
       "      <td>83311</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Private</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>38</td>\n",
       "      <td>215646</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Private</td>\n",
       "      <td>11th</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>53</td>\n",
       "      <td>234721</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Private</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Wife</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>Cuba</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>28</td>\n",
       "      <td>338409</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32556</th>\n",
       "      <td>Private</td>\n",
       "      <td>Assoc-acdm</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Tech-support</td>\n",
       "      <td>Wife</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>27</td>\n",
       "      <td>257302</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32557</th>\n",
       "      <td>Private</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Machine-op-inspct</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "      <td>40</td>\n",
       "      <td>154374</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32558</th>\n",
       "      <td>Private</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>Widowed</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>58</td>\n",
       "      <td>151910</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32559</th>\n",
       "      <td>Private</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Own-child</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>22</td>\n",
       "      <td>201490</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32560</th>\n",
       "      <td>Self-emp-inc</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Wife</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "      <td>52</td>\n",
       "      <td>287927</td>\n",
       "      <td>9</td>\n",
       "      <td>15024</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32561 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               workclass    education              marital  \\\n",
       "0              State-gov    Bachelors        Never-married   \n",
       "1       Self-emp-not-inc    Bachelors   Married-civ-spouse   \n",
       "2                Private      HS-grad             Divorced   \n",
       "3                Private         11th   Married-civ-spouse   \n",
       "4                Private    Bachelors   Married-civ-spouse   \n",
       "...                  ...          ...                  ...   \n",
       "32556            Private   Assoc-acdm   Married-civ-spouse   \n",
       "32557            Private      HS-grad   Married-civ-spouse   \n",
       "32558            Private      HS-grad              Widowed   \n",
       "32559            Private      HS-grad        Never-married   \n",
       "32560       Self-emp-inc      HS-grad   Married-civ-spouse   \n",
       "\n",
       "               occupation    relationship    race      sex   NativeCountry  \\\n",
       "0            Adm-clerical   Not-in-family   White     Male   United-States   \n",
       "1         Exec-managerial         Husband   White     Male   United-States   \n",
       "2       Handlers-cleaners   Not-in-family   White     Male   United-States   \n",
       "3       Handlers-cleaners         Husband   Black     Male   United-States   \n",
       "4          Prof-specialty            Wife   Black   Female            Cuba   \n",
       "...                   ...             ...     ...      ...             ...   \n",
       "32556        Tech-support            Wife   White   Female   United-States   \n",
       "32557   Machine-op-inspct         Husband   White     Male   United-States   \n",
       "32558        Adm-clerical       Unmarried   White   Female   United-States   \n",
       "32559        Adm-clerical       Own-child   White     Male   United-States   \n",
       "32560     Exec-managerial            Wife   White   Female   United-States   \n",
       "\n",
       "      category  age  fnlwgt  educationNum  capGain  capLoss  HoursWeek  \n",
       "0        <=50K   39   77516            13     2174        0         40  \n",
       "1        <=50K   50   83311            13        0        0         13  \n",
       "2        <=50K   38  215646             9        0        0         40  \n",
       "3        <=50K   53  234721             7        0        0         40  \n",
       "4        <=50K   28  338409            13        0        0         40  \n",
       "...        ...  ...     ...           ...      ...      ...        ...  \n",
       "32556    <=50K   27  257302            12        0        0         38  \n",
       "32557     >50K   40  154374             9        0        0         40  \n",
       "32558    <=50K   58  151910             9        0        0         40  \n",
       "32559    <=50K   22  201490             9        0        0         20  \n",
       "32560     >50K   52  287927             9    15024        0         40  \n",
       "\n",
       "[32561 rows x 15 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.concat((data.select_dtypes(include='object'),data.select_dtypes(exclude='object')),axis=1)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 18.\tLabel encoding multiple columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>marital</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>sex</th>\n",
       "      <th>NativeCountry</th>\n",
       "      <th>category</th>\n",
       "      <th>age</th>\n",
       "      <th>fnlwgt</th>\n",
       "      <th>educationNum</th>\n",
       "      <th>capGain</th>\n",
       "      <th>capLoss</th>\n",
       "      <th>HoursWeek</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>State-gov</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>39</td>\n",
       "      <td>77516</td>\n",
       "      <td>13</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>50</td>\n",
       "      <td>83311</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Private</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>38</td>\n",
       "      <td>215646</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Private</td>\n",
       "      <td>11th</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>53</td>\n",
       "      <td>234721</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Private</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Wife</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>Cuba</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>28</td>\n",
       "      <td>338409</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           workclass   education              marital          occupation  \\\n",
       "0          State-gov   Bachelors        Never-married        Adm-clerical   \n",
       "1   Self-emp-not-inc   Bachelors   Married-civ-spouse     Exec-managerial   \n",
       "2            Private     HS-grad             Divorced   Handlers-cleaners   \n",
       "3            Private        11th   Married-civ-spouse   Handlers-cleaners   \n",
       "4            Private   Bachelors   Married-civ-spouse      Prof-specialty   \n",
       "\n",
       "     relationship    race      sex   NativeCountry category  age  fnlwgt  \\\n",
       "0   Not-in-family   White     Male   United-States    <=50K   39   77516   \n",
       "1         Husband   White     Male   United-States    <=50K   50   83311   \n",
       "2   Not-in-family   White     Male   United-States    <=50K   38  215646   \n",
       "3         Husband   Black     Male   United-States    <=50K   53  234721   \n",
       "4            Wife   Black   Female            Cuba    <=50K   28  338409   \n",
       "\n",
       "   educationNum  capGain  capLoss  HoursWeek  \n",
       "0            13     2174        0         40  \n",
       "1            13        0        0         13  \n",
       "2             9        0        0         40  \n",
       "3             7        0        0         40  \n",
       "4            13        0        0         40  "
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "data.loc[:,'workclass':'category'] = data.loc[:,'workclass':'category'].apply(LabelEncoder().fit_transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>marital</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>sex</th>\n",
       "      <th>NativeCountry</th>\n",
       "      <th>category</th>\n",
       "      <th>age</th>\n",
       "      <th>fnlwgt</th>\n",
       "      <th>educationNum</th>\n",
       "      <th>capGain</th>\n",
       "      <th>capLoss</th>\n",
       "      <th>HoursWeek</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>77516</td>\n",
       "      <td>13</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>83311</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>215646</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>234721</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>338409</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   workclass  education  marital  occupation  relationship  race  sex  \\\n",
       "0          7          9        4           1             1     4    1   \n",
       "1          6          9        2           4             0     4    1   \n",
       "2          4         11        0           6             1     4    1   \n",
       "3          4          1        2           6             0     2    1   \n",
       "4          4          9        2          10             5     2    0   \n",
       "\n",
       "   NativeCountry  category  age  fnlwgt  educationNum  capGain  capLoss  \\\n",
       "0             39         0   39   77516            13     2174        0   \n",
       "1             39         0   50   83311            13        0        0   \n",
       "2             39         0   38  215646             9        0        0   \n",
       "3             39         0   53  234721             7        0        0   \n",
       "4              5         0   28  338409            13        0        0   \n",
       "\n",
       "   HoursWeek  \n",
       "0         40  \n",
       "1         13  \n",
       "2         40  \n",
       "3         40  \n",
       "4         40  "
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 19. Finding correllation b/w features and target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(569, 31)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean radius</th>\n",
       "      <th>mean texture</th>\n",
       "      <th>mean perimeter</th>\n",
       "      <th>mean area</th>\n",
       "      <th>mean smoothness</th>\n",
       "      <th>mean compactness</th>\n",
       "      <th>mean concavity</th>\n",
       "      <th>mean concave points</th>\n",
       "      <th>mean symmetry</th>\n",
       "      <th>mean fractal dimension</th>\n",
       "      <th>radius error</th>\n",
       "      <th>texture error</th>\n",
       "      <th>perimeter error</th>\n",
       "      <th>area error</th>\n",
       "      <th>smoothness error</th>\n",
       "      <th>compactness error</th>\n",
       "      <th>concavity error</th>\n",
       "      <th>concave points error</th>\n",
       "      <th>symmetry error</th>\n",
       "      <th>fractal dimension error</th>\n",
       "      <th>worst radius</th>\n",
       "      <th>worst texture</th>\n",
       "      <th>worst perimeter</th>\n",
       "      <th>worst area</th>\n",
       "      <th>worst smoothness</th>\n",
       "      <th>worst compactness</th>\n",
       "      <th>worst concavity</th>\n",
       "      <th>worst concave points</th>\n",
       "      <th>worst symmetry</th>\n",
       "      <th>worst fractal dimension</th>\n",
       "      <th>outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>1.0950</td>\n",
       "      <td>0.9053</td>\n",
       "      <td>8.589</td>\n",
       "      <td>153.40</td>\n",
       "      <td>0.006399</td>\n",
       "      <td>0.04904</td>\n",
       "      <td>0.05373</td>\n",
       "      <td>0.01587</td>\n",
       "      <td>0.03003</td>\n",
       "      <td>0.006193</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.7339</td>\n",
       "      <td>3.398</td>\n",
       "      <td>74.08</td>\n",
       "      <td>0.005225</td>\n",
       "      <td>0.01308</td>\n",
       "      <td>0.01860</td>\n",
       "      <td>0.01340</td>\n",
       "      <td>0.01389</td>\n",
       "      <td>0.003532</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>0.7456</td>\n",
       "      <td>0.7869</td>\n",
       "      <td>4.585</td>\n",
       "      <td>94.03</td>\n",
       "      <td>0.006150</td>\n",
       "      <td>0.04006</td>\n",
       "      <td>0.03832</td>\n",
       "      <td>0.02058</td>\n",
       "      <td>0.02250</td>\n",
       "      <td>0.004571</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>0.4956</td>\n",
       "      <td>1.1560</td>\n",
       "      <td>3.445</td>\n",
       "      <td>27.23</td>\n",
       "      <td>0.009110</td>\n",
       "      <td>0.07458</td>\n",
       "      <td>0.05661</td>\n",
       "      <td>0.01867</td>\n",
       "      <td>0.05963</td>\n",
       "      <td>0.009208</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>0.7572</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>5.438</td>\n",
       "      <td>94.44</td>\n",
       "      <td>0.011490</td>\n",
       "      <td>0.02461</td>\n",
       "      <td>0.05688</td>\n",
       "      <td>0.01885</td>\n",
       "      <td>0.01756</td>\n",
       "      <td>0.005115</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       "0        17.99         10.38          122.80     1001.0          0.11840   \n",
       "1        20.57         17.77          132.90     1326.0          0.08474   \n",
       "2        19.69         21.25          130.00     1203.0          0.10960   \n",
       "3        11.42         20.38           77.58      386.1          0.14250   \n",
       "4        20.29         14.34          135.10     1297.0          0.10030   \n",
       "\n",
       "   mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       "0           0.27760          0.3001              0.14710         0.2419   \n",
       "1           0.07864          0.0869              0.07017         0.1812   \n",
       "2           0.15990          0.1974              0.12790         0.2069   \n",
       "3           0.28390          0.2414              0.10520         0.2597   \n",
       "4           0.13280          0.1980              0.10430         0.1809   \n",
       "\n",
       "   mean fractal dimension  radius error  texture error  perimeter error  \\\n",
       "0                 0.07871        1.0950         0.9053            8.589   \n",
       "1                 0.05667        0.5435         0.7339            3.398   \n",
       "2                 0.05999        0.7456         0.7869            4.585   \n",
       "3                 0.09744        0.4956         1.1560            3.445   \n",
       "4                 0.05883        0.7572         0.7813            5.438   \n",
       "\n",
       "   area error  smoothness error  compactness error  concavity error  \\\n",
       "0      153.40          0.006399            0.04904          0.05373   \n",
       "1       74.08          0.005225            0.01308          0.01860   \n",
       "2       94.03          0.006150            0.04006          0.03832   \n",
       "3       27.23          0.009110            0.07458          0.05661   \n",
       "4       94.44          0.011490            0.02461          0.05688   \n",
       "\n",
       "   concave points error  symmetry error  fractal dimension error  \\\n",
       "0               0.01587         0.03003                 0.006193   \n",
       "1               0.01340         0.01389                 0.003532   \n",
       "2               0.02058         0.02250                 0.004571   \n",
       "3               0.01867         0.05963                 0.009208   \n",
       "4               0.01885         0.01756                 0.005115   \n",
       "\n",
       "   worst radius  worst texture  worst perimeter  worst area  worst smoothness  \\\n",
       "0         25.38          17.33           184.60      2019.0            0.1622   \n",
       "1         24.99          23.41           158.80      1956.0            0.1238   \n",
       "2         23.57          25.53           152.50      1709.0            0.1444   \n",
       "3         14.91          26.50            98.87       567.7            0.2098   \n",
       "4         22.54          16.67           152.20      1575.0            0.1374   \n",
       "\n",
       "   worst compactness  worst concavity  worst concave points  worst symmetry  \\\n",
       "0             0.6656           0.7119                0.2654          0.4601   \n",
       "1             0.1866           0.2416                0.1860          0.2750   \n",
       "2             0.4245           0.4504                0.2430          0.3613   \n",
       "3             0.8663           0.6869                0.2575          0.6638   \n",
       "4             0.2050           0.4000                0.1625          0.2364   \n",
       "\n",
       "   worst fractal dimension  outcome  \n",
       "0                  0.11890        1  \n",
       "1                  0.08902        1  \n",
       "2                  0.08758        1  \n",
       "3                  0.17300        1  \n",
       "4                  0.07678        1  "
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(breast_cancer)\n",
    "print(data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_corr = data.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "outcome                    1.000000\n",
       "worst concave points       0.793566\n",
       "worst perimeter            0.782914\n",
       "mean concave points        0.776614\n",
       "worst radius               0.776454\n",
       "mean perimeter             0.742636\n",
       "worst area                 0.733825\n",
       "mean radius                0.730029\n",
       "mean area                  0.708984\n",
       "mean concavity             0.696360\n",
       "worst concavity            0.659610\n",
       "mean compactness           0.596534\n",
       "worst compactness          0.590998\n",
       "radius error               0.567134\n",
       "perimeter error            0.556141\n",
       "area error                 0.548236\n",
       "worst texture              0.456903\n",
       "worst smoothness           0.421465\n",
       "worst symmetry             0.416294\n",
       "mean texture               0.415185\n",
       "concave points error       0.408042\n",
       "mean smoothness            0.358560\n",
       "mean symmetry              0.330499\n",
       "worst fractal dimension    0.323872\n",
       "compactness error          0.292999\n",
       "concavity error            0.253730\n",
       "fractal dimension error    0.077972\n",
       "symmetry error            -0.006522\n",
       "texture error             -0.008303\n",
       "mean fractal dimension    -0.012838\n",
       "smoothness error          -0.067016\n",
       "Name: outcome, dtype: float64"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_corr.outcome.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 20. Replace special chars in column names with '_'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean radius</th>\n",
       "      <th>mean texture</th>\n",
       "      <th>mean perimeter</th>\n",
       "      <th>mean area</th>\n",
       "      <th>mean smoothness</th>\n",
       "      <th>mean compactness</th>\n",
       "      <th>mean concavity</th>\n",
       "      <th>mean concave points</th>\n",
       "      <th>mean symmetry</th>\n",
       "      <th>mean fractal dimension</th>\n",
       "      <th>radius error</th>\n",
       "      <th>texture error</th>\n",
       "      <th>perimeter error</th>\n",
       "      <th>area error</th>\n",
       "      <th>smoothness error</th>\n",
       "      <th>compactness error</th>\n",
       "      <th>concavity error</th>\n",
       "      <th>concave points error</th>\n",
       "      <th>symmetry error</th>\n",
       "      <th>fractal dimension error</th>\n",
       "      <th>worst radius</th>\n",
       "      <th>worst texture</th>\n",
       "      <th>worst perimeter</th>\n",
       "      <th>worst area</th>\n",
       "      <th>worst smoothness</th>\n",
       "      <th>worst compactness</th>\n",
       "      <th>worst concavity</th>\n",
       "      <th>worst concave points</th>\n",
       "      <th>worst symmetry</th>\n",
       "      <th>worst fractal dimension</th>\n",
       "      <th>outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>1.0950</td>\n",
       "      <td>0.9053</td>\n",
       "      <td>8.589</td>\n",
       "      <td>153.40</td>\n",
       "      <td>0.006399</td>\n",
       "      <td>0.04904</td>\n",
       "      <td>0.05373</td>\n",
       "      <td>0.01587</td>\n",
       "      <td>0.03003</td>\n",
       "      <td>0.006193</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.7339</td>\n",
       "      <td>3.398</td>\n",
       "      <td>74.08</td>\n",
       "      <td>0.005225</td>\n",
       "      <td>0.01308</td>\n",
       "      <td>0.01860</td>\n",
       "      <td>0.01340</td>\n",
       "      <td>0.01389</td>\n",
       "      <td>0.003532</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>0.7456</td>\n",
       "      <td>0.7869</td>\n",
       "      <td>4.585</td>\n",
       "      <td>94.03</td>\n",
       "      <td>0.006150</td>\n",
       "      <td>0.04006</td>\n",
       "      <td>0.03832</td>\n",
       "      <td>0.02058</td>\n",
       "      <td>0.02250</td>\n",
       "      <td>0.004571</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>0.4956</td>\n",
       "      <td>1.1560</td>\n",
       "      <td>3.445</td>\n",
       "      <td>27.23</td>\n",
       "      <td>0.009110</td>\n",
       "      <td>0.07458</td>\n",
       "      <td>0.05661</td>\n",
       "      <td>0.01867</td>\n",
       "      <td>0.05963</td>\n",
       "      <td>0.009208</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>0.7572</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>5.438</td>\n",
       "      <td>94.44</td>\n",
       "      <td>0.011490</td>\n",
       "      <td>0.02461</td>\n",
       "      <td>0.05688</td>\n",
       "      <td>0.01885</td>\n",
       "      <td>0.01756</td>\n",
       "      <td>0.005115</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       "0        17.99         10.38          122.80     1001.0          0.11840   \n",
       "1        20.57         17.77          132.90     1326.0          0.08474   \n",
       "2        19.69         21.25          130.00     1203.0          0.10960   \n",
       "3        11.42         20.38           77.58      386.1          0.14250   \n",
       "4        20.29         14.34          135.10     1297.0          0.10030   \n",
       "\n",
       "   mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       "0           0.27760          0.3001              0.14710         0.2419   \n",
       "1           0.07864          0.0869              0.07017         0.1812   \n",
       "2           0.15990          0.1974              0.12790         0.2069   \n",
       "3           0.28390          0.2414              0.10520         0.2597   \n",
       "4           0.13280          0.1980              0.10430         0.1809   \n",
       "\n",
       "   mean fractal dimension  radius error  texture error  perimeter error  \\\n",
       "0                 0.07871        1.0950         0.9053            8.589   \n",
       "1                 0.05667        0.5435         0.7339            3.398   \n",
       "2                 0.05999        0.7456         0.7869            4.585   \n",
       "3                 0.09744        0.4956         1.1560            3.445   \n",
       "4                 0.05883        0.7572         0.7813            5.438   \n",
       "\n",
       "   area error  smoothness error  compactness error  concavity error  \\\n",
       "0      153.40          0.006399            0.04904          0.05373   \n",
       "1       74.08          0.005225            0.01308          0.01860   \n",
       "2       94.03          0.006150            0.04006          0.03832   \n",
       "3       27.23          0.009110            0.07458          0.05661   \n",
       "4       94.44          0.011490            0.02461          0.05688   \n",
       "\n",
       "   concave points error  symmetry error  fractal dimension error  \\\n",
       "0               0.01587         0.03003                 0.006193   \n",
       "1               0.01340         0.01389                 0.003532   \n",
       "2               0.02058         0.02250                 0.004571   \n",
       "3               0.01867         0.05963                 0.009208   \n",
       "4               0.01885         0.01756                 0.005115   \n",
       "\n",
       "   worst radius  worst texture  worst perimeter  worst area  worst smoothness  \\\n",
       "0         25.38          17.33           184.60      2019.0            0.1622   \n",
       "1         24.99          23.41           158.80      1956.0            0.1238   \n",
       "2         23.57          25.53           152.50      1709.0            0.1444   \n",
       "3         14.91          26.50            98.87       567.7            0.2098   \n",
       "4         22.54          16.67           152.20      1575.0            0.1374   \n",
       "\n",
       "   worst compactness  worst concavity  worst concave points  worst symmetry  \\\n",
       "0             0.6656           0.7119                0.2654          0.4601   \n",
       "1             0.1866           0.2416                0.1860          0.2750   \n",
       "2             0.4245           0.4504                0.2430          0.3613   \n",
       "3             0.8663           0.6869                0.2575          0.6638   \n",
       "4             0.2050           0.4000                0.1625          0.2364   \n",
       "\n",
       "   worst fractal dimension  outcome  \n",
       "0                  0.11890        1  \n",
       "1                  0.08902        1  \n",
       "2                  0.08758        1  \n",
       "3                  0.17300        1  \n",
       "4                  0.07678        1  "
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.rename(columns = {'mean radius':'mean $radius'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean $radius</th>\n",
       "      <th>mean texture</th>\n",
       "      <th>mean perimeter</th>\n",
       "      <th>mean area</th>\n",
       "      <th>mean smoothness</th>\n",
       "      <th>mean compactness</th>\n",
       "      <th>mean concavity</th>\n",
       "      <th>mean concave points</th>\n",
       "      <th>mean symmetry</th>\n",
       "      <th>mean fractal dimension</th>\n",
       "      <th>radius error</th>\n",
       "      <th>texture error</th>\n",
       "      <th>perimeter error</th>\n",
       "      <th>area error</th>\n",
       "      <th>smoothness error</th>\n",
       "      <th>compactness error</th>\n",
       "      <th>concavity error</th>\n",
       "      <th>concave points error</th>\n",
       "      <th>symmetry error</th>\n",
       "      <th>fractal dimension error</th>\n",
       "      <th>worst radius</th>\n",
       "      <th>worst texture</th>\n",
       "      <th>worst perimeter</th>\n",
       "      <th>worst area</th>\n",
       "      <th>worst smoothness</th>\n",
       "      <th>worst compactness</th>\n",
       "      <th>worst concavity</th>\n",
       "      <th>worst concave points</th>\n",
       "      <th>worst symmetry</th>\n",
       "      <th>worst fractal dimension</th>\n",
       "      <th>outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>1.0950</td>\n",
       "      <td>0.9053</td>\n",
       "      <td>8.589</td>\n",
       "      <td>153.40</td>\n",
       "      <td>0.006399</td>\n",
       "      <td>0.04904</td>\n",
       "      <td>0.05373</td>\n",
       "      <td>0.01587</td>\n",
       "      <td>0.03003</td>\n",
       "      <td>0.006193</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.7339</td>\n",
       "      <td>3.398</td>\n",
       "      <td>74.08</td>\n",
       "      <td>0.005225</td>\n",
       "      <td>0.01308</td>\n",
       "      <td>0.01860</td>\n",
       "      <td>0.01340</td>\n",
       "      <td>0.01389</td>\n",
       "      <td>0.003532</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>0.7456</td>\n",
       "      <td>0.7869</td>\n",
       "      <td>4.585</td>\n",
       "      <td>94.03</td>\n",
       "      <td>0.006150</td>\n",
       "      <td>0.04006</td>\n",
       "      <td>0.03832</td>\n",
       "      <td>0.02058</td>\n",
       "      <td>0.02250</td>\n",
       "      <td>0.004571</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>0.4956</td>\n",
       "      <td>1.1560</td>\n",
       "      <td>3.445</td>\n",
       "      <td>27.23</td>\n",
       "      <td>0.009110</td>\n",
       "      <td>0.07458</td>\n",
       "      <td>0.05661</td>\n",
       "      <td>0.01867</td>\n",
       "      <td>0.05963</td>\n",
       "      <td>0.009208</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>0.7572</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>5.438</td>\n",
       "      <td>94.44</td>\n",
       "      <td>0.011490</td>\n",
       "      <td>0.02461</td>\n",
       "      <td>0.05688</td>\n",
       "      <td>0.01885</td>\n",
       "      <td>0.01756</td>\n",
       "      <td>0.005115</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean $radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       "0         17.99         10.38          122.80     1001.0          0.11840   \n",
       "1         20.57         17.77          132.90     1326.0          0.08474   \n",
       "2         19.69         21.25          130.00     1203.0          0.10960   \n",
       "3         11.42         20.38           77.58      386.1          0.14250   \n",
       "4         20.29         14.34          135.10     1297.0          0.10030   \n",
       "\n",
       "   mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       "0           0.27760          0.3001              0.14710         0.2419   \n",
       "1           0.07864          0.0869              0.07017         0.1812   \n",
       "2           0.15990          0.1974              0.12790         0.2069   \n",
       "3           0.28390          0.2414              0.10520         0.2597   \n",
       "4           0.13280          0.1980              0.10430         0.1809   \n",
       "\n",
       "   mean fractal dimension  radius error  texture error  perimeter error  \\\n",
       "0                 0.07871        1.0950         0.9053            8.589   \n",
       "1                 0.05667        0.5435         0.7339            3.398   \n",
       "2                 0.05999        0.7456         0.7869            4.585   \n",
       "3                 0.09744        0.4956         1.1560            3.445   \n",
       "4                 0.05883        0.7572         0.7813            5.438   \n",
       "\n",
       "   area error  smoothness error  compactness error  concavity error  \\\n",
       "0      153.40          0.006399            0.04904          0.05373   \n",
       "1       74.08          0.005225            0.01308          0.01860   \n",
       "2       94.03          0.006150            0.04006          0.03832   \n",
       "3       27.23          0.009110            0.07458          0.05661   \n",
       "4       94.44          0.011490            0.02461          0.05688   \n",
       "\n",
       "   concave points error  symmetry error  fractal dimension error  \\\n",
       "0               0.01587         0.03003                 0.006193   \n",
       "1               0.01340         0.01389                 0.003532   \n",
       "2               0.02058         0.02250                 0.004571   \n",
       "3               0.01867         0.05963                 0.009208   \n",
       "4               0.01885         0.01756                 0.005115   \n",
       "\n",
       "   worst radius  worst texture  worst perimeter  worst area  worst smoothness  \\\n",
       "0         25.38          17.33           184.60      2019.0            0.1622   \n",
       "1         24.99          23.41           158.80      1956.0            0.1238   \n",
       "2         23.57          25.53           152.50      1709.0            0.1444   \n",
       "3         14.91          26.50            98.87       567.7            0.2098   \n",
       "4         22.54          16.67           152.20      1575.0            0.1374   \n",
       "\n",
       "   worst compactness  worst concavity  worst concave points  worst symmetry  \\\n",
       "0             0.6656           0.7119                0.2654          0.4601   \n",
       "1             0.1866           0.2416                0.1860          0.2750   \n",
       "2             0.4245           0.4504                0.2430          0.3613   \n",
       "3             0.8663           0.6869                0.2575          0.6638   \n",
       "4             0.2050           0.4000                0.1625          0.2364   \n",
       "\n",
       "   worst fractal dimension  outcome  \n",
       "0                  0.11890        1  \n",
       "1                  0.08902        1  \n",
       "2                  0.08758        1  \n",
       "3                  0.17300        1  \n",
       "4                  0.07678        1  "
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.columns = data.columns.str.replace('\\W+',\"_\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_radius</th>\n",
       "      <th>mean_texture</th>\n",
       "      <th>mean_perimeter</th>\n",
       "      <th>mean_area</th>\n",
       "      <th>mean_smoothness</th>\n",
       "      <th>mean_compactness</th>\n",
       "      <th>mean_concavity</th>\n",
       "      <th>mean_concave_points</th>\n",
       "      <th>mean_symmetry</th>\n",
       "      <th>mean_fractal_dimension</th>\n",
       "      <th>radius_error</th>\n",
       "      <th>texture_error</th>\n",
       "      <th>perimeter_error</th>\n",
       "      <th>area_error</th>\n",
       "      <th>smoothness_error</th>\n",
       "      <th>compactness_error</th>\n",
       "      <th>concavity_error</th>\n",
       "      <th>concave_points_error</th>\n",
       "      <th>symmetry_error</th>\n",
       "      <th>fractal_dimension_error</th>\n",
       "      <th>worst_radius</th>\n",
       "      <th>worst_texture</th>\n",
       "      <th>worst_perimeter</th>\n",
       "      <th>worst_area</th>\n",
       "      <th>worst_smoothness</th>\n",
       "      <th>worst_compactness</th>\n",
       "      <th>worst_concavity</th>\n",
       "      <th>worst_concave_points</th>\n",
       "      <th>worst_symmetry</th>\n",
       "      <th>worst_fractal_dimension</th>\n",
       "      <th>outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>1.0950</td>\n",
       "      <td>0.9053</td>\n",
       "      <td>8.589</td>\n",
       "      <td>153.40</td>\n",
       "      <td>0.006399</td>\n",
       "      <td>0.04904</td>\n",
       "      <td>0.05373</td>\n",
       "      <td>0.01587</td>\n",
       "      <td>0.03003</td>\n",
       "      <td>0.006193</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.7339</td>\n",
       "      <td>3.398</td>\n",
       "      <td>74.08</td>\n",
       "      <td>0.005225</td>\n",
       "      <td>0.01308</td>\n",
       "      <td>0.01860</td>\n",
       "      <td>0.01340</td>\n",
       "      <td>0.01389</td>\n",
       "      <td>0.003532</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>0.7456</td>\n",
       "      <td>0.7869</td>\n",
       "      <td>4.585</td>\n",
       "      <td>94.03</td>\n",
       "      <td>0.006150</td>\n",
       "      <td>0.04006</td>\n",
       "      <td>0.03832</td>\n",
       "      <td>0.02058</td>\n",
       "      <td>0.02250</td>\n",
       "      <td>0.004571</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>0.4956</td>\n",
       "      <td>1.1560</td>\n",
       "      <td>3.445</td>\n",
       "      <td>27.23</td>\n",
       "      <td>0.009110</td>\n",
       "      <td>0.07458</td>\n",
       "      <td>0.05661</td>\n",
       "      <td>0.01867</td>\n",
       "      <td>0.05963</td>\n",
       "      <td>0.009208</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>0.7572</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>5.438</td>\n",
       "      <td>94.44</td>\n",
       "      <td>0.011490</td>\n",
       "      <td>0.02461</td>\n",
       "      <td>0.05688</td>\n",
       "      <td>0.01885</td>\n",
       "      <td>0.01756</td>\n",
       "      <td>0.005115</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_radius  mean_texture  mean_perimeter  mean_area  mean_smoothness  \\\n",
       "0        17.99         10.38          122.80     1001.0          0.11840   \n",
       "1        20.57         17.77          132.90     1326.0          0.08474   \n",
       "2        19.69         21.25          130.00     1203.0          0.10960   \n",
       "3        11.42         20.38           77.58      386.1          0.14250   \n",
       "4        20.29         14.34          135.10     1297.0          0.10030   \n",
       "\n",
       "   mean_compactness  mean_concavity  mean_concave_points  mean_symmetry  \\\n",
       "0           0.27760          0.3001              0.14710         0.2419   \n",
       "1           0.07864          0.0869              0.07017         0.1812   \n",
       "2           0.15990          0.1974              0.12790         0.2069   \n",
       "3           0.28390          0.2414              0.10520         0.2597   \n",
       "4           0.13280          0.1980              0.10430         0.1809   \n",
       "\n",
       "   mean_fractal_dimension  radius_error  texture_error  perimeter_error  \\\n",
       "0                 0.07871        1.0950         0.9053            8.589   \n",
       "1                 0.05667        0.5435         0.7339            3.398   \n",
       "2                 0.05999        0.7456         0.7869            4.585   \n",
       "3                 0.09744        0.4956         1.1560            3.445   \n",
       "4                 0.05883        0.7572         0.7813            5.438   \n",
       "\n",
       "   area_error  smoothness_error  compactness_error  concavity_error  \\\n",
       "0      153.40          0.006399            0.04904          0.05373   \n",
       "1       74.08          0.005225            0.01308          0.01860   \n",
       "2       94.03          0.006150            0.04006          0.03832   \n",
       "3       27.23          0.009110            0.07458          0.05661   \n",
       "4       94.44          0.011490            0.02461          0.05688   \n",
       "\n",
       "   concave_points_error  symmetry_error  fractal_dimension_error  \\\n",
       "0               0.01587         0.03003                 0.006193   \n",
       "1               0.01340         0.01389                 0.003532   \n",
       "2               0.02058         0.02250                 0.004571   \n",
       "3               0.01867         0.05963                 0.009208   \n",
       "4               0.01885         0.01756                 0.005115   \n",
       "\n",
       "   worst_radius  worst_texture  worst_perimeter  worst_area  worst_smoothness  \\\n",
       "0         25.38          17.33           184.60      2019.0            0.1622   \n",
       "1         24.99          23.41           158.80      1956.0            0.1238   \n",
       "2         23.57          25.53           152.50      1709.0            0.1444   \n",
       "3         14.91          26.50            98.87       567.7            0.2098   \n",
       "4         22.54          16.67           152.20      1575.0            0.1374   \n",
       "\n",
       "   worst_compactness  worst_concavity  worst_concave_points  worst_symmetry  \\\n",
       "0             0.6656           0.7119                0.2654          0.4601   \n",
       "1             0.1866           0.2416                0.1860          0.2750   \n",
       "2             0.4245           0.4504                0.2430          0.3613   \n",
       "3             0.8663           0.6869                0.2575          0.6638   \n",
       "4             0.2050           0.4000                0.1625          0.2364   \n",
       "\n",
       "   worst_fractal_dimension  outcome  \n",
       "0                  0.11890        1  \n",
       "1                  0.08902        1  \n",
       "2                  0.08758        1  \n",
       "3                  0.17300        1  \n",
       "4                  0.07678        1  "
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      1.0950\n",
       "1      0.5435\n",
       "2      0.7456\n",
       "3      0.4956\n",
       "4      0.7572\n",
       "5      0.3345\n",
       "6      0.4467\n",
       "7      0.5835\n",
       "8      0.3063\n",
       "9      0.2976\n",
       "10     0.3795\n",
       "11     0.5058\n",
       "12     0.9555\n",
       "13     0.4033\n",
       "14     0.2121\n",
       "15     0.3700\n",
       "16     0.4727\n",
       "17     0.5692\n",
       "18     0.7582\n",
       "19     0.2699\n",
       "20     0.1852\n",
       "21     0.2773\n",
       "22     0.4388\n",
       "23     0.6917\n",
       "24     0.8068\n",
       "25     1.0460\n",
       "26     0.2545\n",
       "27     0.8529\n",
       "28     0.4390\n",
       "29     0.6003\n",
       "        ...  \n",
       "539    0.2196\n",
       "540    0.2784\n",
       "541    0.2542\n",
       "542    0.3031\n",
       "543    0.2351\n",
       "544    0.2720\n",
       "545    0.3460\n",
       "546    0.2104\n",
       "547    0.1144\n",
       "548    0.2957\n",
       "549    0.5196\n",
       "550    0.3163\n",
       "551    0.2800\n",
       "552    0.2409\n",
       "553    0.3013\n",
       "554    0.2116\n",
       "555    0.2199\n",
       "556    0.2441\n",
       "557    0.5375\n",
       "558    0.2254\n",
       "559    0.2388\n",
       "560    0.3645\n",
       "561    0.3141\n",
       "562    0.2602\n",
       "563    0.9622\n",
       "564    1.1760\n",
       "565    0.7655\n",
       "566    0.4564\n",
       "567    0.7260\n",
       "568    0.3857\n",
       "Name: radius_error, Length: 569, dtype: float64"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.radius_error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PART - 3 (21 to 30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 21.\tSelect data with Regular Expression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 22.\tPandas profiling - Complete EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 23.\tFilter DataFrame by specific row values, using isin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 24.\tUsing Tilda ~ Operator  in Pandas data filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 25.\tPandas read skipinitialspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 26.\tScalar filtering with ix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 27. Move column(s) to the begining/ending in DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 28.\tPandas reading broad charsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 29.\tCreate Random DataFrame "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 30.\tRandom sample from large data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PART - 4 (31 to 40)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 31.\tPandas Cumulative sum cumsum() method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 32.\tBest way to loop through DataFrame , df.iterrows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 33.\tPandas rank method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 34.\tPandas map and applymap methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 35.\tPandas read from Clipboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 36.\tSelect columns by data type select_dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 37.\treverse row/column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 38.\tConvert data type of columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 39.\tCreate csv Zip file from DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 40.\tLoad large dataset in Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33\n"
     ]
    }
   ],
   "source": [
    "def myfunc(n):\n",
    "    return lambda a : a * n + a\n",
    "mydoubler = myfunc(2)\n",
    "print(mydoubler(11))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# References & Credits\n",
    "- Pandas Documentation: https://pandas.pydata.org/docs/\n",
    "- BOOK : https://www.oreilly.com/library/view/python-for-data/9781449323592/\n",
    "\n",
    "- https://stackoverflow.com/users/2411802/alexander\n",
    "- https://stackoverflow.com/users/9840637/anky\n",
    "- https://stackoverflow.com/users/1426056/waitingkuo\n",
    "- https://stackoverflow.com/users/487339/dsm\n",
    "- https://stackoverflow.com/users/1983512/gaurav-singh\n",
    "- https://stackoverflow.com/users/475872/nick-crawford\n",
    "- https://stackoverflow.com/users/3232824/kieranpc\n",
    "- https://stackoverflow.com/users/7758804/trenton-mckinney\n",
    "- https://stackoverflow.com/users/7932273/sociopath\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pandas-profilingNote: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Error processing line 1 of C:\\Users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\zope.interface-5.4.0-py3.8-nspkg.pth:"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "  Downloading pandas_profiling-3.2.0-py2.py3-none-any.whl (262 kB)\n",
      "Collecting tangled-up-in-unicode==0.2.0\n",
      "  Downloading tangled_up_in_unicode-0.2.0-py3-none-any.whl (4.7 MB)\n",
      "Requirement already satisfied: scipy>=1.4.1 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas-profiling) (1.6.2)\n",
      "Collecting markupsafe~=2.1.1\n",
      "  Downloading MarkupSafe-2.1.1-cp38-cp38-win_amd64.whl (17 kB)\n",
      "Collecting missingno>=0.4.2\n",
      "  Downloading missingno-0.5.1-py3-none-any.whl (8.7 kB)"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "  Traceback (most recent call last):\n",
      "    File \"C:\\Users\\user\\anaconda3\\envs\\tensorflow\\lib\\site.py\", line 169, in addpackage\n",
      "      exec(line)\n",
      "    File \"<string>\", line 1, in <module>\n",
      "    File \"<frozen importlib._bootstrap>\", line 553, in module_from_spec\n",
      "  AttributeError: 'NoneType' object has no attribute 'loader'\n",
      "\n",
      "Remainder of file ignored\n",
      "ERROR: Could not install packages due to an OSError: [WinError 5] Access is denied: 'C:\\\\Users\\\\user\\\\anaconda3\\\\envs\\\\tensorflow\\\\Lib\\\\site-packages\\\\~arkupsafe\\\\_speedups.cp38-win_amd64.pyd'\n",
      "Consider using the `--user` option or check the permissions.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Requirement already satisfied: PyYAML>=5.0.0 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas-profiling) (5.4.1)\n",
      "Requirement already satisfied: joblib~=1.1.0 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas-profiling) (1.1.0)\n",
      "Collecting visions[type_image_path]==0.7.4\n",
      "  Downloading visions-0.7.4-py3-none-any.whl (102 kB)\n",
      "Requirement already satisfied: requests>=2.24.0 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas-profiling) (2.25.1)\n",
      "Requirement already satisfied: pandas!=1.0.0,!=1.0.1,!=1.0.2,!=1.1.0,>=0.25.3 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas-profiling) (1.3.5)\n",
      "Requirement already satisfied: seaborn>=0.10.1 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas-profiling) (0.11.2)\n",
      "Collecting tqdm>=4.48.2\n",
      "  Downloading tqdm-4.64.0-py2.py3-none-any.whl (78 kB)\n",
      "Requirement already satisfied: jinja2>=2.11.1 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas-profiling) (2.11.3)\n",
      "Collecting multimethod>=1.4\n",
      "  Downloading multimethod-1.8-py3-none-any.whl (9.8 kB)\n",
      "Requirement already satisfied: numpy>=1.16.0 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas-profiling) (1.19.2)\n",
      "Collecting htmlmin>=0.1.12\n",
      "  Downloading htmlmin-0.1.12.tar.gz (19 kB)\n",
      "Collecting phik>=0.11.1\n",
      "  Downloading phik-0.12.2-cp38-cp38-win_amd64.whl (677 kB)\n",
      "Collecting pydantic>=1.8.1\n",
      "  Downloading pydantic-1.9.0-cp38-cp38-win_amd64.whl (2.1 MB)\n",
      "Requirement already satisfied: matplotlib>=3.2.0 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas-profiling) (3.5.0)\n",
      "Requirement already satisfied: attrs>=19.3.0 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from visions[type_image_path]==0.7.4->pandas-profiling) (20.3.0)\n",
      "Collecting networkx>=2.4\n",
      "  Downloading networkx-2.8-py3-none-any.whl (2.0 MB)\n",
      "Collecting imagehash\n",
      "  Downloading ImageHash-4.2.1.tar.gz (812 kB)\n",
      "Requirement already satisfied: Pillow in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from visions[type_image_path]==0.7.4->pandas-profiling) (8.4.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from matplotlib>=3.2.0->pandas-profiling) (2.8.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from matplotlib>=3.2.0->pandas-profiling) (4.25.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from matplotlib>=3.2.0->pandas-profiling) (1.3.1)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from matplotlib>=3.2.0->pandas-profiling) (2.4.7)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from matplotlib>=3.2.0->pandas-profiling) (20.9)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from matplotlib>=3.2.0->pandas-profiling) (0.11.0)\n",
      "Requirement already satisfied: pytz>=2017.3 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pandas!=1.0.0,!=1.0.1,!=1.0.2,!=1.1.0,>=0.25.3->pandas-profiling) (2021.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from pydantic>=1.8.1->pandas-profiling) (3.7.4.3)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from python-dateutil>=2.7->matplotlib>=3.2.0->pandas-profiling) (1.15.0)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from requests>=2.24.0->pandas-profiling) (1.26.4)\n",
      "Requirement already satisfied: chardet<5,>=3.0.2 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from requests>=2.24.0->pandas-profiling) (4.0.0)\n",
      "Requirement already satisfied: idna<3,>=2.5 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from requests>=2.24.0->pandas-profiling) (2.10)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from requests>=2.24.0->pandas-profiling) (2021.10.8)\n",
      "Requirement already satisfied: colorama in c:\\users\\user\\anaconda3\\envs\\tensorflow\\lib\\site-packages (from tqdm>=4.48.2->pandas-profiling) (0.4.4)\n",
      "Collecting PyWavelets\n",
      "  Downloading PyWavelets-1.3.0-cp38-cp38-win_amd64.whl (4.2 MB)\n",
      "Building wheels for collected packages: htmlmin, imagehash\n",
      "  Building wheel for htmlmin (setup.py): started\n",
      "  Building wheel for htmlmin (setup.py): finished with status 'done'\n",
      "  Created wheel for htmlmin: filename=htmlmin-0.1.12-py3-none-any.whl size=27085 sha256=a3504d00526039cece20fc72b168c3173856c55cfd604db5e8d443c1b9c720df\n",
      "  Stored in directory: c:\\users\\user\\appdata\\local\\pip\\cache\\wheels\\23\\14\\6e\\4be5bfeeb027f4939a01764b48edd5996acf574b0913fe5243\n",
      "  Building wheel for imagehash (setup.py): started\n",
      "  Building wheel for imagehash (setup.py): finished with status 'done'\n",
      "  Created wheel for imagehash: filename=ImageHash-4.2.1-py2.py3-none-any.whl size=295198 sha256=5dd37d08c949c78d449dbc192b75e419c5f5d73dcd00950d6e9d603267eaf52b\n",
      "  Stored in directory: c:\\users\\user\\appdata\\local\\pip\\cache\\wheels\\48\\a1\\7f\\096c1269d6bf78d4768180602579b35a1e8cb1250bb4b40c74\n",
      "Successfully built htmlmin imagehash\n",
      "Installing collected packages: tangled-up-in-unicode, PyWavelets, networkx, multimethod, visions, markupsafe, imagehash, tqdm, pydantic, phik, missingno, htmlmin, pandas-profiling\n",
      "  Attempting uninstall: markupsafe\n",
      "    Found existing installation: MarkupSafe 1.1.1\n",
      "    Uninstalling MarkupSafe-1.1.1:\n",
      "      Successfully uninstalled MarkupSafe-1.1.1\n"
     ]
    }
   ],
   "source": [
    "pip install pandas-profiling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'pandas_profiling'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-1-d821845d4c92>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mpandas_profiling\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mprofileReport\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'pandas_profiling'"
     ]
    }
   ],
   "source": [
    "from pandas_profiling import profileReport"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}