main.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#data sources\n",
    "covid_data = \"Resources/CovidNumbers.csv\"\n",
    "covid_daily_count = \"Resources/COVID-19_Daily_Counts_of_Cases__Hospitalizations__and_Deaths.csv\"\n",
    "March_2019_turnstile = \"Resources/Turnstile_190330.csv\"\n",
    "March_2020_turnstile = \"Resources/Turnstile_200328.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>\\outl0\\strokewidth0 \\strokec2 MODIFIED_ZCTA</th>\n",
       "      <th>NEIGHBORHOOD_NAME</th>\n",
       "      <th>BOROUGH_GROUP</th>\n",
       "      <th>COVID_CASE_COUNT</th>\n",
       "      <th>COVID_CASE_RATE</th>\n",
       "      <th>POP_DENOMINATOR</th>\n",
       "      <th>COVID_DEATH_COUNT</th>\n",
       "      <th>COVID_DEATH_RATE</th>\n",
       "      <th>PERCENT_POSITIVE</th>\n",
       "      <th>TOTAL_COVID_TESTS\\</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10001</td>\n",
       "      <td>Chelsea/NoMad/West Chelsea</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>459.0</td>\n",
       "      <td>1947.97</td>\n",
       "      <td>23563.03</td>\n",
       "      <td>27.0</td>\n",
       "      <td>114.59</td>\n",
       "      <td>5.53</td>\n",
       "      <td>8299\\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10002</td>\n",
       "      <td>Chinatown/Lower East Side</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>1371.0</td>\n",
       "      <td>1786.19</td>\n",
       "      <td>76755.41</td>\n",
       "      <td>161.0</td>\n",
       "      <td>209.76</td>\n",
       "      <td>6.61</td>\n",
       "      <td>20729\\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10003</td>\n",
       "      <td>East Village/Gramercy/Greenwich Village</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>584.0</td>\n",
       "      <td>1085.47</td>\n",
       "      <td>53801.62</td>\n",
       "      <td>35.0</td>\n",
       "      <td>65.05</td>\n",
       "      <td>3.07</td>\n",
       "      <td>19041\\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10004</td>\n",
       "      <td>Financial District</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1232.67</td>\n",
       "      <td>3650.61</td>\n",
       "      <td>1.0</td>\n",
       "      <td>27.39</td>\n",
       "      <td>4.43</td>\n",
       "      <td>1015\\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10005</td>\n",
       "      <td>Financial District</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>109.0</td>\n",
       "      <td>1298.22</td>\n",
       "      <td>8396.11</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23.82</td>\n",
       "      <td>4.24</td>\n",
       "      <td>2569\\</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  \\outl0\\strokewidth0 \\strokec2 MODIFIED_ZCTA  \\\n",
       "0                                       10001   \n",
       "1                                       10002   \n",
       "2                                       10003   \n",
       "3                                       10004   \n",
       "4                                       10005   \n",
       "\n",
       "                         NEIGHBORHOOD_NAME BOROUGH_GROUP  COVID_CASE_COUNT  \\\n",
       "0               Chelsea/NoMad/West Chelsea     Manhattan             459.0   \n",
       "1                Chinatown/Lower East Side     Manhattan            1371.0   \n",
       "2  East Village/Gramercy/Greenwich Village     Manhattan             584.0   \n",
       "3                       Financial District     Manhattan              45.0   \n",
       "4                       Financial District     Manhattan             109.0   \n",
       "\n",
       "   COVID_CASE_RATE  POP_DENOMINATOR  COVID_DEATH_COUNT  COVID_DEATH_RATE  \\\n",
       "0          1947.97         23563.03               27.0            114.59   \n",
       "1          1786.19         76755.41              161.0            209.76   \n",
       "2          1085.47         53801.62               35.0             65.05   \n",
       "3          1232.67          3650.61                1.0             27.39   \n",
       "4          1298.22          8396.11                2.0             23.82   \n",
       "\n",
       "   PERCENT_POSITIVE TOTAL_COVID_TESTS\\  \n",
       "0              5.53              8299\\  \n",
       "1              6.61             20729\\  \n",
       "2              3.07             19041\\  \n",
       "3              4.43              1015\\  \n",
       "4              4.24              2569\\  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#read the covid case rate csv file\n",
    "#data-by-modzcta.csv\n",
    "#This file contains data by modified ZIP code tabulation areas (ZCTA). \n",
    "#This unit of geography is similar to ZIP codes but combines census blocks with smaller populations to allow more stable estimates of population size for rate calculation. \n",
    "#Please see description of modified ZCTAs in the technical notes section (Geography: Zip codes and ZCTAs).\n",
    "#data as of 9/25/20\n",
    "\n",
    "covid_pd = pd.read_csv(covid_data, header = 8)\n",
    "\n",
    "covid_pd.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Modified_ZCTA</th>\n",
       "      <th>NEIGHBORHOOD_NAME</th>\n",
       "      <th>BOROUGH_GROUP</th>\n",
       "      <th>COVID_CASE_COUNT</th>\n",
       "      <th>COVID_CASE_RATE</th>\n",
       "      <th>POP_DENOMINATOR</th>\n",
       "      <th>COVID_DEATH_COUNT</th>\n",
       "      <th>COVID_DEATH_RATE</th>\n",
       "      <th>PERCENT_POSITIVE</th>\n",
       "      <th>TOTAL_COVID_TESTS\\</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10001</td>\n",
       "      <td>Chelsea/NoMad/West Chelsea</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>459.0</td>\n",
       "      <td>1947.97</td>\n",
       "      <td>23563.03</td>\n",
       "      <td>27.0</td>\n",
       "      <td>114.59</td>\n",
       "      <td>5.53</td>\n",
       "      <td>8299\\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10002</td>\n",
       "      <td>Chinatown/Lower East Side</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>1371.0</td>\n",
       "      <td>1786.19</td>\n",
       "      <td>76755.41</td>\n",
       "      <td>161.0</td>\n",
       "      <td>209.76</td>\n",
       "      <td>6.61</td>\n",
       "      <td>20729\\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10003</td>\n",
       "      <td>East Village/Gramercy/Greenwich Village</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>584.0</td>\n",
       "      <td>1085.47</td>\n",
       "      <td>53801.62</td>\n",
       "      <td>35.0</td>\n",
       "      <td>65.05</td>\n",
       "      <td>3.07</td>\n",
       "      <td>19041\\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10004</td>\n",
       "      <td>Financial District</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1232.67</td>\n",
       "      <td>3650.61</td>\n",
       "      <td>1.0</td>\n",
       "      <td>27.39</td>\n",
       "      <td>4.43</td>\n",
       "      <td>1015\\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10005</td>\n",
       "      <td>Financial District</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>109.0</td>\n",
       "      <td>1298.22</td>\n",
       "      <td>8396.11</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23.82</td>\n",
       "      <td>4.24</td>\n",
       "      <td>2569\\</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Modified_ZCTA                        NEIGHBORHOOD_NAME BOROUGH_GROUP  \\\n",
       "0         10001               Chelsea/NoMad/West Chelsea     Manhattan   \n",
       "1         10002                Chinatown/Lower East Side     Manhattan   \n",
       "2         10003  East Village/Gramercy/Greenwich Village     Manhattan   \n",
       "3         10004                       Financial District     Manhattan   \n",
       "4         10005                       Financial District     Manhattan   \n",
       "\n",
       "   COVID_CASE_COUNT  COVID_CASE_RATE  POP_DENOMINATOR  COVID_DEATH_COUNT  \\\n",
       "0             459.0          1947.97         23563.03               27.0   \n",
       "1            1371.0          1786.19         76755.41              161.0   \n",
       "2             584.0          1085.47         53801.62               35.0   \n",
       "3              45.0          1232.67          3650.61                1.0   \n",
       "4             109.0          1298.22          8396.11                2.0   \n",
       "\n",
       "   COVID_DEATH_RATE  PERCENT_POSITIVE TOTAL_COVID_TESTS\\  \n",
       "0            114.59              5.53              8299\\  \n",
       "1            209.76              6.61             20729\\  \n",
       "2             65.05              3.07             19041\\  \n",
       "3             27.39              4.43              1015\\  \n",
       "4             23.82              4.24              2569\\  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#renamed the column\n",
    "covid_clean_df = covid_pd.rename(columns = {\"\\outl0\\strokewidth0 \\strokec2 MODIFIED_ZCTA\": \"Modified_ZCTA\"})\n",
    "covid_clean_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(178, 4)\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Modified_ZCTA</th>\n",
       "      <th>NEIGHBORHOOD_NAME</th>\n",
       "      <th>BOROUGH_GROUP</th>\n",
       "      <th>COVID_CASE_RATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10001</td>\n",
       "      <td>Chelsea/NoMad/West Chelsea</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>1947.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10002</td>\n",
       "      <td>Chinatown/Lower East Side</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>1786.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10003</td>\n",
       "      <td>East Village/Gramercy/Greenwich Village</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>1085.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10004</td>\n",
       "      <td>Financial District</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>1232.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10005</td>\n",
       "      <td>Financial District</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>1298.22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  Modified_ZCTA                        NEIGHBORHOOD_NAME BOROUGH_GROUP  \\\n",
       "0         10001               Chelsea/NoMad/West Chelsea     Manhattan   \n",
       "1         10002                Chinatown/Lower East Side     Manhattan   \n",
       "2         10003  East Village/Gramercy/Greenwich Village     Manhattan   \n",
       "3         10004                       Financial District     Manhattan   \n",
       "4         10005                       Financial District     Manhattan   \n",
       "\n",
       "   COVID_CASE_RATE  \n",
       "0          1947.97  \n",
       "1          1786.19  \n",
       "2          1085.47  \n",
       "3          1232.67  \n",
       "4          1298.22  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#created a new DF with ZIP Code, Neighborhood names, Borough, and COVID case rate\n",
    "columns_to_extract = [\"Modified_ZCTA\", \"NEIGHBORHOOD_NAME\", \"BOROUGH_GROUP\", \"COVID_CASE_RATE\"]\n",
    "covid_case_rate = pd.DataFrame(covid_clean_df, columns = columns_to_extract)\n",
    "\n",
    "print(covid_case_rate.shape)\n",
    "\n",
    "covid_case_rate.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Modified_ZCTA</th>\n",
       "      <th>NEIGHBORHOOD_NAME</th>\n",
       "      <th>BOROUGH_GROUP</th>\n",
       "      <th>COVID_CASE_RATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>11369</td>\n",
       "      <td>Airport/East Elmhurst</td>\n",
       "      <td>Queens</td>\n",
       "      <td>4837.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>11239</td>\n",
       "      <td>East New York</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>4688.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>11368</td>\n",
       "      <td>Corona/North Corona</td>\n",
       "      <td>Queens</td>\n",
       "      <td>4627.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>10469</td>\n",
       "      <td>Allerton/Baychester/Pelham Gardens/Williamsbridge</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>4602.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>11372</td>\n",
       "      <td>Jackson Heights</td>\n",
       "      <td>Queens</td>\n",
       "      <td>4561.81</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Modified_ZCTA                                  NEIGHBORHOOD_NAME  \\\n",
       "140         11369                              Airport/East Elmhurst   \n",
       "125         11239                                      East New York   \n",
       "139         11368                                Corona/North Corona   \n",
       "74          10469  Allerton/Baychester/Pelham Gardens/Williamsbridge   \n",
       "142         11372                                    Jackson Heights   \n",
       "\n",
       "    BOROUGH_GROUP  COVID_CASE_RATE  \n",
       "140        Queens          4837.88  \n",
       "125      Brooklyn          4688.49  \n",
       "139        Queens          4627.48  \n",
       "74          Bronx          4602.27  \n",
       "142        Queens          4561.81  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sorted the covid case rate from the highest to lowest\n",
    "covid_case_rate = covid_case_rate.sort_values(by=[\"COVID_CASE_RATE\"], ascending = False)\n",
    "\n",
    "covid_case_rate.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4, 4)\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Modified_ZCTA</th>\n",
       "      <th>NEIGHBORHOOD_NAME</th>\n",
       "      <th>BOROUGH_GROUP</th>\n",
       "      <th>COVID_CASE_RATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>11369</td>\n",
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       "      <td>Queens</td>\n",
       "      <td>4837.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>11239</td>\n",
       "      <td>East New York</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>4688.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>11368</td>\n",
       "      <td>Corona/North Corona</td>\n",
       "      <td>Queens</td>\n",
       "      <td>4627.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>10469</td>\n",
       "      <td>Allerton/Baychester/Pelham Gardens/Williamsbridge</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>4602.27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Modified_ZCTA                                  NEIGHBORHOOD_NAME  \\\n",
       "140         11369                              Airport/East Elmhurst   \n",
       "125         11239                                      East New York   \n",
       "139         11368                                Corona/North Corona   \n",
       "74          10469  Allerton/Baychester/Pelham Gardens/Williamsbridge   \n",
       "\n",
       "    BOROUGH_GROUP  COVID_CASE_RATE  \n",
       "140        Queens          4837.88  \n",
       "125      Brooklyn          4688.49  \n",
       "139        Queens          4627.48  \n",
       "74          Bronx          4602.27  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#pulled 4 neighborhoods with the highest covid cases\n",
    "covid_case_max = covid_case_rate.nlargest(4, \"COVID_CASE_RATE\")\n",
    "print(covid_case_max.shape)\n",
    "\n",
    "covid_case_max.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4, 4)\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>Modified_ZCTA</th>\n",
       "      <th>NEIGHBORHOOD_NAME</th>\n",
       "      <th>BOROUGH_GROUP</th>\n",
       "      <th>COVID_CASE_RATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>10280</td>\n",
       "      <td>Battery Park City</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>675.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10007</td>\n",
       "      <td>TriBeCa</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>933.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10012</td>\n",
       "      <td>Greenwich Village/SoHo</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>1000.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>11215</td>\n",
       "      <td>Gowanus/Park Slope/Windsor Terrace</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>1042.44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Modified_ZCTA                   NEIGHBORHOOD_NAME BOROUGH_GROUP  \\\n",
       "42          10280                   Battery Park City     Manhattan   \n",
       "6           10007                             TriBeCa     Manhattan   \n",
       "10          10012              Greenwich Village/SoHo     Manhattan   \n",
       "102         11215  Gowanus/Park Slope/Windsor Terrace      Brooklyn   \n",
       "\n",
       "     COVID_CASE_RATE  \n",
       "42            675.77  \n",
       "6             933.36  \n",
       "10           1000.78  \n",
       "102          1042.44  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#pulled 4 neighborhoods with the lowest covid cases\n",
    "covid_case_min = covid_case_rate.nsmallest(4, \"COVID_CASE_RATE\")\n",
    "print(covid_case_min.shape)\n",
    "\n",
    "covid_case_min.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>DATE_OF_INTEREST</th>\n",
       "      <th>CASE_COUNT</th>\n",
       "      <th>HOSPITALIZED_COUNT</th>\n",
       "      <th>DEATH_COUNT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2/29/20</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3/1/20</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3/2/20</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3/3/20</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3/4/20</td>\n",
       "      <td>5</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>9/23/20</td>\n",
       "      <td>377</td>\n",
       "      <td>31</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>9/24/20</td>\n",
       "      <td>308</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>9/25/20</td>\n",
       "      <td>197</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>9/26/20</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>9/27/20</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>212 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    DATE_OF_INTEREST CASE_COUNT HOSPITALIZED_COUNT  DEATH_COUNT\n",
       "0            2/29/20          1                 11            0\n",
       "1             3/1/20          0                  4            0\n",
       "2             3/2/20          0                 21            0\n",
       "3             3/3/20          2                 20            0\n",
       "4             3/4/20          5                 22            0\n",
       "..               ...        ...                ...          ...\n",
       "207          9/23/20        377                 31            3\n",
       "208          9/24/20        308                 24            4\n",
       "209          9/25/20        197                 16            1\n",
       "210          9/26/20         55                  0            1\n",
       "211          9/27/20         19                  0            0\n",
       "\n",
       "[212 rows x 4 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#NYC Open Data = Daily count of NYC residents who tested positive for SARS-CoV-2, who were hospitalized with COVID-19, \n",
    "#and deaths among COVID-19 patients\n",
    "#read the COVID daily count csv file\n",
    "covid_count = pd.read_csv(covid_daily_count)\n",
    "\n",
    "covid_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th></th>\n",
       "      <th>\\outl0\\strokewidth0 \\strokec2 C/A</th>\n",
       "      <th>UNIT</th>\n",
       "      <th>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>DIVISION</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXITS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6989774.0</td>\n",
       "      <td>0002370411                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A002</td>\n",
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       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>4:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6989795.0</td>\n",
       "      <td>0002370413                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
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       "      <td>SUNDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6989813.0</td>\n",
       "      <td>0002370436                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A002</td>\n",
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       "      <td>59 ST</td>\n",
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       "      <td>SUNDAY</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6989924.0</td>\n",
       "      <td>0002370512                                    ...</td>\n",
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       "      <th>4</th>\n",
       "      <td>A002</td>\n",
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       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6990200.0</td>\n",
       "      <td>0002370573                                    ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  \\outl0\\strokewidth0 \\strokec2 C/A  UNIT       SCP STATION LINENAME DIVISION  \\\n",
       "0                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "1                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "2                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "3                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "4                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "\n",
       "      DATE     DAY      TIME     DESC    ENTRIES  \\\n",
       "0  3/23/19  SUNDAY   0:00:00  REGULAR  6989774.0   \n",
       "1  3/23/19  SUNDAY   4:00:00  REGULAR  6989795.0   \n",
       "2  3/23/19  SUNDAY   8:00:00  REGULAR  6989813.0   \n",
       "3  3/23/19  SUNDAY  12:00:00  REGULAR  6989924.0   \n",
       "4  3/23/19  SUNDAY  16:00:00  REGULAR  6990200.0   \n",
       "\n",
       "                                               EXITS  \n",
       "0  0002370411                                    ...  \n",
       "1  0002370413                                    ...  \n",
       "2  0002370436                                    ...  \n",
       "3  0002370512                                    ...  \n",
       "4  0002370573                                    ...  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#read the March 2019 MTA Subway Ridership Data csv file\n",
    "march_2019_data = pd.read_csv(March_2019_turnstile, header = 9)\n",
    "march_2019_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>DIVISION</th>\n",
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       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXITS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
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       "      <td>SUNDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7411940.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>4:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7411942.0</td>\n",
       "      <td>2515966.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7411945.0</td>\n",
       "      <td>2515979.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7411969.0</td>\n",
       "      <td>2516000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7412028.0</td>\n",
       "      <td>2516024.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  \\outl0\\strokewidth0 \\strokec2 C/A  UNIT       SCP STATION LINENAME DIVISION  \\\n",
       "0                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "1                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "2                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "3                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "4                              A002  R051  02-00-00   59 ST  NQR456W      BMT   \n",
       "\n",
       "      DATE     DAY      TIME     DESC    ENTRIES  \\\n",
       "0  3/21/20  SUNDAY   0:00:00  REGULAR  7411940.0   \n",
       "1  3/21/20  SUNDAY   4:00:00  REGULAR  7411942.0   \n",
       "2  3/21/20  SUNDAY   8:00:00  REGULAR  7411945.0   \n",
       "3  3/21/20  SUNDAY  12:00:00  REGULAR  7411969.0   \n",
       "4  3/21/20  SUNDAY  16:00:00  REGULAR  7412028.0   \n",
       "\n",
       "   EXITS                                                                \n",
       "0                                          2515962.0                    \n",
       "1                                          2515966.0                    \n",
       "2                                          2515979.0                    \n",
       "3                                          2516000.0                    \n",
       "4                                          2516024.0                    "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#read March 2020 MTA Subway Ridership Data csv file\n",
    "march_2020_data = pd.read_csv(March_2020_turnstile, header = 9)\n",
    "march_2020_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
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       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6989774.0</td>\n",
       "      <td>0002370411                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>4:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6989795.0</td>\n",
       "      <td>0002370413                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6989813.0</td>\n",
       "      <td>0002370436                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6989924.0</td>\n",
       "      <td>0002370512                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>6990200.0</td>\n",
       "      <td>0002370573                                    ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        SCP STATION LINENAME     DATE     DAY      TIME     DESC    ENTRIES  \\\n",
       "0  02-00-00   59 ST  NQR456W  3/23/19  SUNDAY   0:00:00  REGULAR  6989774.0   \n",
       "1  02-00-00   59 ST  NQR456W  3/23/19  SUNDAY   4:00:00  REGULAR  6989795.0   \n",
       "2  02-00-00   59 ST  NQR456W  3/23/19  SUNDAY   8:00:00  REGULAR  6989813.0   \n",
       "3  02-00-00   59 ST  NQR456W  3/23/19  SUNDAY  12:00:00  REGULAR  6989924.0   \n",
       "4  02-00-00   59 ST  NQR456W  3/23/19  SUNDAY  16:00:00  REGULAR  6990200.0   \n",
       "\n",
       "                                                EXIT  \n",
       "0  0002370411                                    ...  \n",
       "1  0002370413                                    ...  \n",
       "2  0002370436                                    ...  \n",
       "3  0002370512                                    ...  \n",
       "4  0002370573                                    ...  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#renamed the column to EXIT and create a new DF with neccessary data for March 2019\n",
    "mar_2019 = march_2019_data.columns[-1]\n",
    "march_2019_data = march_2019_data.rename(columns = {mar_2019: \"EXIT\"})\n",
    "columns_to_use = ['SCP', 'STATION','LINENAME', 'DATE', \"DAY\", 'TIME', 'DESC', 'ENTRIES','EXIT']\n",
    "march_2019_df = pd.DataFrame(march_2019_data, columns = columns_to_use)\n",
    "\n",
    "march_2019_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8271</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7127334.0</td>\n",
       "      <td>0004371361                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8272</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>4:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7127338.0</td>\n",
       "      <td>0004371367                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8273</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7127339.0</td>\n",
       "      <td>0004371370                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8274</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7127356.0</td>\n",
       "      <td>0004371391                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8275</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7127390.0</td>\n",
       "      <td>0004371434                                    ...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194564</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>9:47:43</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>0000000162                                 \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194565</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>11:00:32</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>0000000162                                 \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194566</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>0000000162                                 \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194567</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>0000000162                                 \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194568</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>20:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>0000000162                                 \\</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7956 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             SCP         STATION   LINENAME     DATE       DAY      TIME  \\\n",
       "8271    00-00-00       CITY HALL        NRW  3/23/19    SUNDAY   0:00:00   \n",
       "8272    00-00-00       CITY HALL        NRW  3/23/19    SUNDAY   4:00:00   \n",
       "8273    00-00-00       CITY HALL        NRW  3/23/19    SUNDAY   8:00:00   \n",
       "8274    00-00-00       CITY HALL        NRW  3/23/19    SUNDAY  12:00:00   \n",
       "8275    00-00-00       CITY HALL        NRW  3/23/19    SUNDAY  16:00:00   \n",
       "...          ...             ...        ...      ...       ...       ...   \n",
       "194564    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/29/19  SATURDAY   9:47:43   \n",
       "194565    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/29/19  SATURDAY  11:00:32   \n",
       "194566    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/29/19  SATURDAY  12:00:00   \n",
       "194567    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/29/19  SATURDAY  16:00:00   \n",
       "194568    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/29/19  SATURDAY  20:00:00   \n",
       "\n",
       "           DESC      ENTRIES  \\\n",
       "8271    REGULAR    7127334.0   \n",
       "8272    REGULAR    7127338.0   \n",
       "8273    REGULAR    7127339.0   \n",
       "8274    REGULAR    7127356.0   \n",
       "8275    REGULAR    7127390.0   \n",
       "...         ...          ...   \n",
       "194564  REGULAR  117440512.0   \n",
       "194565  REGULAR  117440512.0   \n",
       "194566  REGULAR  117440512.0   \n",
       "194567  REGULAR  117440512.0   \n",
       "194568  REGULAR  117440512.0   \n",
       "\n",
       "                                                     EXIT  \n",
       "8271    0004371361                                    ...  \n",
       "8272    0004371367                                    ...  \n",
       "8273    0004371370                                    ...  \n",
       "8274    0004371391                                    ...  \n",
       "8275    0004371434                                    ...  \n",
       "...                                                   ...  \n",
       "194564       0000000162                                 \\  \n",
       "194565       0000000162                                 \\  \n",
       "194566       0000000162                                 \\  \n",
       "194567       0000000162                                 \\  \n",
       "194568       0000000162                                 \\  \n",
       "\n",
       "[7956 rows x 9 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#created a new DF with targeted neighborhoods in 2019\n",
    "newdf_2019 = march_2019_df.loc[(march_2019_df[\"STATION\"] == \"E 180 ST\") |\n",
    "                               (march_2019_df[\"STATION\"] == \"86 ST-2 AVE\") |\n",
    "                               (march_2019_df[\"STATION\"] == \"96 ST\") |\n",
    "                               (march_2019_df[\"STATION\"] == \"CITY HALL\") |\n",
    "                               (march_2019_df[\"STATION\"] == \"ATL AV-BARCLAY\") |\n",
    "                               (march_2019_df[\"STATION\"] == \"W 4 ST-WASH SQ\") |\n",
    "                               (march_2019_df[\"STATION\"] == \"BROADWAY JCT\") |\n",
    "                               (march_2019_df[\"STATION\"] == \"JKSN HT-ROOSVLT\") |\n",
    "                               (march_2019_df[\"STATION\"] == \"WORLD TRADE CTR\") |\n",
    "                               (march_2019_df[\"STATION\"] == \"QUEENSBORO PLZ\")]\n",
    "newdf_2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>0:00:00</td>\n",
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       "      <td>7411940.0</td>\n",
       "      <td>2515962.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
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       "      <td>7411942.0</td>\n",
       "      <td>2515966.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7411945.0</td>\n",
       "      <td>2515979.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7411969.0</td>\n",
       "      <td>2516000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7412028.0</td>\n",
       "      <td>2516024.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        SCP STATION LINENAME     DATE     DAY      TIME     DESC    ENTRIES  \\\n",
       "0  02-00-00   59 ST  NQR456W  3/21/20  SUNDAY   0:00:00  REGULAR  7411940.0   \n",
       "1  02-00-00   59 ST  NQR456W  3/21/20  SUNDAY   4:00:00  REGULAR  7411942.0   \n",
       "2  02-00-00   59 ST  NQR456W  3/21/20  SUNDAY   8:00:00  REGULAR  7411945.0   \n",
       "3  02-00-00   59 ST  NQR456W  3/21/20  SUNDAY  12:00:00  REGULAR  7411969.0   \n",
       "4  02-00-00   59 ST  NQR456W  3/21/20  SUNDAY  16:00:00  REGULAR  7412028.0   \n",
       "\n",
       "        EXIT  \n",
       "0  2515962.0  \n",
       "1  2515966.0  \n",
       "2  2515979.0  \n",
       "3  2516000.0  \n",
       "4  2516024.0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#renamed the column to EXIT and create a new DF with neccessary data for March 2020\n",
    "mar_2020 = march_2020_data.columns[-1]\n",
    "march_2020_data = march_2020_data.rename(columns = {mar_2020: \"EXIT\"})\n",
    "columns_to_use = ['SCP', 'STATION','LINENAME', 'DATE', \"DAY\", 'TIME', 'DESC', 'ENTRIES','EXIT']\n",
    "march_2020_df = pd.DataFrame(march_2020_data, columns = columns_to_use)\n",
    "\n",
    "march_2020_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8032</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5524.0</td>\n",
       "      <td>5348.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8033</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>4:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5524.0</td>\n",
       "      <td>5350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8034</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5524.0</td>\n",
       "      <td>5352.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8035</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5527.0</td>\n",
       "      <td>5357.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8036</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>NRW</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5536.0</td>\n",
       "      <td>5365.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197531</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>4:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197532</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197533</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197534</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197535</th>\n",
       "      <td>1/5/01</td>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>BDNQR2345</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>20:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>117440512.0</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7823 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             SCP         STATION   LINENAME     DATE       DAY      TIME  \\\n",
       "8032    00-00-00       CITY HALL        NRW  3/21/20    SUNDAY   0:00:00   \n",
       "8033    00-00-00       CITY HALL        NRW  3/21/20    SUNDAY   4:00:00   \n",
       "8034    00-00-00       CITY HALL        NRW  3/21/20    SUNDAY   8:00:00   \n",
       "8035    00-00-00       CITY HALL        NRW  3/21/20    SUNDAY  12:00:00   \n",
       "8036    00-00-00       CITY HALL        NRW  3/21/20    SUNDAY  16:00:00   \n",
       "...          ...             ...        ...      ...       ...       ...   \n",
       "197531    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/27/20  SATURDAY   4:00:00   \n",
       "197532    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/27/20  SATURDAY   8:00:00   \n",
       "197533    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/27/20  SATURDAY  12:00:00   \n",
       "197534    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/27/20  SATURDAY  16:00:00   \n",
       "197535    1/5/01  ATL AV-BARCLAY  BDNQR2345  3/27/20  SATURDAY  20:00:00   \n",
       "\n",
       "           DESC      ENTRIES    EXIT  \n",
       "8032    REGULAR       5524.0  5348.0  \n",
       "8033    REGULAR       5524.0  5350.0  \n",
       "8034    REGULAR       5524.0  5352.0  \n",
       "8035    REGULAR       5527.0  5357.0  \n",
       "8036    REGULAR       5536.0  5365.0  \n",
       "...         ...          ...     ...  \n",
       "197531  REGULAR  117440512.0   192.0  \n",
       "197532  REGULAR  117440512.0   192.0  \n",
       "197533  REGULAR  117440512.0   192.0  \n",
       "197534  REGULAR  117440512.0   192.0  \n",
       "197535  REGULAR  117440512.0   192.0  \n",
       "\n",
       "[7823 rows x 9 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#created a new DF with targeted neighborhoods in 2020\n",
    "newdf_2020 = march_2020_df.loc[(march_2020_df[\"STATION\"] == \"E 180 ST\") |\n",
    "                               (march_2020_df[\"STATION\"] == \"86 ST-2 AVE\") |\n",
    "                               (march_2020_df[\"STATION\"] == \"96 ST\") |\n",
    "                               (march_2020_df[\"STATION\"] == \"CITY HALL\") |\n",
    "                               (march_2020_df[\"STATION\"] == \"ATL AV-BARCLAY\") |\n",
    "                               (march_2020_df[\"STATION\"] == \"W 4 ST-WASH SQ\") |\n",
    "                               (march_2020_df[\"STATION\"] == \"BROADWAY JCT\") |\n",
    "                               (march_2020_df[\"STATION\"] == \"JKSN HT-ROOSVLT\") |\n",
    "                               (march_2020_df[\"STATION\"] == \"WORLD TRADE CTR\") |\n",
    "                               (march_2020_df[\"STATION\"] == \"QUEENSBORO PLZ\")]\n",
    "newdf_2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">86 ST-2 AVE</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">Q</th>\n",
       "      <th>00-00-00</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3652121.0</td>\n",
       "      <td>0002153115                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-00-01</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2671740.0</td>\n",
       "      <td>0001177733                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-00-02</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2141046.0</td>\n",
       "      <td>0001084700                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-00-03</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1322707.0</td>\n",
       "      <td>0000951102                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-05-00</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570013.0</td>\n",
       "      <td>0050331652                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WORLD TRADE CTR</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">ACE23</th>\n",
       "      <th>1/5/01</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0000000694                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/00</th>\n",
       "      <td>3/25/19</td>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>261000.0</td>\n",
       "      <td>0000060649                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/01</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>100900.0</td>\n",
       "      <td>0000022901                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/02</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>604961.0</td>\n",
       "      <td>0000159598                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/03</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>140171.0</td>\n",
       "      <td>0000067081                                    \\</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>187 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      DATE        DAY     TIME     DESC  \\\n",
       "STATION         LINENAME SCP                                              \n",
       "86 ST-2 AVE     Q        00-00-00  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-00-01  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-00-02  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-00-03  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-05-00  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "...                                    ...        ...      ...      ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01    3/29/19  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/00    3/25/19    TUESDAY  8:00:00  REGULAR   \n",
       "                         1/6/01    3/29/19  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/02    3/29/19  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/03    3/29/19  WEDNESDAY  8:00:00  REGULAR   \n",
       "\n",
       "                                      ENTRIES  \\\n",
       "STATION         LINENAME SCP                    \n",
       "86 ST-2 AVE     Q        00-00-00   3652121.0   \n",
       "                         00-00-01   2671740.0   \n",
       "                         00-00-02   2141046.0   \n",
       "                         00-00-03   1322707.0   \n",
       "                         00-05-00  36570013.0   \n",
       "...                                       ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01           0.0   \n",
       "                         1/6/00      261000.0   \n",
       "                         1/6/01      100900.0   \n",
       "                         1/6/02      604961.0   \n",
       "                         1/6/03      140171.0   \n",
       "\n",
       "                                                                                EXIT  \n",
       "STATION         LINENAME SCP                                                          \n",
       "86 ST-2 AVE     Q        00-00-00  0002153115                                    ...  \n",
       "                         00-00-01  0001177733                                    ...  \n",
       "                         00-00-02  0001084700                                    ...  \n",
       "                         00-00-03  0000951102                                    ...  \n",
       "                         00-05-00  0050331652                                    ...  \n",
       "...                                                                              ...  \n",
       "WORLD TRADE CTR ACE23    1/5/01      0000000694                                    \\  \n",
       "                         1/6/00      0000060649                                    \\  \n",
       "                         1/6/01      0000022901                                    \\  \n",
       "                         1/6/02      0000159598                                    \\  \n",
       "                         1/6/03      0000067081                                    \\  \n",
       "\n",
       "[187 rows x 6 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#found the highest cumulative entries count based on station, line name, SCP for March 2019\n",
    "march_2019_max = newdf_2019.groupby([\"STATION\", \"LINENAME\",\"SCP\"]).max()\n",
    "\n",
    "march_2019_max"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570313.0</td>\n",
       "      <td>50331652.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WORLD TRADE CTR</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">ACE23</th>\n",
       "      <th>1/5/01</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>708.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/00</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>403205.0</td>\n",
       "      <td>107304.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/01</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>401947.0</td>\n",
       "      <td>92897.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/02</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1033710.0</td>\n",
       "      <td>281265.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/03</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619858.0</td>\n",
       "      <td>307132.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>189 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      DATE        DAY     TIME     DESC  \\\n",
       "STATION         LINENAME SCP                                              \n",
       "86 ST-2 AVE     Q        00-00-00  3/27/20  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-00-01  3/27/20  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-00-02  3/27/20  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-00-03  3/27/20  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-05-00  3/27/20  WEDNESDAY  9:00:00  REGULAR   \n",
       "...                                    ...        ...      ...      ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01    3/27/20  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/00    3/27/20  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/01    3/27/20  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/02    3/27/20  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/03    3/27/20  WEDNESDAY  8:00:00  REGULAR   \n",
       "\n",
       "                                      ENTRIES        EXIT  \n",
       "STATION         LINENAME SCP                               \n",
       "86 ST-2 AVE     Q        00-00-00   5302061.0   2988082.0  \n",
       "                         00-00-01   3876825.0   1629249.0  \n",
       "                         00-00-02   3073461.0   1544023.0  \n",
       "                         00-00-03   2042798.0   1461538.0  \n",
       "                         00-05-00  36570313.0  50331652.0  \n",
       "...                                       ...         ...  \n",
       "WORLD TRADE CTR ACE23    1/5/01           0.0       708.0  \n",
       "                         1/6/00      403205.0    107304.0  \n",
       "                         1/6/01      401947.0     92897.0  \n",
       "                         1/6/02     1033710.0    281265.0  \n",
       "                         1/6/03      619858.0    307132.0  \n",
       "\n",
       "[189 rows x 6 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#found the highest cumulative entries count based on station, line name, SCP for March 2020\n",
    "march_2020_max = newdf_2020.groupby([\"STATION\", \"LINENAME\", \"SCP\"]).max()\n",
    "\n",
    "march_2020_max"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">86 ST-2 AVE</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">Q</th>\n",
       "      <th>00-00-00</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3619381.0</td>\n",
       "      <td>0002134693                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-00-01</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2648355.0</td>\n",
       "      <td>0001167294                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-00-02</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2122526.0</td>\n",
       "      <td>0001074938                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-00-03</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1309084.0</td>\n",
       "      <td>0000941007                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-05-00</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570002.0</td>\n",
       "      <td>0050331652                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WORLD TRADE CTR</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">ACE23</th>\n",
       "      <th>1/5/01</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0000000694                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/00</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>260549.0</td>\n",
       "      <td>0000060511                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/01</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>95007.0</td>\n",
       "      <td>0000021789                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/02</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>597179.0</td>\n",
       "      <td>0000157812                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/03</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>131580.0</td>\n",
       "      <td>0000063117                                    \\</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>187 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      DATE     DAY      TIME     DESC  \\\n",
       "STATION         LINENAME SCP                                            \n",
       "86 ST-2 AVE     Q        00-00-00  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-00-01  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-00-02  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-00-03  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-05-00  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "...                                    ...     ...       ...      ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01    3/23/19  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/00    3/23/19  MONDAY   0:00:00  REGULAR   \n",
       "                         1/6/01    3/23/19  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/02    3/23/19  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/03    3/23/19  FRIDAY   0:00:00  REGULAR   \n",
       "\n",
       "                                      ENTRIES  \\\n",
       "STATION         LINENAME SCP                    \n",
       "86 ST-2 AVE     Q        00-00-00   3619381.0   \n",
       "                         00-00-01   2648355.0   \n",
       "                         00-00-02   2122526.0   \n",
       "                         00-00-03   1309084.0   \n",
       "                         00-05-00  36570002.0   \n",
       "...                                       ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01           0.0   \n",
       "                         1/6/00      260549.0   \n",
       "                         1/6/01       95007.0   \n",
       "                         1/6/02      597179.0   \n",
       "                         1/6/03      131580.0   \n",
       "\n",
       "                                                                                EXIT  \n",
       "STATION         LINENAME SCP                                                          \n",
       "86 ST-2 AVE     Q        00-00-00  0002134693                                    ...  \n",
       "                         00-00-01  0001167294                                    ...  \n",
       "                         00-00-02  0001074938                                    ...  \n",
       "                         00-00-03  0000941007                                    ...  \n",
       "                         00-05-00  0050331652                                    ...  \n",
       "...                                                                              ...  \n",
       "WORLD TRADE CTR ACE23    1/5/01      0000000694                                    \\  \n",
       "                         1/6/00      0000060511                                    \\  \n",
       "                         1/6/01      0000021789                                    \\  \n",
       "                         1/6/02      0000157812                                    \\  \n",
       "                         1/6/03      0000063117                                    \\  \n",
       "\n",
       "[187 rows x 6 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#found the lowest cumulative entries count based on station, line name, SCP for March 2019\n",
    "march_2019_min = newdf_2019.groupby([\"STATION\", \"LINENAME\", \"SCP\"]).min()\n",
    "\n",
    "march_2019_min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>TIME</th>\n",
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       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">86 ST-2 AVE</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">Q</th>\n",
       "      <th>00-00-00</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
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       "      <td>5298209.0</td>\n",
       "      <td>2984796.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-00-01</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3875060.0</td>\n",
       "      <td>1627996.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-00-02</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3072294.0</td>\n",
       "      <td>1542951.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-00-03</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2042042.0</td>\n",
       "      <td>1460301.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-05-00</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570309.0</td>\n",
       "      <td>50331652.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WORLD TRADE CTR</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">ACE23</th>\n",
       "      <th>1/5/01</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>708.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/00</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>403048.0</td>\n",
       "      <td>107204.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/01</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>401628.0</td>\n",
       "      <td>92786.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/02</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1032921.0</td>\n",
       "      <td>280985.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/03</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619150.0</td>\n",
       "      <td>306313.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>189 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      DATE     DAY      TIME     DESC  \\\n",
       "STATION         LINENAME SCP                                            \n",
       "86 ST-2 AVE     Q        00-00-00  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-00-01  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-00-02  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-00-03  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-05-00  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "...                                    ...     ...       ...      ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01    3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/00    3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/01    3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/02    3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/03    3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "\n",
       "                                      ENTRIES        EXIT  \n",
       "STATION         LINENAME SCP                               \n",
       "86 ST-2 AVE     Q        00-00-00   5298209.0   2984796.0  \n",
       "                         00-00-01   3875060.0   1627996.0  \n",
       "                         00-00-02   3072294.0   1542951.0  \n",
       "                         00-00-03   2042042.0   1460301.0  \n",
       "                         00-05-00  36570309.0  50331652.0  \n",
       "...                                       ...         ...  \n",
       "WORLD TRADE CTR ACE23    1/5/01           0.0       708.0  \n",
       "                         1/6/00      403048.0    107204.0  \n",
       "                         1/6/01      401628.0     92786.0  \n",
       "                         1/6/02     1032921.0    280985.0  \n",
       "                         1/6/03      619150.0    306313.0  \n",
       "\n",
       "[189 rows x 6 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#found the lowest cumulative entries count based on station, line name, SCP for March 2020\n",
    "march_2020_min = newdf_2020.groupby([\"STATION\", \"LINENAME\", \"SCP\"]).min()\n",
    "\n",
    "march_2020_min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">86 ST-2 AVE</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">Q</th>\n",
       "      <th>00-00-00</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3652121.0</td>\n",
       "      <td>0002153115                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
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       "      <td>REGULAR</td>\n",
       "      <td>3619381.0</td>\n",
       "      <td>0002134693                                    ...</td>\n",
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       "      <th>00-00-01</th>\n",
       "      <td>3/29/19</td>\n",
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       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2671740.0</td>\n",
       "      <td>0001177733                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2648355.0</td>\n",
       "      <td>0001167294                                    ...</td>\n",
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       "      <th>00-00-02</th>\n",
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       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2141046.0</td>\n",
       "      <td>0001084700                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2122526.0</td>\n",
       "      <td>0001074938                                    ...</td>\n",
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       "    <tr>\n",
       "      <th>00-00-03</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1322707.0</td>\n",
       "      <td>0000951102                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1309084.0</td>\n",
       "      <td>0000941007                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00-05-00</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570013.0</td>\n",
       "      <td>0050331652                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570002.0</td>\n",
       "      <td>0050331652                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WORLD TRADE CTR</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">ACE23</th>\n",
       "      <th>1/5/01</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0000000694                                    \\</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0000000694                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/00</th>\n",
       "      <td>3/25/19</td>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>261000.0</td>\n",
       "      <td>0000060649                                    \\</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>260549.0</td>\n",
       "      <td>0000060511                                    \\</td>\n",
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       "    <tr>\n",
       "      <th>1/6/01</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
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       "      <td>100900.0</td>\n",
       "      <td>0000022901                                    \\</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>95007.0</td>\n",
       "      <td>0000021789                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/02</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
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       "      <td>604961.0</td>\n",
       "      <td>0000159598                                    \\</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>597179.0</td>\n",
       "      <td>0000157812                                    \\</td>\n",
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       "    <tr>\n",
       "      <th>1/6/03</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>140171.0</td>\n",
       "      <td>0000067081                                    \\</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>131580.0</td>\n",
       "      <td>0000063117                                    \\</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>187 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    DATE_x      DAY_x   TIME_x   DESC_x  \\\n",
       "STATION         LINENAME SCP                                              \n",
       "86 ST-2 AVE     Q        00-00-00  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-00-01  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-00-02  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-00-03  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "                         00-05-00  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "...                                    ...        ...      ...      ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01    3/29/19  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/00    3/25/19    TUESDAY  8:00:00  REGULAR   \n",
       "                         1/6/01    3/29/19  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/02    3/29/19  WEDNESDAY  8:00:00  REGULAR   \n",
       "                         1/6/03    3/29/19  WEDNESDAY  8:00:00  REGULAR   \n",
       "\n",
       "                                    ENTRIES_x  \\\n",
       "STATION         LINENAME SCP                    \n",
       "86 ST-2 AVE     Q        00-00-00   3652121.0   \n",
       "                         00-00-01   2671740.0   \n",
       "                         00-00-02   2141046.0   \n",
       "                         00-00-03   1322707.0   \n",
       "                         00-05-00  36570013.0   \n",
       "...                                       ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01           0.0   \n",
       "                         1/6/00      261000.0   \n",
       "                         1/6/01      100900.0   \n",
       "                         1/6/02      604961.0   \n",
       "                         1/6/03      140171.0   \n",
       "\n",
       "                                                                              EXIT_x  \\\n",
       "STATION         LINENAME SCP                                                           \n",
       "86 ST-2 AVE     Q        00-00-00  0002153115                                    ...   \n",
       "                         00-00-01  0001177733                                    ...   \n",
       "                         00-00-02  0001084700                                    ...   \n",
       "                         00-00-03  0000951102                                    ...   \n",
       "                         00-05-00  0050331652                                    ...   \n",
       "...                                                                              ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01      0000000694                                    \\   \n",
       "                         1/6/00      0000060649                                    \\   \n",
       "                         1/6/01      0000022901                                    \\   \n",
       "                         1/6/02      0000159598                                    \\   \n",
       "                         1/6/03      0000067081                                    \\   \n",
       "\n",
       "                                    DATE_y   DAY_y    TIME_y   DESC_y  \\\n",
       "STATION         LINENAME SCP                                            \n",
       "86 ST-2 AVE     Q        00-00-00  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-00-01  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-00-02  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-00-03  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "                         00-05-00  3/23/19  FRIDAY  13:00:00  REGULAR   \n",
       "...                                    ...     ...       ...      ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01    3/23/19  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/00    3/23/19  MONDAY   0:00:00  REGULAR   \n",
       "                         1/6/01    3/23/19  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/02    3/23/19  FRIDAY   0:00:00  REGULAR   \n",
       "                         1/6/03    3/23/19  FRIDAY   0:00:00  REGULAR   \n",
       "\n",
       "                                    ENTRIES_y  \\\n",
       "STATION         LINENAME SCP                    \n",
       "86 ST-2 AVE     Q        00-00-00   3619381.0   \n",
       "                         00-00-01   2648355.0   \n",
       "                         00-00-02   2122526.0   \n",
       "                         00-00-03   1309084.0   \n",
       "                         00-05-00  36570002.0   \n",
       "...                                       ...   \n",
       "WORLD TRADE CTR ACE23    1/5/01           0.0   \n",
       "                         1/6/00      260549.0   \n",
       "                         1/6/01       95007.0   \n",
       "                         1/6/02      597179.0   \n",
       "                         1/6/03      131580.0   \n",
       "\n",
       "                                                                              EXIT_y  \n",
       "STATION         LINENAME SCP                                                          \n",
       "86 ST-2 AVE     Q        00-00-00  0002134693                                    ...  \n",
       "                         00-00-01  0001167294                                    ...  \n",
       "                         00-00-02  0001074938                                    ...  \n",
       "                         00-00-03  0000941007                                    ...  \n",
       "                         00-05-00  0050331652                                    ...  \n",
       "...                                                                              ...  \n",
       "WORLD TRADE CTR ACE23    1/5/01      0000000694                                    \\  \n",
       "                         1/6/00      0000060511                                    \\  \n",
       "                         1/6/01      0000021789                                    \\  \n",
       "                         1/6/02      0000157812                                    \\  \n",
       "                         1/6/03      0000063117                                    \\  \n",
       "\n",
       "[187 rows x 12 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#merged the DF with highest entries and lowest entries into one DF for March 2019\n",
    "march_2019_merge = pd.merge(march_2019_max, march_2019_min, on = [\"STATION\", \"LINENAME\", \"SCP\"], how = \"left\")\n",
    "\n",
    "march_2019_merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>3876825.0</td>\n",
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       "      <td>3875060.0</td>\n",
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       "      <td>3072294.0</td>\n",
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       "      <td>2042798.0</td>\n",
       "      <td>1461538.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
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       "      <td>2042042.0</td>\n",
       "      <td>1460301.0</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WORLD TRADE CTR</th>\n",
       "      <th>1/5/01</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>708.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>708.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/00</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>403205.0</td>\n",
       "      <td>107304.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>403048.0</td>\n",
       "      <td>107204.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/01</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>401947.0</td>\n",
       "      <td>92897.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>401628.0</td>\n",
       "      <td>92786.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/02</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1033710.0</td>\n",
       "      <td>281265.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1032921.0</td>\n",
       "      <td>280985.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/6/03</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619858.0</td>\n",
       "      <td>307132.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619150.0</td>\n",
       "      <td>306313.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>219 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           DATE_x      DAY_x   TIME_x   DESC_x   ENTRIES_x  \\\n",
       "STATION         SCP                                                          \n",
       "86 ST-2 AVE     00-00-00  3/27/20  WEDNESDAY  9:00:00  REGULAR   5302061.0   \n",
       "                00-00-01  3/27/20  WEDNESDAY  9:00:00  REGULAR   3876825.0   \n",
       "                00-00-02  3/27/20  WEDNESDAY  9:00:00  REGULAR   3073461.0   \n",
       "                00-00-03  3/27/20  WEDNESDAY  9:00:00  REGULAR   2042798.0   \n",
       "                00-05-00  3/27/20  WEDNESDAY  9:00:00  REGULAR  36570313.0   \n",
       "...                           ...        ...      ...      ...         ...   \n",
       "WORLD TRADE CTR 1/5/01    3/27/20  WEDNESDAY  8:00:00  REGULAR         0.0   \n",
       "                1/6/00    3/27/20  WEDNESDAY  8:00:00  REGULAR    403205.0   \n",
       "                1/6/01    3/27/20  WEDNESDAY  8:00:00  REGULAR    401947.0   \n",
       "                1/6/02    3/27/20  WEDNESDAY  8:00:00  REGULAR   1033710.0   \n",
       "                1/6/03    3/27/20  WEDNESDAY  8:00:00  REGULAR    619858.0   \n",
       "\n",
       "                              EXIT_x   DATE_y   DAY_y    TIME_y   DESC_y  \\\n",
       "STATION         SCP                                                        \n",
       "86 ST-2 AVE     00-00-00   2988082.0  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "                00-00-01   1629249.0  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "                00-00-02   1544023.0  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "                00-00-03   1461538.0  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "                00-05-00  50331652.0  3/21/20  FRIDAY  13:00:00  REGULAR   \n",
       "...                              ...      ...     ...       ...      ...   \n",
       "WORLD TRADE CTR 1/5/01         708.0  3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "                1/6/00      107304.0  3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "                1/6/01       92897.0  3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "                1/6/02      281265.0  3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "                1/6/03      307132.0  3/21/20  FRIDAY   0:00:00  REGULAR   \n",
       "\n",
       "                           ENTRIES_y      EXIT_y  \n",
       "STATION         SCP                               \n",
       "86 ST-2 AVE     00-00-00   5298209.0   2984796.0  \n",
       "                00-00-01   3875060.0   1627996.0  \n",
       "                00-00-02   3072294.0   1542951.0  \n",
       "                00-00-03   2042042.0   1460301.0  \n",
       "                00-05-00  36570309.0  50331652.0  \n",
       "...                              ...         ...  \n",
       "WORLD TRADE CTR 1/5/01           0.0       708.0  \n",
       "                1/6/00      403048.0    107204.0  \n",
       "                1/6/01      401628.0     92786.0  \n",
       "                1/6/02     1032921.0    280985.0  \n",
       "                1/6/03      619150.0    306313.0  \n",
       "\n",
       "[219 rows x 12 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#merged the DF with highest cumulative entries and lowest cumulative entries into one DF for March 2020\n",
    "march_2020_merge = pd.merge(march_2020_max, march_2020_min, on = [\"STATION\", \"SCP\"], how = \"left\")\n",
    "\n",
    "march_2020_merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DATE_x</th>\n",
       "      <th>DAY_x</th>\n",
       "      <th>TIME_x</th>\n",
       "      <th>DESC_x</th>\n",
       "      <th>ENTRIES_x</th>\n",
       "      <th>EXIT_x</th>\n",
       "      <th>DATE_y</th>\n",
       "      <th>DAY_y</th>\n",
       "      <th>TIME_y</th>\n",
       "      <th>DESC_y</th>\n",
       "      <th>ENTRIES_y</th>\n",
       "      <th>EXIT_y</th>\n",
       "      <th>ENTRIES CHANGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3652121.0</td>\n",
       "      <td>0002153115                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3619381.0</td>\n",
       "      <td>0002134693                                    ...</td>\n",
       "      <td>32740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-00-01</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2671740.0</td>\n",
       "      <td>0001177733                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2648355.0</td>\n",
       "      <td>0001167294                                    ...</td>\n",
       "      <td>23385.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-00-02</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2141046.0</td>\n",
       "      <td>0001084700                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2122526.0</td>\n",
       "      <td>0001074938                                    ...</td>\n",
       "      <td>18520.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-00-03</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1322707.0</td>\n",
       "      <td>0000951102                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1309084.0</td>\n",
       "      <td>0000941007                                    ...</td>\n",
       "      <td>13623.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-05-00</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570013.0</td>\n",
       "      <td>0050331652                                    ...</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570002.0</td>\n",
       "      <td>0050331652                                    ...</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       STATION LINENAME       SCP   DATE_x      DAY_x   TIME_x   DESC_x  \\\n",
       "0  86 ST-2 AVE        Q  00-00-00  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "1  86 ST-2 AVE        Q  00-00-01  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "2  86 ST-2 AVE        Q  00-00-02  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "3  86 ST-2 AVE        Q  00-00-03  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "4  86 ST-2 AVE        Q  00-05-00  3/29/19  WEDNESDAY  9:00:00  REGULAR   \n",
       "\n",
       "    ENTRIES_x                                             EXIT_x   DATE_y  \\\n",
       "0   3652121.0  0002153115                                    ...  3/23/19   \n",
       "1   2671740.0  0001177733                                    ...  3/23/19   \n",
       "2   2141046.0  0001084700                                    ...  3/23/19   \n",
       "3   1322707.0  0000951102                                    ...  3/23/19   \n",
       "4  36570013.0  0050331652                                    ...  3/23/19   \n",
       "\n",
       "    DAY_y    TIME_y   DESC_y   ENTRIES_y  \\\n",
       "0  FRIDAY  13:00:00  REGULAR   3619381.0   \n",
       "1  FRIDAY  13:00:00  REGULAR   2648355.0   \n",
       "2  FRIDAY  13:00:00  REGULAR   2122526.0   \n",
       "3  FRIDAY  13:00:00  REGULAR   1309084.0   \n",
       "4  FRIDAY  13:00:00  REGULAR  36570002.0   \n",
       "\n",
       "                                              EXIT_y  ENTRIES CHANGE  \n",
       "0  0002134693                                    ...         32740.0  \n",
       "1  0001167294                                    ...         23385.0  \n",
       "2  0001074938                                    ...         18520.0  \n",
       "3  0000941007                                    ...         13623.0  \n",
       "4  0050331652                                    ...            11.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#added a new column with the entry count per day for March 2019\n",
    "march_2019_merge[\"ENTRIES CHANGE\"] = march_2019_merge[\"ENTRIES_x\"] - march_2019_merge[\"ENTRIES_y\"]\n",
    "march_2019_merge = march_2019_merge.reset_index()\n",
    "march_2019_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATION</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DATE_x</th>\n",
       "      <th>DAY_x</th>\n",
       "      <th>TIME_x</th>\n",
       "      <th>DESC_x</th>\n",
       "      <th>ENTRIES_x</th>\n",
       "      <th>EXIT_x</th>\n",
       "      <th>DATE_y</th>\n",
       "      <th>DAY_y</th>\n",
       "      <th>TIME_y</th>\n",
       "      <th>DESC_y</th>\n",
       "      <th>ENTRIES_y</th>\n",
       "      <th>EXIT_y</th>\n",
       "      <th>ENTRIES CHANGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5302061.0</td>\n",
       "      <td>2988082.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298209.0</td>\n",
       "      <td>2984796.0</td>\n",
       "      <td>3852.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>00-00-01</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3876825.0</td>\n",
       "      <td>1629249.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3875060.0</td>\n",
       "      <td>1627996.0</td>\n",
       "      <td>1765.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>00-00-02</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3073461.0</td>\n",
       "      <td>1544023.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3072294.0</td>\n",
       "      <td>1542951.0</td>\n",
       "      <td>1167.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>00-00-03</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2042798.0</td>\n",
       "      <td>1461538.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2042042.0</td>\n",
       "      <td>1460301.0</td>\n",
       "      <td>756.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>00-05-00</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570313.0</td>\n",
       "      <td>50331652.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>36570309.0</td>\n",
       "      <td>50331652.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       STATION       SCP   DATE_x      DAY_x   TIME_x   DESC_x   ENTRIES_x  \\\n",
       "0  86 ST-2 AVE  00-00-00  3/27/20  WEDNESDAY  9:00:00  REGULAR   5302061.0   \n",
       "1  86 ST-2 AVE  00-00-01  3/27/20  WEDNESDAY  9:00:00  REGULAR   3876825.0   \n",
       "2  86 ST-2 AVE  00-00-02  3/27/20  WEDNESDAY  9:00:00  REGULAR   3073461.0   \n",
       "3  86 ST-2 AVE  00-00-03  3/27/20  WEDNESDAY  9:00:00  REGULAR   2042798.0   \n",
       "4  86 ST-2 AVE  00-05-00  3/27/20  WEDNESDAY  9:00:00  REGULAR  36570313.0   \n",
       "\n",
       "       EXIT_x   DATE_y   DAY_y    TIME_y   DESC_y   ENTRIES_y      EXIT_y  \\\n",
       "0   2988082.0  3/21/20  FRIDAY  13:00:00  REGULAR   5298209.0   2984796.0   \n",
       "1   1629249.0  3/21/20  FRIDAY  13:00:00  REGULAR   3875060.0   1627996.0   \n",
       "2   1544023.0  3/21/20  FRIDAY  13:00:00  REGULAR   3072294.0   1542951.0   \n",
       "3   1461538.0  3/21/20  FRIDAY  13:00:00  REGULAR   2042042.0   1460301.0   \n",
       "4  50331652.0  3/21/20  FRIDAY  13:00:00  REGULAR  36570309.0  50331652.0   \n",
       "\n",
       "   ENTRIES CHANGE  \n",
       "0          3852.0  \n",
       "1          1765.0  \n",
       "2          1167.0  \n",
       "3           756.0  \n",
       "4             4.0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#added a new column with the entry count per day for March 2020\n",
    "march_2020_merge[\"ENTRIES CHANGE\"] = march_2020_merge[\"ENTRIES_x\"] - march_2020_merge[\"ENTRIES_y\"]\n",
    "march_2020_merge = march_2020_merge.reset_index()\n",
    "march_2020_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>STATION</th>\n",
       "      <th>ENTRIES CHANGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>32740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>23385.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>18520.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>13623.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>451.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>5893.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>7782.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>8591.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>187 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             STATION  ENTRIES CHANGE\n",
       "0        86 ST-2 AVE         32740.0\n",
       "1        86 ST-2 AVE         23385.0\n",
       "2        86 ST-2 AVE         18520.0\n",
       "3        86 ST-2 AVE         13623.0\n",
       "4        86 ST-2 AVE            11.0\n",
       "..               ...             ...\n",
       "182  WORLD TRADE CTR             0.0\n",
       "183  WORLD TRADE CTR           451.0\n",
       "184  WORLD TRADE CTR          5893.0\n",
       "185  WORLD TRADE CTR          7782.0\n",
       "186  WORLD TRADE CTR          8591.0\n",
       "\n",
       "[187 rows x 2 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#created a new DF with the station name and entries count for March 2019\n",
    "columns_to_use = ['STATION','ENTRIES CHANGE']\n",
    "march_2019_entries = pd.DataFrame(march_2019_merge, columns = columns_to_use)\n",
    "march_2019_entries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        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>STATION</th>\n",
       "      <th>ENTRIES CHANGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>3852.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>1765.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>1167.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>756.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>157.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>319.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>789.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>708.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>219 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             STATION  ENTRIES CHANGE\n",
       "0        86 ST-2 AVE          3852.0\n",
       "1        86 ST-2 AVE          1765.0\n",
       "2        86 ST-2 AVE          1167.0\n",
       "3        86 ST-2 AVE           756.0\n",
       "4        86 ST-2 AVE             4.0\n",
       "..               ...             ...\n",
       "214  WORLD TRADE CTR             0.0\n",
       "215  WORLD TRADE CTR           157.0\n",
       "216  WORLD TRADE CTR           319.0\n",
       "217  WORLD TRADE CTR           789.0\n",
       "218  WORLD TRADE CTR           708.0\n",
       "\n",
       "[219 rows x 2 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#created a new DF with the station name and entries count for March 2020\n",
    "columns_to_use = ['STATION','ENTRIES CHANGE']\n",
    "march_2020_entries = pd.DataFrame(march_2020_merge, columns = columns_to_use)\n",
    "march_2020_entries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>TOTAL ENTRIES</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>86 ST-2 AVE</th>\n",
       "      <td>159528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96 ST</th>\n",
       "      <td>382718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATL AV-BARCLAY</th>\n",
       "      <td>268299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BROADWAY JCT</th>\n",
       "      <td>55019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CITY HALL</th>\n",
       "      <td>35982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E 180 ST</th>\n",
       "      <td>44292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JKSN HT-ROOSVLT</th>\n",
       "      <td>317551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QUEENSBORO PLZ</th>\n",
       "      <td>114158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>W 4 ST-WASH SQ</th>\n",
       "      <td>265487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WORLD TRADE CTR</th>\n",
       "      <td>90873</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 TOTAL ENTRIES\n",
       "STATION                       \n",
       "86 ST-2 AVE             159528\n",
       "96 ST                   382718\n",
       "ATL AV-BARCLAY          268299\n",
       "BROADWAY JCT             55019\n",
       "CITY HALL                35982\n",
       "E 180 ST                 44292\n",
       "JKSN HT-ROOSVLT         317551\n",
       "QUEENSBORO PLZ          114158\n",
       "W 4 ST-WASH SQ          265487\n",
       "WORLD TRADE CTR          90873"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#renamed the column and get the sum of total entry counts for each station of March 2019\n",
    "station_change = march_2019_entries.groupby([\"STATION\"]).sum()[\"ENTRIES CHANGE\"].rename(\"TOTAL ENTRIES\")\n",
    "change_2019df = pd.DataFrame(station_change)\n",
    "change_2019df['TOTAL ENTRIES'] = change_2019df['TOTAL ENTRIES'].astype('int64')\n",
    "change_2019df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        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>TOTAL ENTRIES</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>86 ST-2 AVE</th>\n",
       "      <td>12829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96 ST</th>\n",
       "      <td>104596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATL AV-BARCLAY</th>\n",
       "      <td>37918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BROADWAY JCT</th>\n",
       "      <td>18936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CITY HALL</th>\n",
       "      <td>2329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E 180 ST</th>\n",
       "      <td>14040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JKSN HT-ROOSVLT</th>\n",
       "      <td>53313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QUEENSBORO PLZ</th>\n",
       "      <td>11877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>W 4 ST-WASH SQ</th>\n",
       "      <td>18250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WORLD TRADE CTR</th>\n",
       "      <td>6900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 TOTAL ENTRIES\n",
       "STATION                       \n",
       "86 ST-2 AVE              12829\n",
       "96 ST                   104596\n",
       "ATL AV-BARCLAY           37918\n",
       "BROADWAY JCT             18936\n",
       "CITY HALL                 2329\n",
       "E 180 ST                 14040\n",
       "JKSN HT-ROOSVLT          53313\n",
       "QUEENSBORO PLZ           11877\n",
       "W 4 ST-WASH SQ           18250\n",
       "WORLD TRADE CTR           6900"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#renamed the column and get the sum of total entry counts for each station of March 2020\n",
    "station_change = march_2020_entries.groupby([\"STATION\"]).sum()[\"ENTRIES CHANGE\"].rename(\"TOTAL ENTRIES\")\n",
    "change_2020df = pd.DataFrame(station_change)\n",
    "change_2020df['TOTAL ENTRIES'] = change_2020df['TOTAL ENTRIES'].astype('int64')\n",
    "change_2020df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>2019</th>\n",
       "      <th>2020</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1733907</td>\n",
       "      <td>280988</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      2019    2020\n",
       "0  1733907  280988"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#created a new DF with total entry counts for 2019 and 2020\n",
    "total_2019 = change_2019df[\"TOTAL ENTRIES\"].sum()\n",
    "total_2020 = change_2020df[\"TOTAL ENTRIES\"].sum()\n",
    "\n",
    "march_ridership = pd.DataFrame({\"2019\": [total_2019], \"2020\": [total_2020]})\n",
    "march_ridership['2019'] = march_ridership['2019'].astype('int64')\n",
    "march_ridership['2020'] = march_ridership['2020'].astype('int64')\n",
    "\n",
    "march_ridership.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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": [
    "#created a bar graph for Subway Ridership in March\n",
    "march_chart = march_ridership.plot(kind =\"bar\", title = \"Total Ridership in March in 2019 and 2020\")\n",
    "plt.ylabel(\"Total Riders x 10,000\")\n",
    "plt.ylim(0, 2000000)\n",
    "\n",
    "plt.savefig(\"Resources/Total Ridership at March in 2019 & 2020.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>TOTAL ENTRIES_x</th>\n",
       "      <th>TOTAL ENTRIES_y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>86 ST-2 AVE</th>\n",
       "      <td>159528</td>\n",
       "      <td>12829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96 ST</th>\n",
       "      <td>382718</td>\n",
       "      <td>104596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATL AV-BARCLAY</th>\n",
       "      <td>268299</td>\n",
       "      <td>37918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BROADWAY JCT</th>\n",
       "      <td>55019</td>\n",
       "      <td>18936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CITY HALL</th>\n",
       "      <td>35982</td>\n",
       "      <td>2329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E 180 ST</th>\n",
       "      <td>44292</td>\n",
       "      <td>14040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JKSN HT-ROOSVLT</th>\n",
       "      <td>317551</td>\n",
       "      <td>53313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QUEENSBORO PLZ</th>\n",
       "      <td>114158</td>\n",
       "      <td>11877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>W 4 ST-WASH SQ</th>\n",
       "      <td>265487</td>\n",
       "      <td>18250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WORLD TRADE CTR</th>\n",
       "      <td>90873</td>\n",
       "      <td>6900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 TOTAL ENTRIES_x  TOTAL ENTRIES_y\n",
       "STATION                                          \n",
       "86 ST-2 AVE               159528            12829\n",
       "96 ST                     382718           104596\n",
       "ATL AV-BARCLAY            268299            37918\n",
       "BROADWAY JCT               55019            18936\n",
       "CITY HALL                  35982             2329\n",
       "E 180 ST                   44292            14040\n",
       "JKSN HT-ROOSVLT           317551            53313\n",
       "QUEENSBORO PLZ            114158            11877\n",
       "W 4 ST-WASH SQ            265487            18250\n",
       "WORLD TRADE CTR            90873             6900"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#merged into a new DF with total entries from 2019 and 2020\n",
    "march_change = pd.merge(change_2019df, change_2020df, on = \"STATION\", how = \"outer\")\n",
    "\n",
    "march_change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>Total Entries (2019)</th>\n",
       "      <th>Total Entries (2020)</th>\n",
       "      <th>Percent Change (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>86 ST-2 AVE</th>\n",
       "      <td>159528</td>\n",
       "      <td>12829</td>\n",
       "      <td>-91.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96 ST</th>\n",
       "      <td>382718</td>\n",
       "      <td>104596</td>\n",
       "      <td>-72.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATL AV-BARCLAY</th>\n",
       "      <td>268299</td>\n",
       "      <td>37918</td>\n",
       "      <td>-85.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BROADWAY JCT</th>\n",
       "      <td>55019</td>\n",
       "      <td>18936</td>\n",
       "      <td>-65.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CITY HALL</th>\n",
       "      <td>35982</td>\n",
       "      <td>2329</td>\n",
       "      <td>-93.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E 180 ST</th>\n",
       "      <td>44292</td>\n",
       "      <td>14040</td>\n",
       "      <td>-68.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JKSN HT-ROOSVLT</th>\n",
       "      <td>317551</td>\n",
       "      <td>53313</td>\n",
       "      <td>-83.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QUEENSBORO PLZ</th>\n",
       "      <td>114158</td>\n",
       "      <td>11877</td>\n",
       "      <td>-89.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>W 4 ST-WASH SQ</th>\n",
       "      <td>265487</td>\n",
       "      <td>18250</td>\n",
       "      <td>-93.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WORLD TRADE CTR</th>\n",
       "      <td>90873</td>\n",
       "      <td>6900</td>\n",
       "      <td>-92.41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Total Entries (2019)  Total Entries (2020) Percent Change (%)\n",
       "STATION                                                                       \n",
       "86 ST-2 AVE                    159528                 12829             -91.96\n",
       "96 ST                          382718                104596             -72.67\n",
       "ATL AV-BARCLAY                 268299                 37918             -85.87\n",
       "BROADWAY JCT                    55019                 18936             -65.58\n",
       "CITY HALL                       35982                  2329             -93.53\n",
       "E 180 ST                        44292                 14040             -68.30\n",
       "JKSN HT-ROOSVLT                317551                 53313             -83.21\n",
       "QUEENSBORO PLZ                 114158                 11877             -89.60\n",
       "W 4 ST-WASH SQ                 265487                 18250             -93.13\n",
       "WORLD TRADE CTR                 90873                  6900             -92.41"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#renamed the column and found the percent change for each station\n",
    "march_change = march_change.rename(columns = {\"TOTAL ENTRIES_x\": \"Total Entries (2019)\", \"TOTAL ENTRIES_y\": \"Total Entries (2020)\"})\n",
    "\n",
    "march_change[\"Percent Change (%)\"] = round((march_change[\"Total Entries (2020)\"] - march_change[\"Total Entries (2019)\"])/march_change[\"Total Entries (2019)\"] * 100, 2)\n",
    "march_change[\"Percent Change (%)\"] = march_change[\"Percent Change (%)\"].map(\"{:.2f}\".format)\n",
    "\n",
    "march_change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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": [
    "##created a bar graph for Subway Ridership based on stations\n",
    "march_rider_chart = march_change.plot(kind = \"bar\", title = \"Station Ridership at March in 2019 and 2020\")\n",
    "plt.ylabel(\"Turnstile Entries\")\n",
    "plt.ylim(0, 400000)\n",
    "\n",
    "plt.savefig(\"Resources/Station Ridership at March in 2019 & 2020.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>STATION</th>\n",
       "      <th>Percent Change (%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BROADWAY JCT</td>\n",
       "      <td>-65.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>E 180 ST</td>\n",
       "      <td>-68.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>96 ST</td>\n",
       "      <td>-72.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>JKSN HT-ROOSVLT</td>\n",
       "      <td>-83.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>-85.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>QUEENSBORO PLZ</td>\n",
       "      <td>-89.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>-91.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>-92.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>W 4 ST-WASH SQ</td>\n",
       "      <td>-93.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>-93.53</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           STATION  Percent Change (%)\n",
       "0     BROADWAY JCT              -65.58\n",
       "1         E 180 ST              -68.30\n",
       "2            96 ST              -72.67\n",
       "3  JKSN HT-ROOSVLT              -83.21\n",
       "4   ATL AV-BARCLAY              -85.87\n",
       "5   QUEENSBORO PLZ              -89.60\n",
       "6      86 ST-2 AVE              -91.96\n",
       "7  WORLD TRADE CTR              -92.41\n",
       "8   W 4 ST-WASH SQ              -93.13\n",
       "9        CITY HALL              -93.53"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sorted the values based on Percent Change\n",
    "march_change2 = march_change.sort_values(by=[\"Percent Change (%)\"])\n",
    "march_change2 = march_change2.reset_index()\n",
    "columns_to_use = ['STATION','Percent Change (%)']\n",
    "march_change2 = pd.DataFrame(march_change2, columns = columns_to_use)\n",
    "march_change2['Percent Change (%)'] = march_change2['Percent Change (%)'].astype('float64')\n",
    "\n",
    "march_change2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Was there a difference in ridership change YOY in areas with the highest rates of COVID vs areas with the lowest?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>STATION</th>\n",
       "      <th>Percent Change (%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BROADWAY JCT</td>\n",
       "      <td>-65.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>E 180 ST</td>\n",
       "      <td>-68.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>JKSN HT-ROOSVLT</td>\n",
       "      <td>-83.21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           STATION  Percent Change (%)\n",
       "0     BROADWAY JCT              -65.58\n",
       "1         E 180 ST              -68.30\n",
       "3  JKSN HT-ROOSVLT              -83.21"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Create new df with 3 stations with the highest COVID rates\n",
    "highcovid_df = march_change2.loc[(march_change2[\"STATION\"] == \"E 180 ST\") |\n",
    "                                 (march_change2[\"STATION\"] == \"BROADWAY JCT\") |\n",
    "                                 (march_change2[\"STATION\"] == \"JKSN HT-ROOSVLT\")]\n",
    "highcovid_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>STATION</th>\n",
       "      <th>Percent Change (%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ATL AV-BARCLAY</td>\n",
       "      <td>-85.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>W 4 ST-WASH SQ</td>\n",
       "      <td>-93.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CITY HALL</td>\n",
       "      <td>-93.53</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          STATION  Percent Change (%)\n",
       "4  ATL AV-BARCLAY              -85.87\n",
       "8  W 4 ST-WASH SQ              -93.13\n",
       "9       CITY HALL              -93.53"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create new df with 3 stations with the lowest COVID rates\n",
    "lowcovid_df = march_change2.loc[(march_change2[\"STATION\"] == \"W 4 ST-WASH SQ\") | \n",
    "                                (march_change2[\"STATION\"] == \"CITY HALL\") |\n",
    "                                (march_change2[\"STATION\"] == \"ATL AV-BARCLAY\")]\n",
    "lowcovid_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>High Covid</th>\n",
       "      <th>Low Covid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-72.363333</td>\n",
       "      <td>-90.843333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   High Covid  Low Covid\n",
       "0  -72.363333 -90.843333"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create df for charting mean percent change in highest and lowest rate areas\n",
    "low_mean = lowcovid_df[\"Percent Change (%)\"].mean()\n",
    "high_mean = highcovid_df[\"Percent Change (%)\"].mean()\n",
    "\n",
    "high_low_df = pd.DataFrame({\"High Covid\": [high_mean], \"Low Covid\": [low_mean]})\n",
    "\n",
    "high_low_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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": [
    "# Create bar graph to show average ridership in highest and lowest covid areas\n",
    "high_low_df = high_low_df.plot(kind = \"bar\", title = \"Average Ridership Change in Highest vs Lowest Covid Rate Areas\")\n",
    "\n",
    "plt.ylabel(\"Percent Change\")\n",
    "plt.savefig(\"Resources/HighLowCovid_Ridership.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Was there a difference in ridership patterns in Transportation Hubs vs Residential?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>112481</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>1:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3619381.0</td>\n",
       "      <td>0002134693                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112482</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>5:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3619439.0</td>\n",
       "      <td>0002134779                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112483</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3619667.0</td>\n",
       "      <td>0002135019                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112484</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3620548.0</td>\n",
       "      <td>0002135591                                    ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112485</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>17:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>3621618.0</td>\n",
       "      <td>0002136161                                    ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             SCP      STATION LINENAME     DATE     DAY      TIME     DESC  \\\n",
       "112481  00-00-00  86 ST-2 AVE        Q  3/23/19  SUNDAY   1:00:00  REGULAR   \n",
       "112482  00-00-00  86 ST-2 AVE        Q  3/23/19  SUNDAY   5:00:00  REGULAR   \n",
       "112483  00-00-00  86 ST-2 AVE        Q  3/23/19  SUNDAY   9:00:00  REGULAR   \n",
       "112484  00-00-00  86 ST-2 AVE        Q  3/23/19  SUNDAY  13:00:00  REGULAR   \n",
       "112485  00-00-00  86 ST-2 AVE        Q  3/23/19  SUNDAY  17:00:00  REGULAR   \n",
       "\n",
       "          ENTRIES                                               EXIT  \n",
       "112481  3619381.0  0002134693                                    ...  \n",
       "112482  3619439.0  0002134779                                    ...  \n",
       "112483  3619667.0  0002135019                                    ...  \n",
       "112484  3620548.0  0002135591                                    ...  \n",
       "112485  3621618.0  0002136161                                    ...  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Create new df with Penn and UES 86th St for 2019\n",
    "DOW_2019_df = march_2019_df.loc[(march_2019_df[\"STATION\"] == \"34 ST-PENN STA\") | \n",
    "                                (march_2019_df[\"STATION\"] == \"86 ST-2 AVE\")]\n",
    "DOW_2019_df.head() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>112789</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>1:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298209.0</td>\n",
       "      <td>2984796.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112790</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>5:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298214.0</td>\n",
       "      <td>2984808.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112791</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298270.0</td>\n",
       "      <td>2984923.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112792</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298369.0</td>\n",
       "      <td>2985068.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112793</th>\n",
       "      <td>00-00-00</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>17:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298539.0</td>\n",
       "      <td>2985179.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             SCP      STATION LINENAME     DATE     DAY      TIME     DESC  \\\n",
       "112789  00-00-00  86 ST-2 AVE        Q  3/21/20  SUNDAY   1:00:00  REGULAR   \n",
       "112790  00-00-00  86 ST-2 AVE        Q  3/21/20  SUNDAY   5:00:00  REGULAR   \n",
       "112791  00-00-00  86 ST-2 AVE        Q  3/21/20  SUNDAY   9:00:00  REGULAR   \n",
       "112792  00-00-00  86 ST-2 AVE        Q  3/21/20  SUNDAY  13:00:00  REGULAR   \n",
       "112793  00-00-00  86 ST-2 AVE        Q  3/21/20  SUNDAY  17:00:00  REGULAR   \n",
       "\n",
       "          ENTRIES       EXIT  \n",
       "112789  5298209.0  2984796.0  \n",
       "112790  5298214.0  2984808.0  \n",
       "112791  5298270.0  2984923.0  \n",
       "112792  5298369.0  2985068.0  \n",
       "112793  5298539.0  2985179.0  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Create new df with Penn and UES 86th St for 2020\n",
    "DOW_2020_df = march_2020_df.loc[(march_2020_df[\"STATION\"] == \"34 ST-PENN STA\") | \n",
    "                                (march_2020_df[\"STATION\"] == \"86 ST-2 AVE\")]\n",
    "DOW_2020_df.head() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\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></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DAY</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">34 ST-PENN STA</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">123ACE</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">00-00-00</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>3/28/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9491179.0</td>\n",
       "      <td>0005423397                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>3/24/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9471801.0</td>\n",
       "      <td>0005417074                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9495898.0</td>\n",
       "      <td>0005425170                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUNDAY</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9468117.0</td>\n",
       "      <td>0005416711                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THURSDAY</th>\n",
       "      <td>3/27/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9486426.0</td>\n",
       "      <td>0005421597                                    \\</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              DATE     TIME     DESC  \\\n",
       "STATION        LINENAME SCP      DAY                                   \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY    3/28/19  6:00:00  REGULAR   \n",
       "                                 MONDAY    3/24/19  6:00:00  REGULAR   \n",
       "                                 SATURDAY  3/29/19  6:00:00  REGULAR   \n",
       "                                 SUNDAY    3/23/19  6:00:00  REGULAR   \n",
       "                                 THURSDAY  3/27/19  6:00:00  REGULAR   \n",
       "\n",
       "                                             ENTRIES  \\\n",
       "STATION        LINENAME SCP      DAY                   \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY    9491179.0   \n",
       "                                 MONDAY    9471801.0   \n",
       "                                 SATURDAY  9495898.0   \n",
       "                                 SUNDAY    9468117.0   \n",
       "                                 THURSDAY  9486426.0   \n",
       "\n",
       "                                                                                      EXIT  \n",
       "STATION        LINENAME SCP      DAY                                                        \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY    0005423397                                    \\  \n",
       "                                 MONDAY    0005417074                                    \\  \n",
       "                                 SATURDAY  0005425170                                    \\  \n",
       "                                 SUNDAY    0005416711                                    \\  \n",
       "                                 THURSDAY  0005421597                                    \\  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Groupby to isolate Max for Day of Week Per Station, Line, Turnstile ID.\n",
    "DOW2019_max = DOW_2019_df.groupby([\"STATION\", \"LINENAME\", \"SCP\",\"DAY\"]).max()\n",
    "\n",
    "DOW2019_max.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DAY</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">34 ST-PENN STA</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">123ACE</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">00-00-00</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>3/26/20</td>\n",
       "      <td>9:39:41</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>494795.0</td>\n",
       "      <td>200387.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>3/22/20</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>491998.0</td>\n",
       "      <td>199664.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>495408.0</td>\n",
       "      <td>200583.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUNDAY</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>491550.0</td>\n",
       "      <td>199546.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THURSDAY</th>\n",
       "      <td>3/25/20</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>494136.0</td>\n",
       "      <td>200226.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              DATE     TIME     DESC  \\\n",
       "STATION        LINENAME SCP      DAY                                   \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY    3/26/20  9:39:41  REGULAR   \n",
       "                                 MONDAY    3/22/20  6:00:00  REGULAR   \n",
       "                                 SATURDAY  3/27/20  6:00:00  REGULAR   \n",
       "                                 SUNDAY    3/21/20  6:00:00  REGULAR   \n",
       "                                 THURSDAY  3/25/20  6:00:00  REGULAR   \n",
       "\n",
       "                                            ENTRIES      EXIT  \n",
       "STATION        LINENAME SCP      DAY                           \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY    494795.0  200387.0  \n",
       "                                 MONDAY    491998.0  199664.0  \n",
       "                                 SATURDAY  495408.0  200583.0  \n",
       "                                 SUNDAY    491550.0  199546.0  \n",
       "                                 THURSDAY  494136.0  200226.0  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Groupby to isolate Max for Day of Week Per Station, Line, Turnstile ID.\n",
    "DOW2020_max = DOW_2020_df.groupby([\"STATION\", \"LINENAME\", \"SCP\",\"DAY\"]).max()\n",
    "\n",
    "DOW2020_max.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        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></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DAY</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">34 ST-PENN STA</th>\n",
       "      <th rowspan=\"10\" valign=\"top\">123ACE</th>\n",
       "      <th rowspan=\"7\" valign=\"top\">00-00-00</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>3/28/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9486859.0</td>\n",
       "      <td>0005421762                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>3/24/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9468597.0</td>\n",
       "      <td>0005416757                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9491826.0</td>\n",
       "      <td>0005423547                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUNDAY</th>\n",
       "      <td>3/23/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9465056.0</td>\n",
       "      <td>0005416433                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THURSDAY</th>\n",
       "      <td>3/27/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9482150.0</td>\n",
       "      <td>0005420124                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUESDAY</th>\n",
       "      <td>3/25/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9472162.0</td>\n",
       "      <td>0005417098                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEDNESDAY</th>\n",
       "      <td>3/26/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9477019.0</td>\n",
       "      <td>0005418540                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">00-00-01</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>3/28/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9630541.0</td>\n",
       "      <td>0005269748                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>3/24/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9612920.0</td>\n",
       "      <td>0005264288                                    \\</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>3/29/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9635454.0</td>\n",
       "      <td>0005271587                                    \\</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               DATE      TIME     DESC  \\\n",
       "STATION        LINENAME SCP      DAY                                     \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY     3/28/19  10:00:00  REGULAR   \n",
       "                                 MONDAY     3/24/19  10:00:00  REGULAR   \n",
       "                                 SATURDAY   3/29/19  10:00:00  REGULAR   \n",
       "                                 SUNDAY     3/23/19  10:00:00  REGULAR   \n",
       "                                 THURSDAY   3/27/19  10:00:00  REGULAR   \n",
       "                                 TUESDAY    3/25/19  10:00:00  REGULAR   \n",
       "                                 WEDNESDAY  3/26/19  10:00:00  REGULAR   \n",
       "                        00-00-01 FRIDAY     3/28/19  10:00:00  REGULAR   \n",
       "                                 MONDAY     3/24/19  10:00:00  REGULAR   \n",
       "                                 SATURDAY   3/29/19  10:00:00  REGULAR   \n",
       "\n",
       "                                              ENTRIES  \\\n",
       "STATION        LINENAME SCP      DAY                    \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY     9486859.0   \n",
       "                                 MONDAY     9468597.0   \n",
       "                                 SATURDAY   9491826.0   \n",
       "                                 SUNDAY     9465056.0   \n",
       "                                 THURSDAY   9482150.0   \n",
       "                                 TUESDAY    9472162.0   \n",
       "                                 WEDNESDAY  9477019.0   \n",
       "                        00-00-01 FRIDAY     9630541.0   \n",
       "                                 MONDAY     9612920.0   \n",
       "                                 SATURDAY   9635454.0   \n",
       "\n",
       "                                                                                       EXIT  \n",
       "STATION        LINENAME SCP      DAY                                                         \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY     0005421762                                    \\  \n",
       "                                 MONDAY     0005416757                                    \\  \n",
       "                                 SATURDAY   0005423547                                    \\  \n",
       "                                 SUNDAY     0005416433                                    \\  \n",
       "                                 THURSDAY   0005420124                                    \\  \n",
       "                                 TUESDAY    0005417098                                    \\  \n",
       "                                 WEDNESDAY  0005418540                                    \\  \n",
       "                        00-00-01 FRIDAY     0005269748                                    \\  \n",
       "                                 MONDAY     0005264288                                    \\  \n",
       "                                 SATURDAY   0005271587                                    \\  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Groupby to isolate Min for Day of Week Per Station, Line, Turnstile ID.\n",
    "DOW2019_min = DOW_2019_df.groupby([\"STATION\", \"LINENAME\", \"SCP\",\"DAY\"]).min()\n",
    "\n",
    "DOW2019_min.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXIT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DAY</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">34 ST-PENN STA</th>\n",
       "      <th rowspan=\"10\" valign=\"top\">123ACE</th>\n",
       "      <th rowspan=\"7\" valign=\"top\">00-00-00</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>3/26/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>494182.0</td>\n",
       "      <td>200240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>3/22/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>491601.0</td>\n",
       "      <td>199560.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>494857.0</td>\n",
       "      <td>200401.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUNDAY</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>491036.0</td>\n",
       "      <td>199418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THURSDAY</th>\n",
       "      <td>3/25/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>493515.0</td>\n",
       "      <td>200058.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUESDAY</th>\n",
       "      <td>3/23/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>492054.0</td>\n",
       "      <td>199681.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEDNESDAY</th>\n",
       "      <td>3/24/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>492799.0</td>\n",
       "      <td>199883.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">00-00-01</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>3/26/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>11071111.0</td>\n",
       "      <td>5764592.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>3/22/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>11069308.0</td>\n",
       "      <td>5763813.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>11071567.0</td>\n",
       "      <td>5764784.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               DATE      TIME     DESC  \\\n",
       "STATION        LINENAME SCP      DAY                                     \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY     3/26/20  10:00:00  REGULAR   \n",
       "                                 MONDAY     3/22/20  10:00:00  REGULAR   \n",
       "                                 SATURDAY   3/27/20  10:00:00  REGULAR   \n",
       "                                 SUNDAY     3/21/20  10:00:00  REGULAR   \n",
       "                                 THURSDAY   3/25/20  10:00:00  REGULAR   \n",
       "                                 TUESDAY    3/23/20  10:00:00  REGULAR   \n",
       "                                 WEDNESDAY  3/24/20  10:00:00  REGULAR   \n",
       "                        00-00-01 FRIDAY     3/26/20  10:00:00  REGULAR   \n",
       "                                 MONDAY     3/22/20  10:00:00  REGULAR   \n",
       "                                 SATURDAY   3/27/20  10:00:00  REGULAR   \n",
       "\n",
       "                                               ENTRIES       EXIT  \n",
       "STATION        LINENAME SCP      DAY                               \n",
       "34 ST-PENN STA 123ACE   00-00-00 FRIDAY       494182.0   200240.0  \n",
       "                                 MONDAY       491601.0   199560.0  \n",
       "                                 SATURDAY     494857.0   200401.0  \n",
       "                                 SUNDAY       491036.0   199418.0  \n",
       "                                 THURSDAY     493515.0   200058.0  \n",
       "                                 TUESDAY      492054.0   199681.0  \n",
       "                                 WEDNESDAY    492799.0   199883.0  \n",
       "                        00-00-01 FRIDAY     11071111.0  5764592.0  \n",
       "                                 MONDAY     11069308.0  5763813.0  \n",
       "                                 SATURDAY   11071567.0  5764784.0  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Groupby to isolate Min for Day of Week Per Station, Line, Turnstile ID.\n",
    "DOW2020_min = DOW_2020_df.groupby([\"STATION\", \"LINENAME\", \"SCP\",\"DAY\"]).min()\n",
    "\n",
    "DOW2020_min.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DAY</th>\n",
       "      <th>DATE_x</th>\n",
       "      <th>TIME_x</th>\n",
       "      <th>DESC_x</th>\n",
       "      <th>ENTRIES_x</th>\n",
       "      <th>EXIT_x</th>\n",
       "      <th>DATE_y</th>\n",
       "      <th>TIME_y</th>\n",
       "      <th>DESC_y</th>\n",
       "      <th>ENTRIES_y</th>\n",
       "      <th>EXIT_y</th>\n",
       "      <th>ENTRIES CHANGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>3/28/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9491179.0</td>\n",
       "      <td>0005423397                                    \\</td>\n",
       "      <td>3/28/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9486859.0</td>\n",
       "      <td>0005421762                                    \\</td>\n",
       "      <td>4320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>3/24/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9471801.0</td>\n",
       "      <td>0005417074                                    \\</td>\n",
       "      <td>3/24/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9468597.0</td>\n",
       "      <td>0005416757                                    \\</td>\n",
       "      <td>3204.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9495898.0</td>\n",
       "      <td>0005425170                                    \\</td>\n",
       "      <td>3/29/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9491826.0</td>\n",
       "      <td>0005423547                                    \\</td>\n",
       "      <td>4072.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9468117.0</td>\n",
       "      <td>0005416711                                    \\</td>\n",
       "      <td>3/23/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9465056.0</td>\n",
       "      <td>0005416433                                    \\</td>\n",
       "      <td>3061.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>3/27/19</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9486426.0</td>\n",
       "      <td>0005421597                                    \\</td>\n",
       "      <td>3/27/19</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>9482150.0</td>\n",
       "      <td>0005420124                                    \\</td>\n",
       "      <td>4276.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          STATION LINENAME       SCP       DAY   DATE_x   TIME_x   DESC_x  \\\n",
       "0  34 ST-PENN STA   123ACE  00-00-00    FRIDAY  3/28/19  6:00:00  REGULAR   \n",
       "1  34 ST-PENN STA   123ACE  00-00-00    MONDAY  3/24/19  6:00:00  REGULAR   \n",
       "2  34 ST-PENN STA   123ACE  00-00-00  SATURDAY  3/29/19  6:00:00  REGULAR   \n",
       "3  34 ST-PENN STA   123ACE  00-00-00    SUNDAY  3/23/19  6:00:00  REGULAR   \n",
       "4  34 ST-PENN STA   123ACE  00-00-00  THURSDAY  3/27/19  6:00:00  REGULAR   \n",
       "\n",
       "   ENTRIES_x                                           EXIT_x   DATE_y  \\\n",
       "0  9491179.0  0005423397                                    \\  3/28/19   \n",
       "1  9471801.0  0005417074                                    \\  3/24/19   \n",
       "2  9495898.0  0005425170                                    \\  3/29/19   \n",
       "3  9468117.0  0005416711                                    \\  3/23/19   \n",
       "4  9486426.0  0005421597                                    \\  3/27/19   \n",
       "\n",
       "     TIME_y   DESC_y  ENTRIES_y  \\\n",
       "0  10:00:00  REGULAR  9486859.0   \n",
       "1  10:00:00  REGULAR  9468597.0   \n",
       "2  10:00:00  REGULAR  9491826.0   \n",
       "3  10:00:00  REGULAR  9465056.0   \n",
       "4  10:00:00  REGULAR  9482150.0   \n",
       "\n",
       "                                            EXIT_y  ENTRIES CHANGE  \n",
       "0  0005421762                                    \\          4320.0  \n",
       "1  0005416757                                    \\          3204.0  \n",
       "2  0005423547                                    \\          4072.0  \n",
       "3  0005416433                                    \\          3061.0  \n",
       "4  0005420124                                    \\          4276.0  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge min and max into one df, calculate difference and add a column for Entries Change\n",
    "DOW2019_merge = pd.merge(DOW2019_max, DOW2019_min, on = [\"STATION\", \"LINENAME\", \"SCP\", \"DAY\"], how = \"left\")\n",
    "\n",
    "DOW2019_merge[\"ENTRIES CHANGE\"] = DOW2019_merge[\"ENTRIES_x\"] - DOW2019_merge[\"ENTRIES_y\"]\n",
    "DOW2019_merge = DOW2019_merge.reset_index()\n",
    "\n",
    "DOW2019_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DAY</th>\n",
       "      <th>DATE_x</th>\n",
       "      <th>TIME_x</th>\n",
       "      <th>DESC_x</th>\n",
       "      <th>ENTRIES_x</th>\n",
       "      <th>EXIT_x</th>\n",
       "      <th>DATE_y</th>\n",
       "      <th>TIME_y</th>\n",
       "      <th>DESC_y</th>\n",
       "      <th>ENTRIES_y</th>\n",
       "      <th>EXIT_y</th>\n",
       "      <th>ENTRIES CHANGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>3/26/20</td>\n",
       "      <td>9:39:41</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>494795.0</td>\n",
       "      <td>200387.0</td>\n",
       "      <td>3/26/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>494182.0</td>\n",
       "      <td>200240.0</td>\n",
       "      <td>613.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>3/22/20</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>491998.0</td>\n",
       "      <td>199664.0</td>\n",
       "      <td>3/22/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>491601.0</td>\n",
       "      <td>199560.0</td>\n",
       "      <td>397.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>495408.0</td>\n",
       "      <td>200583.0</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>494857.0</td>\n",
       "      <td>200401.0</td>\n",
       "      <td>551.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>491550.0</td>\n",
       "      <td>199546.0</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>491036.0</td>\n",
       "      <td>199418.0</td>\n",
       "      <td>514.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>123ACE</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>3/25/20</td>\n",
       "      <td>6:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>494136.0</td>\n",
       "      <td>200226.0</td>\n",
       "      <td>3/25/20</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>493515.0</td>\n",
       "      <td>200058.0</td>\n",
       "      <td>621.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          STATION LINENAME       SCP       DAY   DATE_x   TIME_x   DESC_x  \\\n",
       "0  34 ST-PENN STA   123ACE  00-00-00    FRIDAY  3/26/20  9:39:41  REGULAR   \n",
       "1  34 ST-PENN STA   123ACE  00-00-00    MONDAY  3/22/20  6:00:00  REGULAR   \n",
       "2  34 ST-PENN STA   123ACE  00-00-00  SATURDAY  3/27/20  6:00:00  REGULAR   \n",
       "3  34 ST-PENN STA   123ACE  00-00-00    SUNDAY  3/21/20  6:00:00  REGULAR   \n",
       "4  34 ST-PENN STA   123ACE  00-00-00  THURSDAY  3/25/20  6:00:00  REGULAR   \n",
       "\n",
       "   ENTRIES_x    EXIT_x   DATE_y    TIME_y   DESC_y  ENTRIES_y    EXIT_y  \\\n",
       "0   494795.0  200387.0  3/26/20  10:00:00  REGULAR   494182.0  200240.0   \n",
       "1   491998.0  199664.0  3/22/20  10:00:00  REGULAR   491601.0  199560.0   \n",
       "2   495408.0  200583.0  3/27/20  10:00:00  REGULAR   494857.0  200401.0   \n",
       "3   491550.0  199546.0  3/21/20  10:00:00  REGULAR   491036.0  199418.0   \n",
       "4   494136.0  200226.0  3/25/20  10:00:00  REGULAR   493515.0  200058.0   \n",
       "\n",
       "   ENTRIES CHANGE  \n",
       "0           613.0  \n",
       "1           397.0  \n",
       "2           551.0  \n",
       "3           514.0  \n",
       "4           621.0  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge min and max into one df, calculate difference and add a column for Entries Change\n",
    "DOW2020_merge = pd.merge(DOW2020_max, DOW2020_min, on = [\"STATION\", \"LINENAME\", \"SCP\", \"DAY\"], how = \"left\")\n",
    "\n",
    "DOW2020_merge[\"ENTRIES CHANGE\"] = DOW2020_merge[\"ENTRIES_x\"] - DOW2020_merge[\"ENTRIES_y\"]\n",
    "DOW2020_merge = DOW2020_merge.reset_index()\n",
    "\n",
    "DOW2020_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>STATION</th>\n",
       "      <th>DAY</th>\n",
       "      <th>ENTRIES CHANGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>4320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>3204.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>4072.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>3061.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>4276.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          STATION       DAY  ENTRIES CHANGE\n",
       "0  34 ST-PENN STA    FRIDAY          4320.0\n",
       "1  34 ST-PENN STA    MONDAY          3204.0\n",
       "2  34 ST-PENN STA  SATURDAY          4072.0\n",
       "3  34 ST-PENN STA    SUNDAY          3061.0\n",
       "4  34 ST-PENN STA  THURSDAY          4276.0"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create df with only necessary columns\n",
    "columns_to_use = ['STATION','DAY','ENTRIES CHANGE']\n",
    "DOW2019_merge = pd.DataFrame(DOW2019_merge, columns = columns_to_use)\n",
    "DOW2019_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>STATION</th>\n",
       "      <th>DAY</th>\n",
       "      <th>ENTRIES CHANGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>613.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>397.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>551.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>514.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>621.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          STATION       DAY  ENTRIES CHANGE\n",
       "0  34 ST-PENN STA    FRIDAY           613.0\n",
       "1  34 ST-PENN STA    MONDAY           397.0\n",
       "2  34 ST-PENN STA  SATURDAY           551.0\n",
       "3  34 ST-PENN STA    SUNDAY           514.0\n",
       "4  34 ST-PENN STA  THURSDAY           621.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create df with only necessary columns\n",
    "columns_to_use = ['STATION','DAY','ENTRIES CHANGE']\n",
    "DOW2020_merge = pd.DataFrame(DOW2020_merge, columns = columns_to_use)\n",
    "DOW2020_merge.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></th>\n",
       "      <th></th>\n",
       "      <th>TOTAL ENTRIES</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>DAY</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"7\" valign=\"top\">34 ST-PENN STA</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>49652.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>25805.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>47757.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUNDAY</th>\n",
       "      <td>26911.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THURSDAY</th>\n",
       "      <td>49662.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUESDAY</th>\n",
       "      <td>48187.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEDNESDAY</th>\n",
       "      <td>49532.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"7\" valign=\"top\">86 ST-2 AVE</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>25292.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>11675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>25200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUNDAY</th>\n",
       "      <td>15576.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THURSDAY</th>\n",
       "      <td>25082.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUESDAY</th>\n",
       "      <td>23256.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEDNESDAY</th>\n",
       "      <td>24765.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          TOTAL ENTRIES\n",
       "STATION        DAY                     \n",
       "34 ST-PENN STA FRIDAY           49652.0\n",
       "               MONDAY           25805.0\n",
       "               SATURDAY         47757.0\n",
       "               SUNDAY           26911.0\n",
       "               THURSDAY         49662.0\n",
       "               TUESDAY          48187.0\n",
       "               WEDNESDAY        49532.0\n",
       "86 ST-2 AVE    FRIDAY           25292.0\n",
       "               MONDAY           11675.0\n",
       "               SATURDAY         25200.0\n",
       "               SUNDAY           15576.0\n",
       "               THURSDAY         25082.0\n",
       "               TUESDAY          23256.0\n",
       "               WEDNESDAY        24765.0"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create df calculating the total change in entries per day of week per station\n",
    "DOW2019_change = DOW2019_merge.groupby([\"STATION\",\"DAY\"]).sum()[\"ENTRIES CHANGE\"].rename(\"TOTAL ENTRIES\")\n",
    "DOW2019_total = pd.DataFrame(DOW2019_change)\n",
    "DOW2019_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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></th>\n",
       "      <th>TOTAL ENTRIES</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>DAY</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"7\" valign=\"top\">34 ST-PENN STA</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>3903.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>2121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>3338.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUNDAY</th>\n",
       "      <td>2979.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THURSDAY</th>\n",
       "      <td>4080.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUESDAY</th>\n",
       "      <td>4684.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEDNESDAY</th>\n",
       "      <td>4250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"7\" valign=\"top\">86 ST-2 AVE</th>\n",
       "      <th>FRIDAY</th>\n",
       "      <td>1669.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONDAY</th>\n",
       "      <td>1045.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SATURDAY</th>\n",
       "      <td>1605.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUNDAY</th>\n",
       "      <td>1690.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THURSDAY</th>\n",
       "      <td>1745.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUESDAY</th>\n",
       "      <td>1787.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEDNESDAY</th>\n",
       "      <td>1903.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          TOTAL ENTRIES\n",
       "STATION        DAY                     \n",
       "34 ST-PENN STA FRIDAY            3903.0\n",
       "               MONDAY            2121.0\n",
       "               SATURDAY          3338.0\n",
       "               SUNDAY            2979.0\n",
       "               THURSDAY          4080.0\n",
       "               TUESDAY           4684.0\n",
       "               WEDNESDAY         4250.0\n",
       "86 ST-2 AVE    FRIDAY            1669.0\n",
       "               MONDAY            1045.0\n",
       "               SATURDAY          1605.0\n",
       "               SUNDAY            1690.0\n",
       "               THURSDAY          1745.0\n",
       "               TUESDAY           1787.0\n",
       "               WEDNESDAY         1903.0"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create df calculating the total change in entries per day of week per station\n",
    "DOW2020_change = DOW2020_merge.groupby([\"STATION\",\"DAY\"]).sum()[\"ENTRIES CHANGE\"].rename(\"TOTAL ENTRIES\")\n",
    "DOW2020_total = pd.DataFrame(DOW2020_change)\n",
    "DOW2020_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\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>STATION</th>\n",
       "      <th>DAY</th>\n",
       "      <th>2020 Entries</th>\n",
       "      <th>2019 Entries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>3903.0</td>\n",
       "      <td>49652.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>2121.0</td>\n",
       "      <td>25805.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>3338.0</td>\n",
       "      <td>47757.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>2979.0</td>\n",
       "      <td>26911.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>4080.0</td>\n",
       "      <td>49662.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>4684.0</td>\n",
       "      <td>48187.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>4250.0</td>\n",
       "      <td>49532.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>1669.0</td>\n",
       "      <td>25292.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>1045.0</td>\n",
       "      <td>11675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>1605.0</td>\n",
       "      <td>25200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>1690.0</td>\n",
       "      <td>15576.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>1745.0</td>\n",
       "      <td>25082.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>1787.0</td>\n",
       "      <td>23256.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>1903.0</td>\n",
       "      <td>24765.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           STATION        DAY  2020 Entries  2019 Entries\n",
       "0   34 ST-PENN STA     FRIDAY        3903.0       49652.0\n",
       "1   34 ST-PENN STA     MONDAY        2121.0       25805.0\n",
       "2   34 ST-PENN STA   SATURDAY        3338.0       47757.0\n",
       "3   34 ST-PENN STA     SUNDAY        2979.0       26911.0\n",
       "4   34 ST-PENN STA   THURSDAY        4080.0       49662.0\n",
       "5   34 ST-PENN STA    TUESDAY        4684.0       48187.0\n",
       "6   34 ST-PENN STA  WEDNESDAY        4250.0       49532.0\n",
       "7      86 ST-2 AVE     FRIDAY        1669.0       25292.0\n",
       "8      86 ST-2 AVE     MONDAY        1045.0       11675.0\n",
       "9      86 ST-2 AVE   SATURDAY        1605.0       25200.0\n",
       "10     86 ST-2 AVE     SUNDAY        1690.0       15576.0\n",
       "11     86 ST-2 AVE   THURSDAY        1745.0       25082.0\n",
       "12     86 ST-2 AVE    TUESDAY        1787.0       23256.0\n",
       "13     86 ST-2 AVE  WEDNESDAY        1903.0       24765.0"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create df to be used for chart \n",
    "DOW_chart = pd.merge(DOW2020_change, DOW2019_change, on = [\"STATION\", \"DAY\"], how = \"left\")\n",
    "DOW_chart = DOW_chart.rename(columns = {\"DAY\": \"DAY\",\"TOTAL ENTRIES_x\": \"2020 Entries\", \n",
    "                                              \"TOTAL ENTRIES_y\": \"2019 Entries\"})\n",
    "DOW_chart = DOW_chart.reset_index()\n",
    "DOW_chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>STATION</th>\n",
       "      <th>DAY</th>\n",
       "      <th>2020 Entries</th>\n",
       "      <th>2019 Entries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>3903.0</td>\n",
       "      <td>49652.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>2121.0</td>\n",
       "      <td>25805.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>3338.0</td>\n",
       "      <td>47757.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>2979.0</td>\n",
       "      <td>26911.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>4080.0</td>\n",
       "      <td>49662.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>4684.0</td>\n",
       "      <td>48187.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>4250.0</td>\n",
       "      <td>49532.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          STATION        DAY  2020 Entries  2019 Entries\n",
       "0  34 ST-PENN STA     FRIDAY        3903.0       49652.0\n",
       "1  34 ST-PENN STA     MONDAY        2121.0       25805.0\n",
       "2  34 ST-PENN STA   SATURDAY        3338.0       47757.0\n",
       "3  34 ST-PENN STA     SUNDAY        2979.0       26911.0\n",
       "4  34 ST-PENN STA   THURSDAY        4080.0       49662.0\n",
       "5  34 ST-PENN STA    TUESDAY        4684.0       48187.0\n",
       "6  34 ST-PENN STA  WEDNESDAY        4250.0       49532.0"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Isolate Penn Sta data in new df\n",
    "station_to_find = \"34 ST-PENN STA\"               \n",
    "Penn_DOW_df = DOW_chart.loc[DOW_chart[\"STATION\"] == station_to_find]\n",
    "\n",
    "Penn_DOW_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>STATION</th>\n",
       "      <th>DAY</th>\n",
       "      <th>2020 Entries</th>\n",
       "      <th>2019 Entries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>1669.0</td>\n",
       "      <td>25292.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>1045.0</td>\n",
       "      <td>11675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>1605.0</td>\n",
       "      <td>25200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>1690.0</td>\n",
       "      <td>15576.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>1745.0</td>\n",
       "      <td>25082.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>1787.0</td>\n",
       "      <td>23256.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>1903.0</td>\n",
       "      <td>24765.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        STATION        DAY  2020 Entries  2019 Entries\n",
       "7   86 ST-2 AVE     FRIDAY        1669.0       25292.0\n",
       "8   86 ST-2 AVE     MONDAY        1045.0       11675.0\n",
       "9   86 ST-2 AVE   SATURDAY        1605.0       25200.0\n",
       "10  86 ST-2 AVE     SUNDAY        1690.0       15576.0\n",
       "11  86 ST-2 AVE   THURSDAY        1745.0       25082.0\n",
       "12  86 ST-2 AVE    TUESDAY        1787.0       23256.0\n",
       "13  86 ST-2 AVE  WEDNESDAY        1903.0       24765.0"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Isolate 86th St data in new df\n",
    "station_to_find = \"86 ST-2 AVE\"               \n",
    "UES_DOW_df = DOW_chart.loc[DOW_chart[\"STATION\"] == station_to_find]\n",
    "\n",
    "UES_DOW_df"
   ]
  },
  {
   "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>DAY</th>\n",
       "      <th>STATION</th>\n",
       "      <th>2020 Entries</th>\n",
       "      <th>2019 Entries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MONDAY</td>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>2121.0</td>\n",
       "      <td>25805.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>4684.0</td>\n",
       "      <td>48187.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>4250.0</td>\n",
       "      <td>49532.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>4080.0</td>\n",
       "      <td>49662.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>3903.0</td>\n",
       "      <td>49652.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>3338.0</td>\n",
       "      <td>47757.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>2979.0</td>\n",
       "      <td>26911.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         DAY         STATION  2020 Entries  2019 Entries\n",
       "0     MONDAY  34 ST-PENN STA        2121.0       25805.0\n",
       "1    TUESDAY  34 ST-PENN STA        4684.0       48187.0\n",
       "2  WEDNESDAY  34 ST-PENN STA        4250.0       49532.0\n",
       "3   THURSDAY  34 ST-PENN STA        4080.0       49662.0\n",
       "4     FRIDAY  34 ST-PENN STA        3903.0       49652.0\n",
       "5   SATURDAY  34 ST-PENN STA        3338.0       47757.0\n",
       "6     SUNDAY  34 ST-PENN STA        2979.0       26911.0"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use loc to fix the order of days of week for x axis\n",
    "field = \"DAY\"\n",
    "day_order = [\"MONDAY\", \"TUESDAY\", \"WEDNESDAY\", \"THURSDAY\", \"FRIDAY\", \"SATURDAY\", \"SUNDAY\"]\n",
    "Penn_sort_df = Penn_DOW_df.set_index(field).loc[day_order]\n",
    "Penn_sort_df = Penn_sort_df.reset_index()\n",
    "Penn_sort_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>DAY</th>\n",
       "      <th>STATION</th>\n",
       "      <th>2020 Entries</th>\n",
       "      <th>2019 Entries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MONDAY</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>1045.0</td>\n",
       "      <td>11675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>1787.0</td>\n",
       "      <td>23256.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>1903.0</td>\n",
       "      <td>24765.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>1745.0</td>\n",
       "      <td>25082.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>1669.0</td>\n",
       "      <td>25292.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>1605.0</td>\n",
       "      <td>25200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>1690.0</td>\n",
       "      <td>15576.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         DAY      STATION  2020 Entries  2019 Entries\n",
       "0     MONDAY  86 ST-2 AVE        1045.0       11675.0\n",
       "1    TUESDAY  86 ST-2 AVE        1787.0       23256.0\n",
       "2  WEDNESDAY  86 ST-2 AVE        1903.0       24765.0\n",
       "3   THURSDAY  86 ST-2 AVE        1745.0       25082.0\n",
       "4     FRIDAY  86 ST-2 AVE        1669.0       25292.0\n",
       "5   SATURDAY  86 ST-2 AVE        1605.0       25200.0\n",
       "6     SUNDAY  86 ST-2 AVE        1690.0       15576.0"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "field = \"DAY\"\n",
    "day_order = [\"MONDAY\", \"TUESDAY\", \"WEDNESDAY\", \"THURSDAY\", \"FRIDAY\", \"SATURDAY\", \"SUNDAY\"]\n",
    "UES_sort_df = UES_DOW_df.set_index(field).loc[day_order]\n",
    "UES_sort_df = UES_sort_df.reset_index()\n",
    "UES_sort_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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": [
    "# Plot Penn Sta Graph\n",
    "x_axis = Penn_sort_df[\"DAY\"]\n",
    "D2020_y = Penn_sort_df[\"2020 Entries\"]\n",
    "D2019_y = Penn_sort_df[\"2019 Entries\"]\n",
    "\n",
    "plt.plot(x_axis, D2020_y, marker = \"o\", label = \"2020 Entries\", color = \"red\")\n",
    "plt.plot(x_axis, D2019_y, marker = \"o\", label = \"2019 Entries\", color = \"blue\")\n",
    "plt.title(\"Total Entries at Penn Station by Day of Week\")\n",
    "plt.ylim(0, 55000)\n",
    "plt.xlabel(\"Day of Week\")\n",
    "plt.ylabel(\"Turnstile Entries\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.savefig(\"Resources/DailyEntries_Penn.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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": [
    "# Plot 86th St Graph\n",
    "x_axis = UES_sort_df[\"DAY\"]\n",
    "D2020_y = UES_sort_df[\"2020 Entries\"]\n",
    "D2019_y = UES_sort_df[\"2019 Entries\"]\n",
    "\n",
    "plt.plot(x_axis, D2020_y, marker = \"o\", label = \"2020 Entries\", color = \"red\")\n",
    "plt.plot(x_axis, D2019_y, marker = \"o\", label = \"2019 Entries\", color = \"blue\")\n",
    "plt.title(\"Total Entries at 86th ST/2nd Ave by Day of Week\")\n",
    "plt.ylim(0, 55000)\n",
    "plt.xlabel(\"Day of Week\")\n",
    "plt.ylabel(\"Turnstile Entries\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.savefig(\"Resources/DailyEntries_UES.png\")\n",
    "plt.show()"
   ]
  },
  {
   "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></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>Entries (End)</th>\n",
       "      <th>EXIT (End)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">86 ST-2 AVE</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">Q</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">00-00-00</th>\n",
       "      <th>3/21/20</th>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298678.0</td>\n",
       "      <td>2985259.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/22/20</th>\n",
       "      <td>MONDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5299091.0</td>\n",
       "      <td>2985630.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/23/20</th>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5299674.0</td>\n",
       "      <td>2986159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/24/20</th>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5300321.0</td>\n",
       "      <td>2986668.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/25/20</th>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5300925.0</td>\n",
       "      <td>2987152.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WORLD TRADE CTR</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">ACE23</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">1/6/03</th>\n",
       "      <th>3/23/20</th>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619339.0</td>\n",
       "      <td>306544.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/24/20</th>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619480.0</td>\n",
       "      <td>306703.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/25/20</th>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619611.0</td>\n",
       "      <td>306843.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/26/20</th>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619739.0</td>\n",
       "      <td>306980.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/27/20</th>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619858.0</td>\n",
       "      <td>307132.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1301 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 DAY     TIME     DESC  \\\n",
       "STATION         LINENAME SCP      DATE                                   \n",
       "86 ST-2 AVE     Q        00-00-00 3/21/20     SUNDAY  9:00:00  REGULAR   \n",
       "                                  3/22/20     MONDAY  9:00:00  REGULAR   \n",
       "                                  3/23/20    TUESDAY  9:00:00  REGULAR   \n",
       "                                  3/24/20  WEDNESDAY  9:00:00  REGULAR   \n",
       "                                  3/25/20   THURSDAY  9:00:00  REGULAR   \n",
       "...                                              ...      ...      ...   \n",
       "WORLD TRADE CTR ACE23    1/6/03   3/23/20    TUESDAY  8:00:00  REGULAR   \n",
       "                                  3/24/20  WEDNESDAY  8:00:00  REGULAR   \n",
       "                                  3/25/20   THURSDAY  8:00:00  REGULAR   \n",
       "                                  3/26/20     FRIDAY  8:00:00  REGULAR   \n",
       "                                  3/27/20   SATURDAY  8:00:00  REGULAR   \n",
       "\n",
       "                                           Entries (End)  EXIT (End)  \n",
       "STATION         LINENAME SCP      DATE                                \n",
       "86 ST-2 AVE     Q        00-00-00 3/21/20      5298678.0   2985259.0  \n",
       "                                  3/22/20      5299091.0   2985630.0  \n",
       "                                  3/23/20      5299674.0   2986159.0  \n",
       "                                  3/24/20      5300321.0   2986668.0  \n",
       "                                  3/25/20      5300925.0   2987152.0  \n",
       "...                                                  ...         ...  \n",
       "WORLD TRADE CTR ACE23    1/6/03   3/23/20       619339.0    306544.0  \n",
       "                                  3/24/20       619480.0    306703.0  \n",
       "                                  3/25/20       619611.0    306843.0  \n",
       "                                  3/26/20       619739.0    306980.0  \n",
       "                                  3/27/20       619858.0    307132.0  \n",
       "\n",
       "[1301 rows x 5 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#found the highest cumulative entry counts based on station, line name, turnstile, and date\n",
    "march_2020_datemax = newdf_2020.groupby([\"STATION\", \"LINENAME\", \"SCP\", \"DATE\"]).max()\n",
    "march_2020_datemax = march_2020_datemax.rename(columns = {\"ENTRIES\": \"Entries (End)\", \"EXIT\": \"EXIT (End)\"})\n",
    "march_2020_datemax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>Entries (Start)</th>\n",
       "      <th>EXIT (start)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">86 ST-2 AVE</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">Q</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">00-00-00</th>\n",
       "      <th>3/21/20</th>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298209.0</td>\n",
       "      <td>2984796.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/22/20</th>\n",
       "      <td>MONDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298768.0</td>\n",
       "      <td>2985286.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/23/20</th>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5299164.0</td>\n",
       "      <td>2985661.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/24/20</th>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5299743.0</td>\n",
       "      <td>2986182.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/25/20</th>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5300381.0</td>\n",
       "      <td>2986704.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WORLD TRADE CTR</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">ACE23</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">1/6/03</th>\n",
       "      <th>3/23/20</th>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619257.0</td>\n",
       "      <td>306424.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/24/20</th>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619358.0</td>\n",
       "      <td>306552.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/25/20</th>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619498.0</td>\n",
       "      <td>306714.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/26/20</th>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619627.0</td>\n",
       "      <td>306850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/27/20</th>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619753.0</td>\n",
       "      <td>306990.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1301 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 DAY      TIME     DESC  \\\n",
       "STATION         LINENAME SCP      DATE                                    \n",
       "86 ST-2 AVE     Q        00-00-00 3/21/20     SUNDAY  13:00:00  REGULAR   \n",
       "                                  3/22/20     MONDAY  13:00:00  REGULAR   \n",
       "                                  3/23/20    TUESDAY  13:00:00  REGULAR   \n",
       "                                  3/24/20  WEDNESDAY  13:00:00  REGULAR   \n",
       "                                  3/25/20   THURSDAY  13:00:00  REGULAR   \n",
       "...                                              ...       ...      ...   \n",
       "WORLD TRADE CTR ACE23    1/6/03   3/23/20    TUESDAY   0:00:00  REGULAR   \n",
       "                                  3/24/20  WEDNESDAY   0:00:00  REGULAR   \n",
       "                                  3/25/20   THURSDAY   0:00:00  REGULAR   \n",
       "                                  3/26/20     FRIDAY   0:00:00  REGULAR   \n",
       "                                  3/27/20   SATURDAY   0:00:00  REGULAR   \n",
       "\n",
       "                                           Entries (Start)  EXIT (start)  \n",
       "STATION         LINENAME SCP      DATE                                    \n",
       "86 ST-2 AVE     Q        00-00-00 3/21/20        5298209.0     2984796.0  \n",
       "                                  3/22/20        5298768.0     2985286.0  \n",
       "                                  3/23/20        5299164.0     2985661.0  \n",
       "                                  3/24/20        5299743.0     2986182.0  \n",
       "                                  3/25/20        5300381.0     2986704.0  \n",
       "...                                                    ...           ...  \n",
       "WORLD TRADE CTR ACE23    1/6/03   3/23/20         619257.0      306424.0  \n",
       "                                  3/24/20         619358.0      306552.0  \n",
       "                                  3/25/20         619498.0      306714.0  \n",
       "                                  3/26/20         619627.0      306850.0  \n",
       "                                  3/27/20         619753.0      306990.0  \n",
       "\n",
       "[1301 rows x 5 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#found the lowest cumulative entry counts based on station, line name, turnstile, and date\n",
    "march_2020_datemin = newdf_2020.groupby([\"STATION\", \"LINENAME\", \"SCP\", \"DATE\"]).min()\n",
    "march_2020_datemin = march_2020_datemin.rename(columns = {\"ENTRIES\": \"Entries (Start)\", \"EXIT\": \"EXIT (start)\"})\n",
    "march_2020_datemin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>SCP</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY</th>\n",
       "      <th>TIME_x</th>\n",
       "      <th>DESC_x</th>\n",
       "      <th>Entries (Start)</th>\n",
       "      <th>EXIT (start)</th>\n",
       "      <th>TIME_y</th>\n",
       "      <th>DESC_y</th>\n",
       "      <th>Entries (End)</th>\n",
       "      <th>EXIT (End)</th>\n",
       "      <th>Ride Entry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>3/21/20</td>\n",
       "      <td>SUNDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298209.0</td>\n",
       "      <td>2984796.0</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298678.0</td>\n",
       "      <td>2985259.0</td>\n",
       "      <td>469.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>3/22/20</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5298768.0</td>\n",
       "      <td>2985286.0</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5299091.0</td>\n",
       "      <td>2985630.0</td>\n",
       "      <td>323.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>3/23/20</td>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5299164.0</td>\n",
       "      <td>2985661.0</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5299674.0</td>\n",
       "      <td>2986159.0</td>\n",
       "      <td>510.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>3/24/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5299743.0</td>\n",
       "      <td>2986182.0</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5300321.0</td>\n",
       "      <td>2986668.0</td>\n",
       "      <td>578.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86 ST-2 AVE</td>\n",
       "      <td>Q</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>3/25/20</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5300381.0</td>\n",
       "      <td>2986704.0</td>\n",
       "      <td>9:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>5300925.0</td>\n",
       "      <td>2987152.0</td>\n",
       "      <td>544.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>ACE23</td>\n",
       "      <td>1/6/03</td>\n",
       "      <td>3/23/20</td>\n",
       "      <td>TUESDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619257.0</td>\n",
       "      <td>306424.0</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619339.0</td>\n",
       "      <td>306544.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1297</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>ACE23</td>\n",
       "      <td>1/6/03</td>\n",
       "      <td>3/24/20</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619358.0</td>\n",
       "      <td>306552.0</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619480.0</td>\n",
       "      <td>306703.0</td>\n",
       "      <td>122.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1298</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>ACE23</td>\n",
       "      <td>1/6/03</td>\n",
       "      <td>3/25/20</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619498.0</td>\n",
       "      <td>306714.0</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619611.0</td>\n",
       "      <td>306843.0</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1299</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>ACE23</td>\n",
       "      <td>1/6/03</td>\n",
       "      <td>3/26/20</td>\n",
       "      <td>FRIDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619627.0</td>\n",
       "      <td>306850.0</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619739.0</td>\n",
       "      <td>306980.0</td>\n",
       "      <td>112.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1300</th>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>ACE23</td>\n",
       "      <td>1/6/03</td>\n",
       "      <td>3/27/20</td>\n",
       "      <td>SATURDAY</td>\n",
       "      <td>0:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619753.0</td>\n",
       "      <td>306990.0</td>\n",
       "      <td>8:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>619858.0</td>\n",
       "      <td>307132.0</td>\n",
       "      <td>105.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1301 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              STATION LINENAME       SCP     DATE        DAY    TIME_x  \\\n",
       "0         86 ST-2 AVE        Q  00-00-00  3/21/20     SUNDAY  13:00:00   \n",
       "1         86 ST-2 AVE        Q  00-00-00  3/22/20     MONDAY  13:00:00   \n",
       "2         86 ST-2 AVE        Q  00-00-00  3/23/20    TUESDAY  13:00:00   \n",
       "3         86 ST-2 AVE        Q  00-00-00  3/24/20  WEDNESDAY  13:00:00   \n",
       "4         86 ST-2 AVE        Q  00-00-00  3/25/20   THURSDAY  13:00:00   \n",
       "...               ...      ...       ...      ...        ...       ...   \n",
       "1296  WORLD TRADE CTR    ACE23    1/6/03  3/23/20    TUESDAY   0:00:00   \n",
       "1297  WORLD TRADE CTR    ACE23    1/6/03  3/24/20  WEDNESDAY   0:00:00   \n",
       "1298  WORLD TRADE CTR    ACE23    1/6/03  3/25/20   THURSDAY   0:00:00   \n",
       "1299  WORLD TRADE CTR    ACE23    1/6/03  3/26/20     FRIDAY   0:00:00   \n",
       "1300  WORLD TRADE CTR    ACE23    1/6/03  3/27/20   SATURDAY   0:00:00   \n",
       "\n",
       "       DESC_x  Entries (Start)  EXIT (start)   TIME_y   DESC_y  Entries (End)  \\\n",
       "0     REGULAR        5298209.0     2984796.0  9:00:00  REGULAR      5298678.0   \n",
       "1     REGULAR        5298768.0     2985286.0  9:00:00  REGULAR      5299091.0   \n",
       "2     REGULAR        5299164.0     2985661.0  9:00:00  REGULAR      5299674.0   \n",
       "3     REGULAR        5299743.0     2986182.0  9:00:00  REGULAR      5300321.0   \n",
       "4     REGULAR        5300381.0     2986704.0  9:00:00  REGULAR      5300925.0   \n",
       "...       ...              ...           ...      ...      ...            ...   \n",
       "1296  REGULAR         619257.0      306424.0  8:00:00  REGULAR       619339.0   \n",
       "1297  REGULAR         619358.0      306552.0  8:00:00  REGULAR       619480.0   \n",
       "1298  REGULAR         619498.0      306714.0  8:00:00  REGULAR       619611.0   \n",
       "1299  REGULAR         619627.0      306850.0  8:00:00  REGULAR       619739.0   \n",
       "1300  REGULAR         619753.0      306990.0  8:00:00  REGULAR       619858.0   \n",
       "\n",
       "      EXIT (End)  Ride Entry  \n",
       "0      2985259.0       469.0  \n",
       "1      2985630.0       323.0  \n",
       "2      2986159.0       510.0  \n",
       "3      2986668.0       578.0  \n",
       "4      2987152.0       544.0  \n",
       "...          ...         ...  \n",
       "1296    306544.0        82.0  \n",
       "1297    306703.0       122.0  \n",
       "1298    306843.0       113.0  \n",
       "1299    306980.0       112.0  \n",
       "1300    307132.0       105.0  \n",
       "\n",
       "[1301 rows x 14 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#merged 2 DFs into a new DF with both highest and lowest cumulative entries\n",
    "march_2020_datemerge = pd.merge(march_2020_datemin, march_2020_datemax, on = [\"STATION\", \"LINENAME\", \"SCP\", \"DATE\", \"DAY\"], how = \"left\")\n",
    "march_2020_datemerge = march_2020_datemerge.reset_index()\n",
    "march_2020_datemerge[\"Ride Entry\"] = march_2020_datemerge[\"Entries (End)\"] - march_2020_datemerge[\"Entries (Start)\"]\n",
    "march_2020_datemerge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7, 2)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\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>DATE</th>\n",
       "      <th>Ride Entry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>31840.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3/22/20</td>\n",
       "      <td>21217.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3/23/20</td>\n",
       "      <td>31746.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3/24/20</td>\n",
       "      <td>33869.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3/25/20</td>\n",
       "      <td>31192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3/26/20</td>\n",
       "      <td>30599.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>27682.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      DATE  Ride Entry\n",
       "0  3/21/20     31840.0\n",
       "1  3/22/20     21217.0\n",
       "2  3/23/20     31746.0\n",
       "3  3/24/20     33869.0\n",
       "4  3/25/20     31192.0\n",
       "5  3/26/20     30599.0\n",
       "6  3/27/20     27682.0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#found the total entries based on dates\n",
    "date_change = march_2020_datemerge.groupby([\"DATE\"]).sum()[\"Ride Entry\"]\n",
    "march_date_pd = pd.DataFrame(date_change)\n",
    "march_date_pd = march_date_pd.reset_index()\n",
    "print(march_date_pd.shape)\n",
    "march_date_pd.head(10)"
   ]
  },
  {
   "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>DATE</th>\n",
       "      <th>CASE_COUNT</th>\n",
       "      <th>HOSPITALIZED_COUNT</th>\n",
       "      <th>DEATH_COUNT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>2,638</td>\n",
       "      <td>701</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>3/22/20</td>\n",
       "      <td>2,580</td>\n",
       "      <td>725</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>3/23/20</td>\n",
       "      <td>3,572</td>\n",
       "      <td>1,042</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>3/24/20</td>\n",
       "      <td>4,506</td>\n",
       "      <td>1,167</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>3/25/20</td>\n",
       "      <td>4,874</td>\n",
       "      <td>1,312</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>3/26/20</td>\n",
       "      <td>5,051</td>\n",
       "      <td>1,454</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>5,121</td>\n",
       "      <td>1,402</td>\n",
       "      <td>218</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       DATE CASE_COUNT HOSPITALIZED_COUNT  DEATH_COUNT\n",
       "21  3/21/20      2,638                701           44\n",
       "22  3/22/20      2,580                725           50\n",
       "23  3/23/20      3,572              1,042           82\n",
       "24  3/24/20      4,506              1,167           95\n",
       "25  3/25/20      4,874              1,312          123\n",
       "26  3/26/20      5,051              1,454          190\n",
       "27  3/27/20      5,121              1,402          218"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#located the last week of March 2020 and extracted the data\n",
    "date_2020 = covid_count.loc[(covid_count[\"DATE_OF_INTEREST\"] == \"3/21/20\") | \n",
    "                            (covid_count[\"DATE_OF_INTEREST\"] == \"3/22/20\") | \n",
    "                            (covid_count[\"DATE_OF_INTEREST\"] == \"3/23/20\") | \n",
    "                            (covid_count[\"DATE_OF_INTEREST\"] == \"3/24/20\") | \n",
    "                            (covid_count[\"DATE_OF_INTEREST\"] == \"3/25/20\") | \n",
    "                            (covid_count[\"DATE_OF_INTEREST\"] == \"3/26/20\") | \n",
    "                            (covid_count[\"DATE_OF_INTEREST\"] == \"3/27/20\")]\n",
    "\n",
    "date_2020 = date_2020.rename(columns = {\"DATE_OF_INTEREST\": \"DATE\"})\n",
    "date_2020"
   ]
  },
  {
   "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>DATE</th>\n",
       "      <th>Ride Entry</th>\n",
       "      <th>CASE_COUNT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3/21/20</td>\n",
       "      <td>31840.0</td>\n",
       "      <td>2,638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3/22/20</td>\n",
       "      <td>21217.0</td>\n",
       "      <td>2,580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3/23/20</td>\n",
       "      <td>31746.0</td>\n",
       "      <td>3,572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3/24/20</td>\n",
       "      <td>33869.0</td>\n",
       "      <td>4,506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3/25/20</td>\n",
       "      <td>31192.0</td>\n",
       "      <td>4,874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3/26/20</td>\n",
       "      <td>30599.0</td>\n",
       "      <td>5,051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3/27/20</td>\n",
       "      <td>27682.0</td>\n",
       "      <td>5,121</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      DATE  Ride Entry CASE_COUNT\n",
       "0  3/21/20     31840.0      2,638\n",
       "1  3/22/20     21217.0      2,580\n",
       "2  3/23/20     31746.0      3,572\n",
       "3  3/24/20     33869.0      4,506\n",
       "4  3/25/20     31192.0      4,874\n",
       "5  3/26/20     30599.0      5,051\n",
       "6  3/27/20     27682.0      5,121"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#merged 2 DFs into a new DF with station names, rider entries, and covid case rate\n",
    "march_chart_pd = pd.merge(march_date_pd, date_2020, on = \"DATE\", how = \"left\")\n",
    "march_chart_pd = march_chart_pd.drop([\"HOSPITALIZED_COUNT\", \"DEATH_COUNT\"], axis=1)\n",
    "march_chart_pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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": [
    "#created a line graph\n",
    "x_axis = march_chart_pd[\"DATE\"]\n",
    "case_y = march_chart_pd[\"CASE_COUNT\"]\n",
    "\n",
    "plt.plot(x_axis, case_y, marker = \"o\", label = \"COVID cases\", color = \"red\")\n",
    "plt.title(\"COVID case in March 2020\")\n",
    "plt.xlabel(\"Date\")\n",
    "plt.savefig(\"Resources/CovidCases.png\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "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": [
    "ride_y = march_chart_pd[\"Ride Entry\"]\n",
    "plt.plot(x_axis, ride_y, marker = \"o\", label = \"MTA ridership\", color = \"blue\")\n",
    "plt.title(\"MTA Ridership in March 2020\")\n",
    "plt.ylim(15000, 35000)\n",
    "plt.xlabel(\"Date\")\n",
    "plt.savefig(\"Resources/DailyRidership2020.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}