PyCitySchools_Challenge_testing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "264664ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\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>Student ID</th>\n",
       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
       "      <th>grade</th>\n",
       "      <th>school_name</th>\n",
       "      <th>reading_score</th>\n",
       "      <th>math_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Paul Bradley</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>66</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>67</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>97</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Bryan Miranda</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Sheena Carter</td>\n",
       "      <td>F</td>\n",
       "      <td>11th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>82</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Nicole Baker</td>\n",
       "      <td>F</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>96</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Michael Roth</td>\n",
       "      <td>M</td>\n",
       "      <td>10th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>95</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Matthew Greene</td>\n",
       "      <td>M</td>\n",
       "      <td>10th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>96</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Student ID     student_name gender grade        school_name  reading_score  \\\n",
       "0           0     Paul Bradley      M   9th  Huang High School             66   \n",
       "1           1     Victor Smith      M  12th  Huang High School             94   \n",
       "2           2  Kevin Rodriguez      M  12th  Huang High School             90   \n",
       "3           3    Richard Scott      M  12th  Huang High School             67   \n",
       "4           4       Bonnie Ray      F   9th  Huang High School             97   \n",
       "5           5    Bryan Miranda      M   9th  Huang High School             94   \n",
       "6           6    Sheena Carter      F  11th  Huang High School             82   \n",
       "7           7     Nicole Baker      F  12th  Huang High School             96   \n",
       "8           8     Michael Roth      M  10th  Huang High School             95   \n",
       "9           9   Matthew Greene      M  10th  Huang High School             96   \n",
       "\n",
       "   math_score  \n",
       "0          79  \n",
       "1          61  \n",
       "2          60  \n",
       "3          58  \n",
       "4          84  \n",
       "5          94  \n",
       "6          80  \n",
       "7          69  \n",
       "8          87  \n",
       "9          84  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dependencies and Setup\n",
    "import pandas as pd\n",
    "\n",
    "# File to Load (Remember to change the path if needed.)\n",
    "school_data_to_load = \"Resources/schools_complete.csv\"\n",
    "student_data_to_load = \"Resources/students_complete.csv\"\n",
    "\n",
    "# Read the School Data and Student Data and store into a Pandas DataFrame\n",
    "school_data_df = pd.read_csv(school_data_to_load)\n",
    "student_data_df = pd.read_csv(student_data_to_load)\n",
    "\n",
    "# Cleaning Student Names and Replacing Substrings in a Python String\n",
    "# Add each prefix and suffix to remove to a list.\n",
    "prefixes_suffixes = [\"Dr. \", \"Mr. \",\"Ms. \", \"Mrs. \", \"Miss \", \" MD\", \" DDS\", \" DVM\", \" PhD\"]\n",
    "\n",
    "# Iterate through the words in the \"prefixes_suffixes\" list and replace them with an empty space, \"\".\n",
    "for word in prefixes_suffixes:\n",
    "    student_data_df[\"student_name\"] = student_data_df[\"student_name\"].str.replace(word,\"\")\n",
    "\n",
    "# Check names.\n",
    "student_data_df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "776a6ba3",
   "metadata": {},
   "source": [
    "## Deliverable 1: Replace the reading and math scores.\n",
    "\n",
    "### Replace the 9th grade reading and math scores at Thomas High School with NaN."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4a9f2da9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install numpy using conda install numpy or pip install numpy. \n",
    "# Step 1. Import numpy as np.\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0d6ee83d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 2. Use the loc method on the student_data_df to select all the reading scores from the 9th grade at Thomas High School and replace them with NaN.\n",
    "student_data_df.loc[]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6f621ae7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#  Step 3. Refactor the code in Step 2 to replace the math scores with NaN.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d37f6637",
   "metadata": {},
   "outputs": [],
   "source": [
    "#  Step 4. Check the student data for NaN's. \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d2fb873",
   "metadata": {},
   "source": [
    "## Deliverable 2 : Repeat the school district analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d86dd447",
   "metadata": {},
   "source": [
    "### District Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "164fb200",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>Student ID</th>\n",
       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
       "      <th>grade</th>\n",
       "      <th>school_name</th>\n",
       "      <th>reading_score</th>\n",
       "      <th>math_score</th>\n",
       "      <th>School ID</th>\n",
       "      <th>type</th>\n",
       "      <th>size</th>\n",
       "      <th>budget</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Paul Bradley</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>66</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>67</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>97</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Student ID     student_name gender grade        school_name  reading_score  \\\n",
       "0           0     Paul Bradley      M   9th  Huang High School             66   \n",
       "1           1     Victor Smith      M  12th  Huang High School             94   \n",
       "2           2  Kevin Rodriguez      M  12th  Huang High School             90   \n",
       "3           3    Richard Scott      M  12th  Huang High School             67   \n",
       "4           4       Bonnie Ray      F   9th  Huang High School             97   \n",
       "\n",
       "   math_score  School ID      type  size   budget  \n",
       "0          79          0  District  2917  1910635  \n",
       "1          61          0  District  2917  1910635  \n",
       "2          60          0  District  2917  1910635  \n",
       "3          58          0  District  2917  1910635  \n",
       "4          84          0  District  2917  1910635  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combine the data into a single dataset\n",
    "school_data_complete_df = pd.merge(student_data_df, school_data_df, how=\"left\", on=[\"school_name\", \"school_name\"])\n",
    "school_data_complete_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5e096b7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the Totals (Schools and Students)\n",
    "school_count = len(school_data_complete_df[\"school_name\"].unique())\n",
    "student_count = school_data_complete_df[\"Student ID\"].count()\n",
    "\n",
    "# Calculate the Total Budget\n",
    "total_budget = school_data_df[\"budget\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ecfbbd93",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the Average Scores using the \"clean_student_data\".\n",
    "average_reading_score = school_data_complete_df[\"reading_score\"].mean()\n",
    "average_math_score = school_data_complete_df[\"math_score\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b2460177",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 1. Get the number of students that are in ninth grade at Thomas High School.\n",
    "# These students have no grades. \n",
    "\n",
    "\n",
    "# Get the total student count \n",
    "student_count = school_data_complete_df[\"Student ID\"].count()\n",
    "\n",
    "\n",
    "# Step 2. Subtract the number of students that are in ninth grade at \n",
    "# Thomas High School from the total student count to get the new total student count.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fd0cb969",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the passing rates using the \"clean_student_data\".\n",
    "passing_math_count = school_data_complete_df[(school_data_complete_df[\"math_score\"] >= 70)].count()[\"student_name\"]\n",
    "passing_reading_count = school_data_complete_df[(school_data_complete_df[\"reading_score\"] >= 70)].count()[\"student_name\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2f920ed0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 3. Calculate the passing percentages with the new total student count.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "61cc6a94",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the students who passed both reading and math.\n",
    "passing_math_reading = school_data_complete_df[(school_data_complete_df[\"math_score\"] >= 70)\n",
    "                                               & (school_data_complete_df[\"reading_score\"] >= 70)]\n",
    "\n",
    "# Calculate the number of students that passed both reading and math.\n",
    "overall_passing_math_reading_count = passing_math_reading[\"student_name\"].count()\n",
    "\n",
    "\n",
    "# Step 4.Calculate the overall passing percentage with new total student count.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "03244d00",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a DataFrame\n",
    "district_summary_df = pd.DataFrame(\n",
    "          [{\"Total Schools\": school_count, \n",
    "          \"Total Students\": student_count, \n",
    "          \"Total Budget\": total_budget,\n",
    "          \"Average Math Score\": average_math_score, \n",
    "          \"Average Reading Score\": average_reading_score,\n",
    "          \"% Passing Math\": passing_math_percentage,\n",
    "         \"% Passing Reading\": passing_reading_percentage,\n",
    "        \"% Overall Passing\": overall_passing_percentage}])\n",
    "\n",
    "\n",
    "\n",
    "# Format the \"Total Students\" to have the comma for a thousands separator.\n",
    "district_summary_df[\"Total Students\"] = district_summary_df[\"Total Students\"].map(\"{:,}\".format)\n",
    "# Format the \"Total Budget\" to have the comma for a thousands separator, a decimal separator and a \"$\".\n",
    "district_summary_df[\"Total Budget\"] = district_summary_df[\"Total Budget\"].map(\"${:,.2f}\".format)\n",
    "# Format the columns.\n",
    "district_summary_df[\"Average Math Score\"] = district_summary_df[\"Average Math Score\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"Average Reading Score\"] = district_summary_df[\"Average Reading Score\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"% Passing Math\"] = district_summary_df[\"% Passing Math\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"% Passing Reading\"] = district_summary_df[\"% Passing Reading\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"% Overall Passing\"] = district_summary_df[\"% Overall Passing\"].map(\"{:.1f}\".format)\n",
    "\n",
    "# Display the data frame\n",
    "district_summary_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99030f99",
   "metadata": {},
   "source": [
    "##  School Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b4b7d257",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Determine the School Type\n",
    "per_school_types = school_data_df.set_index([\"school_name\"])[\"type\"]\n",
    "\n",
    "# Calculate the total student count.\n",
    "per_school_counts = school_data_complete_df[\"school_name\"].value_counts()\n",
    "\n",
    "# Calculate the total school budget and per capita spending\n",
    "per_school_budget = school_data_complete_df.groupby([\"school_name\"]).mean()[\"budget\"]\n",
    "# Calculate the per capita spending.\n",
    "per_school_capita = per_school_budget / per_school_counts\n",
    "\n",
    "# Calculate the average test scores.\n",
    "per_school_math = school_data_complete_df.groupby([\"school_name\"]).mean()[\"math_score\"]\n",
    "per_school_reading = school_data_complete_df.groupby([\"school_name\"]).mean()[\"reading_score\"]\n",
    "\n",
    "# Calculate the passing scores by creating a filtered DataFrame.\n",
    "per_school_passing_math = school_data_complete_df[(school_data_complete_df[\"math_score\"] >= 70)]\n",
    "per_school_passing_reading = school_data_complete_df[(school_data_complete_df[\"reading_score\"] >= 70)]\n",
    "\n",
    "# Calculate the number of students passing math and passing reading by school.\n",
    "per_school_passing_math = per_school_passing_math.groupby([\"school_name\"]).count()[\"student_name\"]\n",
    "per_school_passing_reading = per_school_passing_reading.groupby([\"school_name\"]).count()[\"student_name\"]\n",
    "\n",
    "# Calculate the percentage of passing math and reading scores per school.\n",
    "per_school_passing_math = per_school_passing_math / per_school_counts * 100\n",
    "per_school_passing_reading = per_school_passing_reading / per_school_counts * 100\n",
    "\n",
    "# Calculate the students who passed both reading and math.\n",
    "per_passing_math_reading = school_data_complete_df[(school_data_complete_df[\"reading_score\"] >= 70)\n",
    "                                               & (school_data_complete_df[\"math_score\"] >= 70)]\n",
    "\n",
    "# Calculate the number of students passing math and passing reading by school.\n",
    "per_passing_math_reading = per_passing_math_reading.groupby([\"school_name\"]).count()[\"student_name\"]\n",
    "\n",
    "# Calculate the percentage of passing math and reading scores per school.\n",
    "per_overall_passing_percentage = per_passing_math_reading / per_school_counts * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b04971c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the DataFrame\n",
    "per_school_summary_df = pd.DataFrame({\n",
    "    \"School Type\": per_school_types,\n",
    "    \"Total Students\": per_school_counts,\n",
    "    \"Total School Budget\": per_school_budget,\n",
    "    \"Per Student Budget\": per_school_capita,\n",
    "    \"Average Math Score\": per_school_math,\n",
    "    \"Average Reading Score\": per_school_reading,\n",
    "    \"% Passing Math\": per_school_passing_math,\n",
    "    \"% Passing Reading\": per_school_passing_reading,\n",
    "    \"% Overall Passing\": per_overall_passing_percentage})\n",
    "\n",
    "\n",
    "# per_school_summary_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "da6f5d91",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format the Total School Budget and the Per Student Budget\n",
    "per_school_summary_df[\"Total School Budget\"] = per_school_summary_df[\"Total School Budget\"].map(\"${:,.2f}\".format)\n",
    "per_school_summary_df[\"Per Student Budget\"] = per_school_summary_df[\"Per Student Budget\"].map(\"${:,.2f}\".format)\n",
    "\n",
    "# Display the data frame\n",
    "per_school_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "53727240",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 5.  Get the number of 10th-12th graders from Thomas High School (THS).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "bc82f67d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 6. Get all the students passing math from THS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e17926e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 7. Get all the students passing reading from THS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "bba0f328",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 8. Get all the students passing math and reading from THS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "453916f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 9. Calculate the percentage of 10th-12th grade students passing math from Thomas High School. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d619c665",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 10. Calculate the percentage of 10th-12th grade students passing reading from Thomas High School.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "16ccfc37",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 11. Calculate the overall passing percentage of 10th-12th grade from Thomas High School. \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b783da88",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 12. Replace the passing math percent for Thomas High School in the per_school_summary_df.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f0256548",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 13. Replace the passing reading percentage for Thomas High School in the per_school_summary_df.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "156b13e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 14. Replace the overall passing percentage for Thomas High School in the per_school_summary_df.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0290a742",
   "metadata": {},
   "outputs": [],
   "source": [
    "# per_school_summary_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cda6466",
   "metadata": {},
   "source": [
    "## High and Low Performing Schools "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "109bbaf3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Sort and show top five schools.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cbfffed1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sort and show top five schools.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08f6b224",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Math and Reading Scores by Grade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e4324e58",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a Series of scores by grade levels using conditionals.\n",
    "\n",
    "\n",
    "# Group each school Series by the school name for the average math score.\n",
    "\n",
    "\n",
    "# Group each school Series by the school name for the average reading score.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "1b98ffea",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine each Series for average math scores by school into single data frame.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "68178c9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine each Series for average reading scores by school into single data frame.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "c2b0e94f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format each grade column.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a2feafed",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove the index.\n",
    "\n",
    "\n",
    "# Display the data frame\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "8428c1a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Remove the index.\n",
    "\n",
    "\n",
    "# Display the data frame\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fa78f5e",
   "metadata": {},
   "source": [
    "## Scores by School Spending"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f8263b10",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the spending bins and group names.\n",
    "\n",
    "\n",
    "# Categorize spending based on the bins.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "2507aaa4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "7e650983",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the DataFrame\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "316acb15",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format the DataFrame \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01bbd9e5",
   "metadata": {},
   "source": [
    "## Scores by School Size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "6f9e7089",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the bins.\n",
    "\n",
    "# Categorize spending based on the bins.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "1fd0144e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "f2b74a57",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Assemble into DataFrame. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "f8226f06",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format the DataFrame  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4dd0aec",
   "metadata": {},
   "source": [
    "## Scores by School Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c04d8348",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "10af0eaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assemble into DataFrame. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "9a00b471",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Format the DataFrame \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87e974d0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d43a04a3",
   "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>Student ID</th>\n",
       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
       "      <th>grade</th>\n",
       "      <th>school_name</th>\n",
       "      <th>reading_score</th>\n",
       "      <th>math_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Paul Bradley</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>66</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>67</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>97</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Bryan Miranda</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Sheena Carter</td>\n",
       "      <td>F</td>\n",
       "      <td>11th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>82</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Nicole Baker</td>\n",
       "      <td>F</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>96</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Michael Roth</td>\n",
       "      <td>M</td>\n",
       "      <td>10th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>95</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Matthew Greene</td>\n",
       "      <td>M</td>\n",
       "      <td>10th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>96</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Student ID     student_name gender grade        school_name  reading_score  \\\n",
       "0           0     Paul Bradley      M   9th  Huang High School             66   \n",
       "1           1     Victor Smith      M  12th  Huang High School             94   \n",
       "2           2  Kevin Rodriguez      M  12th  Huang High School             90   \n",
       "3           3    Richard Scott      M  12th  Huang High School             67   \n",
       "4           4       Bonnie Ray      F   9th  Huang High School             97   \n",
       "5           5    Bryan Miranda      M   9th  Huang High School             94   \n",
       "6           6    Sheena Carter      F  11th  Huang High School             82   \n",
       "7           7     Nicole Baker      F  12th  Huang High School             96   \n",
       "8           8     Michael Roth      M  10th  Huang High School             95   \n",
       "9           9   Matthew Greene      M  10th  Huang High School             96   \n",
       "\n",
       "   math_score  \n",
       "0          79  \n",
       "1          61  \n",
       "2          60  \n",
       "3          58  \n",
       "4          84  \n",
       "5          94  \n",
       "6          80  \n",
       "7          69  \n",
       "8          87  \n",
       "9          84  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dependencies and Setup\n",
    "import pandas as pd\n",
    "\n",
    "# File to Load (Remember to change the path if needed.)\n",
    "school_data_to_load = \"Resources/schools_complete.csv\"\n",
    "student_data_to_load = \"Resources/students_complete.csv\"\n",
    "\n",
    "# Read the School Data and Student Data and store into a Pandas DataFrame\n",
    "school_data_df = pd.read_csv(school_data_to_load)\n",
    "student_data_df = pd.read_csv(student_data_to_load)\n",
    "\n",
    "# Cleaning Student Names and Replacing Substrings in a Python String\n",
    "# Add each prefix and suffix to remove to a list.\n",
    "prefixes_suffixes = [\"Dr. \", \"Mr. \",\"Ms. \", \"Mrs. \", \"Miss \", \" MD\", \" DDS\", \" DVM\", \" PhD\"]\n",
    "\n",
    "# Iterate through the words in the \"prefixes_suffixes\" list and replace them with an empty space, \"\".\n",
    "for word in prefixes_suffixes:\n",
    "    student_data_df[\"student_name\"] = student_data_df[\"student_name\"].str.replace(word,\"\")\n",
    "\n",
    "# Check names.\n",
    "student_data_df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82a4f362",
   "metadata": {},
   "source": [
    "## Deliverable 1: Replace the reading and math scores.\n",
    "\n",
    "### Replace the 9th grade reading and math scores at Thomas High School with NaN."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "065a9110",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install numpy using conda install numpy or pip install numpy. \n",
    "# Step 1. Import numpy as np.\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "645562e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 2. Use the loc method on the student_data_df to select all the reading scores from the 9th grade at Thomas High School and replace them with NaN.\n",
    "student_data_df.loc[]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "492fedab",
   "metadata": {},
   "outputs": [],
   "source": [
    "#  Step 3. Refactor the code in Step 2 to replace the math scores with NaN.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c1849ba6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#  Step 4. Check the student data for NaN's. \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5597cdc",
   "metadata": {},
   "source": [
    "## Deliverable 2 : Repeat the school district analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e74eb1c0",
   "metadata": {},
   "source": [
    "### District Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5a496df7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
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       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>M</td>\n",
       "      <td>9th</td>\n",
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       "      <td>66</td>\n",
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       "      <td>2917</td>\n",
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       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
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       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>67</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>97</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Student ID     student_name gender grade        school_name  reading_score  \\\n",
       "0           0     Paul Bradley      M   9th  Huang High School             66   \n",
       "1           1     Victor Smith      M  12th  Huang High School             94   \n",
       "2           2  Kevin Rodriguez      M  12th  Huang High School             90   \n",
       "3           3    Richard Scott      M  12th  Huang High School             67   \n",
       "4           4       Bonnie Ray      F   9th  Huang High School             97   \n",
       "\n",
       "   math_score  School ID      type  size   budget  \n",
       "0          79          0  District  2917  1910635  \n",
       "1          61          0  District  2917  1910635  \n",
       "2          60          0  District  2917  1910635  \n",
       "3          58          0  District  2917  1910635  \n",
       "4          84          0  District  2917  1910635  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combine the data into a single dataset\n",
    "school_data_complete_df = pd.merge(student_data_df, school_data_df, how=\"left\", on=[\"school_name\", \"school_name\"])\n",
    "school_data_complete_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "62c851e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the Totals (Schools and Students)\n",
    "school_count = len(school_data_complete_df[\"school_name\"].unique())\n",
    "student_count = school_data_complete_df[\"Student ID\"].count()\n",
    "\n",
    "# Calculate the Total Budget\n",
    "total_budget = school_data_df[\"budget\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "62c57bd8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the Average Scores using the \"clean_student_data\".\n",
    "average_reading_score = school_data_complete_df[\"reading_score\"].mean()\n",
    "average_math_score = school_data_complete_df[\"math_score\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5663d1c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 1. Get the number of students that are in ninth grade at Thomas High School.\n",
    "# These students have no grades. \n",
    "\n",
    "\n",
    "# Get the total student count \n",
    "student_count = school_data_complete_df[\"Student ID\"].count()\n",
    "\n",
    "\n",
    "# Step 2. Subtract the number of students that are in ninth grade at \n",
    "# Thomas High School from the total student count to get the new total student count.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6255d77e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the passing rates using the \"clean_student_data\".\n",
    "passing_math_count = school_data_complete_df[(school_data_complete_df[\"math_score\"] >= 70)].count()[\"student_name\"]\n",
    "passing_reading_count = school_data_complete_df[(school_data_complete_df[\"reading_score\"] >= 70)].count()[\"student_name\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2ad16a91",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 3. Calculate the passing percentages with the new total student count.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ea1dc20d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the students who passed both reading and math.\n",
    "passing_math_reading = school_data_complete_df[(school_data_complete_df[\"math_score\"] >= 70)\n",
    "                                               & (school_data_complete_df[\"reading_score\"] >= 70)]\n",
    "\n",
    "# Calculate the number of students that passed both reading and math.\n",
    "overall_passing_math_reading_count = passing_math_reading[\"student_name\"].count()\n",
    "\n",
    "\n",
    "# Step 4.Calculate the overall passing percentage with new total student count.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "12f3adec",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a DataFrame\n",
    "district_summary_df = pd.DataFrame(\n",
    "          [{\"Total Schools\": school_count, \n",
    "          \"Total Students\": student_count, \n",
    "          \"Total Budget\": total_budget,\n",
    "          \"Average Math Score\": average_math_score, \n",
    "          \"Average Reading Score\": average_reading_score,\n",
    "          \"% Passing Math\": passing_math_percentage,\n",
    "         \"% Passing Reading\": passing_reading_percentage,\n",
    "        \"% Overall Passing\": overall_passing_percentage}])\n",
    "\n",
    "\n",
    "\n",
    "# Format the \"Total Students\" to have the comma for a thousands separator.\n",
    "district_summary_df[\"Total Students\"] = district_summary_df[\"Total Students\"].map(\"{:,}\".format)\n",
    "# Format the \"Total Budget\" to have the comma for a thousands separator, a decimal separator and a \"$\".\n",
    "district_summary_df[\"Total Budget\"] = district_summary_df[\"Total Budget\"].map(\"${:,.2f}\".format)\n",
    "# Format the columns.\n",
    "district_summary_df[\"Average Math Score\"] = district_summary_df[\"Average Math Score\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"Average Reading Score\"] = district_summary_df[\"Average Reading Score\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"% Passing Math\"] = district_summary_df[\"% Passing Math\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"% Passing Reading\"] = district_summary_df[\"% Passing Reading\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"% Overall Passing\"] = district_summary_df[\"% Overall Passing\"].map(\"{:.1f}\".format)\n",
    "\n",
    "# Display the data frame\n",
    "district_summary_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9e8db62",
   "metadata": {},
   "source": [
    "##  School Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c3427c5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Determine the School Type\n",
    "per_school_types = school_data_df.set_index([\"school_name\"])[\"type\"]\n",
    "\n",
    "# Calculate the total student count.\n",
    "per_school_counts = school_data_complete_df[\"school_name\"].value_counts()\n",
    "\n",
    "# Calculate the total school budget and per capita spending\n",
    "per_school_budget = school_data_complete_df.groupby([\"school_name\"]).mean()[\"budget\"]\n",
    "# Calculate the per capita spending.\n",
    "per_school_capita = per_school_budget / per_school_counts\n",
    "\n",
    "# Calculate the average test scores.\n",
    "per_school_math = school_data_complete_df.groupby([\"school_name\"]).mean()[\"math_score\"]\n",
    "per_school_reading = school_data_complete_df.groupby([\"school_name\"]).mean()[\"reading_score\"]\n",
    "\n",
    "# Calculate the passing scores by creating a filtered DataFrame.\n",
    "per_school_passing_math = school_data_complete_df[(school_data_complete_df[\"math_score\"] >= 70)]\n",
    "per_school_passing_reading = school_data_complete_df[(school_data_complete_df[\"reading_score\"] >= 70)]\n",
    "\n",
    "# Calculate the number of students passing math and passing reading by school.\n",
    "per_school_passing_math = per_school_passing_math.groupby([\"school_name\"]).count()[\"student_name\"]\n",
    "per_school_passing_reading = per_school_passing_reading.groupby([\"school_name\"]).count()[\"student_name\"]\n",
    "\n",
    "# Calculate the percentage of passing math and reading scores per school.\n",
    "per_school_passing_math = per_school_passing_math / per_school_counts * 100\n",
    "per_school_passing_reading = per_school_passing_reading / per_school_counts * 100\n",
    "\n",
    "# Calculate the students who passed both reading and math.\n",
    "per_passing_math_reading = school_data_complete_df[(school_data_complete_df[\"reading_score\"] >= 70)\n",
    "                                               & (school_data_complete_df[\"math_score\"] >= 70)]\n",
    "\n",
    "# Calculate the number of students passing math and passing reading by school.\n",
    "per_passing_math_reading = per_passing_math_reading.groupby([\"school_name\"]).count()[\"student_name\"]\n",
    "\n",
    "# Calculate the percentage of passing math and reading scores per school.\n",
    "per_overall_passing_percentage = per_passing_math_reading / per_school_counts * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a62e9d89",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the DataFrame\n",
    "per_school_summary_df = pd.DataFrame({\n",
    "    \"School Type\": per_school_types,\n",
    "    \"Total Students\": per_school_counts,\n",
    "    \"Total School Budget\": per_school_budget,\n",
    "    \"Per Student Budget\": per_school_capita,\n",
    "    \"Average Math Score\": per_school_math,\n",
    "    \"Average Reading Score\": per_school_reading,\n",
    "    \"% Passing Math\": per_school_passing_math,\n",
    "    \"% Passing Reading\": per_school_passing_reading,\n",
    "    \"% Overall Passing\": per_overall_passing_percentage})\n",
    "\n",
    "\n",
    "# per_school_summary_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "294a1f30",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format the Total School Budget and the Per Student Budget\n",
    "per_school_summary_df[\"Total School Budget\"] = per_school_summary_df[\"Total School Budget\"].map(\"${:,.2f}\".format)\n",
    "per_school_summary_df[\"Per Student Budget\"] = per_school_summary_df[\"Per Student Budget\"].map(\"${:,.2f}\".format)\n",
    "\n",
    "# Display the data frame\n",
    "per_school_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d0ce136e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 5.  Get the number of 10th-12th graders from Thomas High School (THS).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d209b885",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 6. Get all the students passing math from THS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b7fe2851",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 7. Get all the students passing reading from THS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "30c3999d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 8. Get all the students passing math and reading from THS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "177588a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 9. Calculate the percentage of 10th-12th grade students passing math from Thomas High School. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ef5a8282",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 10. Calculate the percentage of 10th-12th grade students passing reading from Thomas High School.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d50914e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 11. Calculate the overall passing percentage of 10th-12th grade from Thomas High School. \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "5a291f09",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 12. Replace the passing math percent for Thomas High School in the per_school_summary_df.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7f92cb30",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 13. Replace the passing reading percentage for Thomas High School in the per_school_summary_df.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ed0fb3c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 14. Replace the overall passing percentage for Thomas High School in the per_school_summary_df.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e95a442d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# per_school_summary_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd297950",
   "metadata": {},
   "source": [
    "## High and Low Performing Schools "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "82efa637",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Sort and show top five schools.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "2f44982c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sort and show top five schools.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaafb5b2",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Math and Reading Scores by Grade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "0568fbea",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a Series of scores by grade levels using conditionals.\n",
    "\n",
    "\n",
    "# Group each school Series by the school name for the average math score.\n",
    "\n",
    "\n",
    "# Group each school Series by the school name for the average reading score.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e844787b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine each Series for average math scores by school into single data frame.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fe5565b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine each Series for average reading scores by school into single data frame.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "3367843c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format each grade column.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "14c37a4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove the index.\n",
    "\n",
    "\n",
    "# Display the data frame\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "8934ed4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Remove the index.\n",
    "\n",
    "\n",
    "# Display the data frame\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ce4deb8",
   "metadata": {},
   "source": [
    "## Scores by School Spending"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d5492eca",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the spending bins and group names.\n",
    "\n",
    "\n",
    "# Categorize spending based on the bins.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "062b3613",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "ec35a3d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the DataFrame\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "122dfa60",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format the DataFrame \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d8a41c5",
   "metadata": {},
   "source": [
    "## Scores by School Size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "54567f56",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the bins.\n",
    "\n",
    "# Categorize spending based on the bins.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "0943f797",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "5687feec",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Assemble into DataFrame. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "893d1180",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format the DataFrame  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "328c829c",
   "metadata": {},
   "source": [
    "## Scores by School Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "edbbf2e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "4f93582f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assemble into DataFrame. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "c08e277c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Format the DataFrame \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b666b8f3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "58fed748",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "97859e68",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import csv\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0cfdfcf8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Files to Load ##better to use indirect path, just import os as first line\n",
    "schools_to_load = os.path.join('Resources', 'schools_complete.csv')\n",
    "students_to_load= os.path.join('Resources', 'students_complete.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "82b1f1c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read the school data file and store it in a Pandas DataFrame.\n",
    "school_data_df = pd.read_csv(schools_to_load)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c1de89ef",
   "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>Student ID</th>\n",
       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
       "      <th>grade</th>\n",
       "      <th>school_name</th>\n",
       "      <th>reading_score</th>\n",
       "      <th>math_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Paul Bradley</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>66</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Dr. Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>67</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>97</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Student ID       student_name gender grade        school_name  \\\n",
       "0           0       Paul Bradley      M   9th  Huang High School   \n",
       "1           1       Victor Smith      M  12th  Huang High School   \n",
       "2           2    Kevin Rodriguez      M  12th  Huang High School   \n",
       "3           3  Dr. Richard Scott      M  12th  Huang High School   \n",
       "4           4         Bonnie Ray      F   9th  Huang High School   \n",
       "\n",
       "   reading_score  math_score  \n",
       "0             66          79  \n",
       "1             94          61  \n",
       "2             90          60  \n",
       "3             67          58  \n",
       "4             97          84  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the student data file and store it in a Pandas DataFrame.\n",
    "student_data_df = pd.read_csv(students_to_load)\n",
    "student_data_df.head() ##insert number inside () for top X rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4fb90592",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "School ID      15\n",
       "school_name    15\n",
       "type           15\n",
       "size           15\n",
       "budget         15\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine if there are any missing values in the school data.\n",
    "school_data_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "42125a32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Student ID       39170\n",
       "student_name     39170\n",
       "gender           39170\n",
       "grade            39170\n",
       "school_name      39170\n",
       "reading_score    39170\n",
       "math_score       39170\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine if there are any missing values in the student data.\n",
    "student_data_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e2889cf6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "    School ID  school_name   type   size  budget\n",
       "0       False        False  False  False   False\n",
       "1       False        False  False  False   False\n",
       "2       False        False  False  False   False\n",
       "3       False        False  False  False   False\n",
       "4       False        False  False  False   False\n",
       "5       False        False  False  False   False\n",
       "6       False        False  False  False   False\n",
       "7       False        False  False  False   False\n",
       "8       False        False  False  False   False\n",
       "9       False        False  False  False   False\n",
       "10      False        False  False  False   False\n",
       "11      False        False  False  False   False\n",
       "12      False        False  False  False   False\n",
       "13      False        False  False  False   False\n",
       "14      False        False  False  False   False"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine if there are any missing values in the school data.\n",
    "school_data_df.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "60c5de63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Student ID       0\n",
       "student_name     0\n",
       "gender           0\n",
       "grade            0\n",
       "school_name      0\n",
       "reading_score    0\n",
       "math_score       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine if there are any missing values in the student data.\n",
    "student_data_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7497d614",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Student ID       39170\n",
       "student_name     39170\n",
       "gender           39170\n",
       "grade            39170\n",
       "school_name      39170\n",
       "reading_score    39170\n",
       "math_score       39170\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine if there are not any missing values in the student data.\n",
    "student_data_df.notnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4b4655d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "School ID       int64\n",
       "school_name    object\n",
       "type           object\n",
       "size            int64\n",
       "budget          int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine data types for the school DataFrame.\n",
    "school_data_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "23ae6636",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Student ID        int64\n",
       "student_name     object\n",
       "gender           object\n",
       "grade            object\n",
       "school_name      object\n",
       "reading_score     int64\n",
       "math_score        int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine data types for the student DataFrame.\n",
    "student_data_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "101e50b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add each prefix and suffix to remove to a list.\n",
    "prefixes_suffixes = [\"Dr. \", \"Mr. \",\"Ms. \", \"Mrs. \", \"Miss \", \" MD\", \" DDS\", \" DVM\", \" PhD\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d61bb6a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\kimbl\\anaconda3\\envs\\PythonData\\lib\\site-packages\\ipykernel_launcher.py:3: FutureWarning: The default value of regex will change from True to False in a future version.\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
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       "<p>39170 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Student ID     student_name gender grade         school_name  \\\n",
       "0               0     Paul Bradley      M   9th   Huang High School   \n",
       "1               1     Victor Smith      M  12th   Huang High School   \n",
       "2               2  Kevin Rodriguez      M  12th   Huang High School   \n",
       "3               3    Richard Scott      M  12th   Huang High School   \n",
       "4               4       Bonnie Ray      F   9th   Huang High School   \n",
       "...           ...              ...    ...   ...                 ...   \n",
       "39165       39165     Donna Howard      F  12th  Thomas High School   \n",
       "39166       39166        Dawn Bell      F  10th  Thomas High School   \n",
       "39167       39167   Rebecca Tanner      F   9th  Thomas High School   \n",
       "39168       39168     Desiree Kidd      F  10th  Thomas High School   \n",
       "39169       39169  Carolyn Jackson      F  11th  Thomas High School   \n",
       "\n",
       "       reading_score  math_score  \n",
       "0                 66          79  \n",
       "1                 94          61  \n",
       "2                 90          60  \n",
       "3                 67          58  \n",
       "4                 97          84  \n",
       "...              ...         ...  \n",
       "39165             99          90  \n",
       "39166             95          70  \n",
       "39167             73          84  \n",
       "39168             99          90  \n",
       "39169             95          75  \n",
       "\n",
       "[39170 rows x 7 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "# Iterate through the words in the \"prefixes_suffixes\" list and replace them with an empty space, \"\".\n",
    "for word in prefixes_suffixes:\n",
    "    student_data_df[\"student_name\"] = student_data_df[\"student_name\"].str.replace(word,\"\")\n",
    "    \n",
    "student_data_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "379c23a8",
   "metadata": {},
   "outputs": [
    {
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       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>67</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>97</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39165</th>\n",
       "      <td>39165</td>\n",
       "      <td>Donna Howard</td>\n",
       "      <td>F</td>\n",
       "      <td>12th</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>99</td>\n",
       "      <td>90</td>\n",
       "      <td>14</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>1043130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39166</th>\n",
       "      <td>39166</td>\n",
       "      <td>Dawn Bell</td>\n",
       "      <td>F</td>\n",
       "      <td>10th</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>95</td>\n",
       "      <td>70</td>\n",
       "      <td>14</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>1043130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39167</th>\n",
       "      <td>39167</td>\n",
       "      <td>Rebecca Tanner</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>73</td>\n",
       "      <td>84</td>\n",
       "      <td>14</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>1043130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39168</th>\n",
       "      <td>39168</td>\n",
       "      <td>Desiree Kidd</td>\n",
       "      <td>F</td>\n",
       "      <td>10th</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>99</td>\n",
       "      <td>90</td>\n",
       "      <td>14</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>1043130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39169</th>\n",
       "      <td>39169</td>\n",
       "      <td>Carolyn Jackson</td>\n",
       "      <td>F</td>\n",
       "      <td>11th</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>95</td>\n",
       "      <td>75</td>\n",
       "      <td>14</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>1043130</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>39170 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Student ID     student_name gender grade         school_name  \\\n",
       "0               0     Paul Bradley      M   9th   Huang High School   \n",
       "1               1     Victor Smith      M  12th   Huang High School   \n",
       "2               2  Kevin Rodriguez      M  12th   Huang High School   \n",
       "3               3    Richard Scott      M  12th   Huang High School   \n",
       "4               4       Bonnie Ray      F   9th   Huang High School   \n",
       "...           ...              ...    ...   ...                 ...   \n",
       "39165       39165     Donna Howard      F  12th  Thomas High School   \n",
       "39166       39166        Dawn Bell      F  10th  Thomas High School   \n",
       "39167       39167   Rebecca Tanner      F   9th  Thomas High School   \n",
       "39168       39168     Desiree Kidd      F  10th  Thomas High School   \n",
       "39169       39169  Carolyn Jackson      F  11th  Thomas High School   \n",
       "\n",
       "       reading_score  math_score  School ID      type  size   budget  \n",
       "0                 66          79          0  District  2917  1910635  \n",
       "1                 94          61          0  District  2917  1910635  \n",
       "2                 90          60          0  District  2917  1910635  \n",
       "3                 67          58          0  District  2917  1910635  \n",
       "4                 97          84          0  District  2917  1910635  \n",
       "...              ...         ...        ...       ...   ...      ...  \n",
       "39165             99          90         14   Charter  1635  1043130  \n",
       "39166             95          70         14   Charter  1635  1043130  \n",
       "39167             73          84         14   Charter  1635  1043130  \n",
       "39168             99          90         14   Charter  1635  1043130  \n",
       "39169             95          75         14   Charter  1635  1043130  \n",
       "\n",
       "[39170 rows x 11 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combine the data into a single dataset.\n",
    "school_data_complete_df = pd.merge(student_data_df, school_data_df, on=[\"school_name\", \"school_name\"])\n",
    "school_data_complete_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "74d980d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "39170"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the total number of students.\n",
    "student_count = school_data_complete_df[\"Student ID\"].count()\n",
    "student_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fcd9fd50",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the total number of schools.\n",
    "school_count = len(school_data_complete_df.school_name.unique())\n",
    "school_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "809118e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24649428"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the total budget.\n",
    "total_budget = school_data_df[\"budget\"].sum()\n",
    "total_budget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "98a5af55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "81.87784018381414"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the average reading score.\n",
    "average_reading_score = school_data_complete_df[\"reading_score\"].mean()\n",
    "average_reading_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4525b7fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "78.98537145774827"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the average math score.\n",
    "average_math_score = school_data_complete_df[\"math_score\"].mean()\n",
    "average_math_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0c1039ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "29,370 students passed Math.\n"
     ]
    }
   ],
   "source": [
    "# Get all the students that are passing math in a new DataFrame.\n",
    "passing_math = school_data_complete_df[school_data_complete_df[\"math_score\"] >=70]\n",
    "passing_math_count = passing_math['student_name'].count()\n",
    "print(f'{passing_math_count:,} students passed Math.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6a6dd052",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33,610 students passed Reading.\n"
     ]
    }
   ],
   "source": [
    "# Get all the students that are passing reading in a new DataFrame.\n",
    "passing_reading = school_data_complete_df[school_data_complete_df[\"reading_score\"] >=70]\n",
    "passing_reading_count = passing_reading['student_name'].count()\n",
    "print(f'{passing_reading_count:,} students passed Reading.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "328480cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "percent_passing_math = (passing_math_count)/float(student_count) * 100\n",
    "percent_passing_reading = passing_reading_count / float(student_count) * 100\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d72f1abd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25,528 passed both Math & Reading.\n"
     ]
    }
   ],
   "source": [
    "# Calculate the students who passed both math and reading.\n",
    "passing_math_reading = school_data_complete_df[(school_data_complete_df['math_score'] >= 70) & (school_data_complete_df['reading_score'] >= 70)]\n",
    "\n",
    "# Calculate the number of students who passed both math and reading.\n",
    "passing_math_reading_count = passing_math_reading['student_name'].count()\n",
    "print(f'{passing_math_reading_count:,} passed both Math & Reading.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6bd43e77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65.17232575950983"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the overall passing percentage.\n",
    "percent_overall_passing = passing_math_reading_count / float(student_count) * 100\n",
    "percent_overall_passing\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fb767c25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\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>Total Schools</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>15</td>\n",
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       "      <td>24649428</td>\n",
       "      <td>78.985371</td>\n",
       "      <td>81.87784</td>\n",
       "      <td>74.980853</td>\n",
       "      <td>85.805463</td>\n",
       "      <td>65.172326</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Total Schools  Total Students  Total Budget  Average Math Score  \\\n",
       "0             15           39170      24649428           78.985371   \n",
       "\n",
       "   Average Reading Score  % Passing Math  % Passing Reading  % Overall Passing  \n",
       "0               81.87784       74.980853          85.805463          65.172326  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "district_summary_df = pd.DataFrame(\n",
    "    [{'Total Schools':school_count,\n",
    "     'Total Students':student_count,\n",
    "     'Total Budget':total_budget,\n",
    "     'Average Math Score': average_math_score,\n",
    "     'Average Reading Score':average_reading_score,\n",
    "     '% Passing Math':percent_passing_math,\n",
    "     '% Passing Reading': percent_passing_reading,\n",
    "     '% Overall Passing':percent_overall_passing}]\n",
    ")\n",
    "district_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7be4f510",
   "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 Schools</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15</td>\n",
       "      <td>39,170</td>\n",
       "      <td>$24,649,428.00</td>\n",
       "      <td>79.0</td>\n",
       "      <td>81.9</td>\n",
       "      <td>75%</td>\n",
       "      <td>86%</td>\n",
       "      <td>65%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Total Schools Total Students    Total Budget Average Math Score  \\\n",
       "0             15         39,170  $24,649,428.00               79.0   \n",
       "\n",
       "  Average Reading Score % Passing Math % Passing Reading % Overall Passing  \n",
       "0                  81.9            75%               86%               65%  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Format the columns.   \n",
    "district_summary_df[\"Total Students\"] = district_summary_df[\"Total Students\"].map('{:,}'.format)\n",
    "district_summary_df[\"Total Budget\"] = district_summary_df[\"Total Budget\"].map(\"${:,.2f}\".format)\n",
    "district_summary_df[\"Average Math Score\"] = district_summary_df[\"Average Math Score\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"Average Reading Score\"] = district_summary_df[\"Average Reading Score\"].map(\"{:.1f}\".format)\n",
    "district_summary_df[\"% Passing Math\"] = district_summary_df[\"% Passing Math\"].map(\"{:.0f}%\".format)\n",
    "district_summary_df[\"% Passing Reading\"] = district_summary_df[\"% Passing Reading\"].map(\"{:.0f}%\".format)\n",
    "district_summary_df[\"% Overall Passing\"] = district_summary_df[\"% Overall Passing\"].map(\"{:.0f}%\".format)\n",
    "district_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c55f64f3",
   "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 Schools</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15</td>\n",
       "      <td>39,170</td>\n",
       "      <td>$24,649,428.00</td>\n",
       "      <td>79.0</td>\n",
       "      <td>81.9</td>\n",
       "      <td>75%</td>\n",
       "      <td>86%</td>\n",
       "      <td>65%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Total Schools Total Students    Total Budget Average Math Score  \\\n",
       "0             15         39,170  $24,649,428.00               79.0   \n",
       "\n",
       "  Average Reading Score % Passing Math % Passing Reading % Overall Passing  \n",
       "0                  81.9            75%               86%               65%  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reorder the columns in the order you want them to appear.\n",
    "new_column_order = [\"Total Schools\", \"Total Students\", \"Total Budget\",\"Average Math Score\", \"Average Reading Score\", \"% Passing Math\", \"% Passing Reading\", \"% Overall Passing\"]\n",
    "\n",
    "# Assign district summary df the new column order.\n",
    "district_summary_df = district_summary_df[new_column_order]\n",
    "district_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4b36edf7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a function that calculates the percentage of students that passed both # math and reading and prints the passing percentage to the output when the\n",
    "# function is called.\n",
    "def percent_passing_math():\n",
    "    return passing_math_count / float(student_count) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6c7d6b30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "school_name\n",
       "Huang High School        District\n",
       "Figueroa High School     District\n",
       "Shelton High School       Charter\n",
       "Hernandez High School    District\n",
       "Griffin High School       Charter\n",
       "Wilson High School        Charter\n",
       "Cabrera High School       Charter\n",
       "Bailey High School       District\n",
       "Holden High School        Charter\n",
       "Pena High School          Charter\n",
       "Wright High School        Charter\n",
       "Rodriguez High School    District\n",
       "Johnson High School      District\n",
       "Ford High School         District\n",
       "Thomas High School        Charter\n",
       "Name: type, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine the school type.\n",
    "per_school_types = school_data_df.set_index([\"school_name\"])[\"type\"]\n",
    "per_school_types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ea8189c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "passing_math_count = 29370\n",
    "student_count = 39170"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b475f731",
   "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>type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>Charter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>Charter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>Charter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>Charter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>Charter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>Charter</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           type\n",
       "school_name                    \n",
       "Huang High School      District\n",
       "Figueroa High School   District\n",
       "Shelton High School     Charter\n",
       "Hernandez High School  District\n",
       "Griffin High School     Charter\n",
       "Wilson High School      Charter\n",
       "Cabrera High School     Charter\n",
       "Bailey High School     District\n",
       "Holden High School      Charter\n",
       "Pena High School        Charter\n",
       "Wright High School      Charter\n",
       "Rodriguez High School  District\n",
       "Johnson High School    District\n",
       "Ford High School       District\n",
       "Thomas High School      Charter"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(per_school_types)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "dba95f64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "74.9808526933878"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Call the function.\n",
    "percent_passing_math()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2e75575d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "school_name\n",
       "Huang High School        2917\n",
       "Figueroa High School     2949\n",
       "Shelton High School      1761\n",
       "Hernandez High School    4635\n",
       "Griffin High School      1468\n",
       "Wilson High School       2283\n",
       "Cabrera High School      1858\n",
       "Bailey High School       4976\n",
       "Holden High School        427\n",
       "Pena High School          962\n",
       "Wright High School       1800\n",
       "Rodriguez High School    3999\n",
       "Johnson High School      4761\n",
       "Ford High School         2739\n",
       "Thomas High School       1635\n",
       "Name: size, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the total student count.\n",
    "per_school_counts = school_data_df.set_index([\"school_name\"])[\"size\"]\n",
    "per_school_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "78d59d8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "school_name\n",
       "Huang High School        1910635\n",
       "Figueroa High School     1884411\n",
       "Shelton High School      1056600\n",
       "Hernandez High School    3022020\n",
       "Griffin High School       917500\n",
       "Wilson High School       1319574\n",
       "Cabrera High School      1081356\n",
       "Bailey High School       3124928\n",
       "Holden High School        248087\n",
       "Pena High School          585858\n",
       "Wright High School       1049400\n",
       "Rodriguez High School    2547363\n",
       "Johnson High School      3094650\n",
       "Ford High School         1763916\n",
       "Thomas High School       1043130\n",
       "Name: budget, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the total school budget.\n",
    "per_school_budget = school_data_df.set_index([\"school_name\"])[\"budget\"]\n",
    "per_school_budget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "3bf8def6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "school_name\n",
       "Huang High School        655.0\n",
       "Figueroa High School     639.0\n",
       "Shelton High School      600.0\n",
       "Hernandez High School    652.0\n",
       "Griffin High School      625.0\n",
       "Wilson High School       578.0\n",
       "Cabrera High School      582.0\n",
       "Bailey High School       628.0\n",
       "Holden High School       581.0\n",
       "Pena High School         609.0\n",
       "Wright High School       583.0\n",
       "Rodriguez High School    637.0\n",
       "Johnson High School      650.0\n",
       "Ford High School         644.0\n",
       "Thomas High School       638.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the per capita spending.\n",
    "per_school_capita = per_school_budget / per_school_counts\n",
    "per_school_capita"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "06f6ef6a",
   "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>Student ID</th>\n",
       "      <th>reading_score</th>\n",
       "      <th>math_score</th>\n",
       "      <th>School ID</th>\n",
       "      <th>size</th>\n",
       "      <th>budget</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_name</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>Bailey High School</th>\n",
       "      <td>20358.5</td>\n",
       "      <td>81.033963</td>\n",
       "      <td>77.048432</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4976.0</td>\n",
       "      <td>3124928.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>16941.5</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1858.0</td>\n",
       "      <td>1081356.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>4391.0</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2949.0</td>\n",
       "      <td>1884411.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>36165.0</td>\n",
       "      <td>80.746258</td>\n",
       "      <td>77.102592</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2739.0</td>\n",
       "      <td>1763916.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>12995.5</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1468.0</td>\n",
       "      <td>917500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>9944.0</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4635.0</td>\n",
       "      <td>3022020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>23060.0</td>\n",
       "      <td>83.814988</td>\n",
       "      <td>83.803279</td>\n",
       "      <td>8.0</td>\n",
       "      <td>427.0</td>\n",
       "      <td>248087.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>1458.0</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2917.0</td>\n",
       "      <td>1910635.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>32415.0</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>12.0</td>\n",
       "      <td>4761.0</td>\n",
       "      <td>3094650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>23754.5</td>\n",
       "      <td>84.044699</td>\n",
       "      <td>83.839917</td>\n",
       "      <td>9.0</td>\n",
       "      <td>962.0</td>\n",
       "      <td>585858.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>28035.0</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3999.0</td>\n",
       "      <td>2547363.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>6746.0</td>\n",
       "      <td>83.725724</td>\n",
       "      <td>83.359455</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1761.0</td>\n",
       "      <td>1056600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>38352.0</td>\n",
       "      <td>83.848930</td>\n",
       "      <td>83.418349</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1635.0</td>\n",
       "      <td>1043130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>14871.0</td>\n",
       "      <td>83.989488</td>\n",
       "      <td>83.274201</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2283.0</td>\n",
       "      <td>1319574.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>25135.5</td>\n",
       "      <td>83.955000</td>\n",
       "      <td>83.682222</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>1049400.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Student ID  reading_score  math_score  School ID  \\\n",
       "school_name                                                               \n",
       "Bailey High School        20358.5      81.033963   77.048432        7.0   \n",
       "Cabrera High School       16941.5      83.975780   83.061895        6.0   \n",
       "Figueroa High School       4391.0      81.158020   76.711767        1.0   \n",
       "Ford High School          36165.0      80.746258   77.102592       13.0   \n",
       "Griffin High School       12995.5      83.816757   83.351499        4.0   \n",
       "Hernandez High School      9944.0      80.934412   77.289752        3.0   \n",
       "Holden High School        23060.0      83.814988   83.803279        8.0   \n",
       "Huang High School          1458.0      81.182722   76.629414        0.0   \n",
       "Johnson High School       32415.0      80.966394   77.072464       12.0   \n",
       "Pena High School          23754.5      84.044699   83.839917        9.0   \n",
       "Rodriguez High School     28035.0      80.744686   76.842711       11.0   \n",
       "Shelton High School        6746.0      83.725724   83.359455        2.0   \n",
       "Thomas High School        38352.0      83.848930   83.418349       14.0   \n",
       "Wilson High School        14871.0      83.989488   83.274201        5.0   \n",
       "Wright High School        25135.5      83.955000   83.682222       10.0   \n",
       "\n",
       "                         size     budget  \n",
       "school_name                               \n",
       "Bailey High School     4976.0  3124928.0  \n",
       "Cabrera High School    1858.0  1081356.0  \n",
       "Figueroa High School   2949.0  1884411.0  \n",
       "Ford High School       2739.0  1763916.0  \n",
       "Griffin High School    1468.0   917500.0  \n",
       "Hernandez High School  4635.0  3022020.0  \n",
       "Holden High School      427.0   248087.0  \n",
       "Huang High School      2917.0  1910635.0  \n",
       "Johnson High School    4761.0  3094650.0  \n",
       "Pena High School        962.0   585858.0  \n",
       "Rodriguez High School  3999.0  2547363.0  \n",
       "Shelton High School    1761.0  1056600.0  \n",
       "Thomas High School     1635.0  1043130.0  \n",
       "Wilson High School     2283.0  1319574.0  \n",
       "Wright High School     1800.0  1049400.0  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the average math scores.\n",
    "per_school_averages = school_data_complete_df.groupby([\"school_name\"]).mean()\n",
    "per_school_averages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "77dac4f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the average test scores.\n",
    "per_school_math = school_data_complete_df.groupby([\"school_name\"]).mean()[\"math_score\"]\n",
    "\n",
    "per_school_reading = school_data_complete_df.groupby([\"school_name\"]).mean()[\"reading_score\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "7b8b6d77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "school_name\n",
       "Bailey High School       77.048432\n",
       "Cabrera High School      83.061895\n",
       "Figueroa High School     76.711767\n",
       "Ford High School         77.102592\n",
       "Griffin High School      83.351499\n",
       "Hernandez High School    77.289752\n",
       "Holden High School       83.803279\n",
       "Huang High School        76.629414\n",
       "Johnson High School      77.072464\n",
       "Pena High School         83.839917\n",
       "Rodriguez High School    76.842711\n",
       "Shelton High School      83.359455\n",
       "Thomas High School       83.418349\n",
       "Wilson High School       83.274201\n",
       "Wright High School       83.682222\n",
       "Name: math_score, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "per_school_math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "fb4213b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "school_name\n",
       "Bailey High School       81.033963\n",
       "Cabrera High School      83.975780\n",
       "Figueroa High School     81.158020\n",
       "Ford High School         80.746258\n",
       "Griffin High School      83.816757\n",
       "Hernandez High School    80.934412\n",
       "Holden High School       83.814988\n",
       "Huang High School        81.182722\n",
       "Johnson High School      80.966394\n",
       "Pena High School         84.044699\n",
       "Rodriguez High School    80.744686\n",
       "Shelton High School      83.725724\n",
       "Thomas High School       83.848930\n",
       "Wilson High School       83.989488\n",
       "Wright High School       83.955000\n",
       "Name: reading_score, dtype: float64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "per_school_reading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "1fec4f2d",
   "metadata": {},
   "outputs": [],
   "source": [
    " # To get the passing percentages, we need to:\n",
    " # 1. Determine what is the passing grade.\n",
    " # 2. Get the number of students who passed math and reading.\n",
    " # 3. Get the students who passed math and passed reading."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "f15ad9d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the passing scores by creating a filtered DataFrame.\n",
    "per_school_passing_math = school_data_complete_df[(school_data_complete_df[\"math_score\"] >= 70)]\n",
    "\n",
    "per_school_passing_reading = school_data_complete_df[(school_data_complete_df[\"reading_score\"] >= 70)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "71d457be",
   "metadata": {},
   "outputs": [
    {
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       "      <td>Donna Howard</td>\n",
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       "      <td>Rebecca Tanner</td>\n",
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       "      <td>Desiree Kidd</td>\n",
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      ],
      "text/plain": [
       "       Student ID     student_name gender grade         school_name  \\\n",
       "0               0     Paul Bradley      M   9th   Huang High School   \n",
       "4               4       Bonnie Ray      F   9th   Huang High School   \n",
       "5               5    Bryan Miranda      M   9th   Huang High School   \n",
       "6               6    Sheena Carter      F  11th   Huang High School   \n",
       "8               8     Michael Roth      M  10th   Huang High School   \n",
       "...           ...              ...    ...   ...                 ...   \n",
       "39165       39165     Donna Howard      F  12th  Thomas High School   \n",
       "39166       39166        Dawn Bell      F  10th  Thomas High School   \n",
       "39167       39167   Rebecca Tanner      F   9th  Thomas High School   \n",
       "39168       39168     Desiree Kidd      F  10th  Thomas High School   \n",
       "39169       39169  Carolyn Jackson      F  11th  Thomas High School   \n",
       "\n",
       "       reading_score  math_score  School ID      type  size   budget  \n",
       "0                 66          79          0  District  2917  1910635  \n",
       "4                 97          84          0  District  2917  1910635  \n",
       "5                 94          94          0  District  2917  1910635  \n",
       "6                 82          80          0  District  2917  1910635  \n",
       "8                 95          87          0  District  2917  1910635  \n",
       "...              ...         ...        ...       ...   ...      ...  \n",
       "39165             99          90         14   Charter  1635  1043130  \n",
       "39166             95          70         14   Charter  1635  1043130  \n",
       "39167             73          84         14   Charter  1635  1043130  \n",
       "39168             99          90         14   Charter  1635  1043130  \n",
       "39169             95          75         14   Charter  1635  1043130  \n",
       "\n",
       "[29370 rows x 11 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "per_school_passing_math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "9b6a997d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the number of students passing math and passing reading by school.\n",
    "per_school_passing_math = per_school_passing_math.groupby([\"school_name\"]).count()[\"student_name\"]\n",
    "\n",
    "per_school_passing_reading = per_school_passing_reading.groupby([\"school_name\"]).count()[\"student_name\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "3637f230",
   "metadata": {},
   "outputs": [
    {
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       "      <td>Donna Howard</td>\n",
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       "      <td>12th</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>99</td>\n",
       "      <td>90</td>\n",
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       "      <td>Dawn Bell</td>\n",
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       "      <td>70</td>\n",
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       "      <td>1635</td>\n",
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       "      <td>Rebecca Tanner</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>73</td>\n",
       "      <td>84</td>\n",
       "      <td>14</td>\n",
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       "      <td>Desiree Kidd</td>\n",
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       "      <td>10th</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>99</td>\n",
       "      <td>90</td>\n",
       "      <td>14</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
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       "      <td>Carolyn Jackson</td>\n",
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       "      <td>Thomas High School</td>\n",
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       "      <td>1043130</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>25528 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Student ID     student_name gender grade         school_name  \\\n",
       "4               4       Bonnie Ray      F   9th   Huang High School   \n",
       "5               5    Bryan Miranda      M   9th   Huang High School   \n",
       "6               6    Sheena Carter      F  11th   Huang High School   \n",
       "8               8     Michael Roth      M  10th   Huang High School   \n",
       "9               9   Matthew Greene      M  10th   Huang High School   \n",
       "...           ...              ...    ...   ...                 ...   \n",
       "39165       39165     Donna Howard      F  12th  Thomas High School   \n",
       "39166       39166        Dawn Bell      F  10th  Thomas High School   \n",
       "39167       39167   Rebecca Tanner      F   9th  Thomas High School   \n",
       "39168       39168     Desiree Kidd      F  10th  Thomas High School   \n",
       "39169       39169  Carolyn Jackson      F  11th  Thomas High School   \n",
       "\n",
       "       reading_score  math_score  School ID      type  size   budget  \n",
       "4                 97          84          0  District  2917  1910635  \n",
       "5                 94          94          0  District  2917  1910635  \n",
       "6                 82          80          0  District  2917  1910635  \n",
       "8                 95          87          0  District  2917  1910635  \n",
       "9                 96          84          0  District  2917  1910635  \n",
       "...              ...         ...        ...       ...   ...      ...  \n",
       "39165             99          90         14   Charter  1635  1043130  \n",
       "39166             95          70         14   Charter  1635  1043130  \n",
       "39167             73          84         14   Charter  1635  1043130  \n",
       "39168             99          90         14   Charter  1635  1043130  \n",
       "39169             95          75         14   Charter  1635  1043130  \n",
       "\n",
       "[25528 rows x 11 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the students who passed both math and reading.\n",
    "per_passing_math_reading = school_data_complete_df[(school_data_complete_df[\"math_score\"] >= 70) & (school_data_complete_df[\"reading_score\"] >= 70)]\n",
    "\n",
    "per_passing_math_reading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "bbc65436",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the number of students who passed both math and reading.\n",
    "per_passing_math_reading = per_passing_math_reading.groupby([\"school_name\"]).count()[\"student_name\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b96bfbcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the percentage of passing math and reading scores per school.\n",
    "per_school_passing_math = per_school_passing_math / per_school_counts * 100\n",
    "\n",
    "per_school_passing_reading = per_school_passing_reading / per_school_counts * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "d547c505",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the overall passing percentage.\n",
    "per_overall_passing_percentage = per_passing_math_reading / per_school_counts * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "a9b9d514",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>3124928</td>\n",
       "      <td>628.0</td>\n",
       "      <td>77.048432</td>\n",
       "      <td>81.033963</td>\n",
       "      <td>66.680064</td>\n",
       "      <td>81.933280</td>\n",
       "      <td>54.642283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>1081356</td>\n",
       "      <td>582.0</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>94.133477</td>\n",
       "      <td>97.039828</td>\n",
       "      <td>91.334769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>1884411</td>\n",
       "      <td>639.0</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>1763916</td>\n",
       "      <td>644.0</td>\n",
       "      <td>77.102592</td>\n",
       "      <td>80.746258</td>\n",
       "      <td>68.309602</td>\n",
       "      <td>79.299014</td>\n",
       "      <td>54.289887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>917500</td>\n",
       "      <td>625.0</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>93.392371</td>\n",
       "      <td>97.138965</td>\n",
       "      <td>90.599455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>3022020</td>\n",
       "      <td>652.0</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>66.752967</td>\n",
       "      <td>80.862999</td>\n",
       "      <td>53.527508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>427</td>\n",
       "      <td>248087</td>\n",
       "      <td>581.0</td>\n",
       "      <td>83.803279</td>\n",
       "      <td>83.814988</td>\n",
       "      <td>92.505855</td>\n",
       "      <td>96.252927</td>\n",
       "      <td>89.227166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "      <td>655.0</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>65.683922</td>\n",
       "      <td>81.316421</td>\n",
       "      <td>53.513884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>3094650</td>\n",
       "      <td>650.0</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>66.057551</td>\n",
       "      <td>81.222432</td>\n",
       "      <td>53.539172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>585858</td>\n",
       "      <td>609.0</td>\n",
       "      <td>83.839917</td>\n",
       "      <td>84.044699</td>\n",
       "      <td>94.594595</td>\n",
       "      <td>95.945946</td>\n",
       "      <td>90.540541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>2547363</td>\n",
       "      <td>637.0</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>66.366592</td>\n",
       "      <td>80.220055</td>\n",
       "      <td>52.988247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>1056600</td>\n",
       "      <td>600.0</td>\n",
       "      <td>83.359455</td>\n",
       "      <td>83.725724</td>\n",
       "      <td>93.867121</td>\n",
       "      <td>95.854628</td>\n",
       "      <td>89.892107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>1043130</td>\n",
       "      <td>638.0</td>\n",
       "      <td>83.418349</td>\n",
       "      <td>83.848930</td>\n",
       "      <td>93.272171</td>\n",
       "      <td>97.308869</td>\n",
       "      <td>90.948012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>1319574</td>\n",
       "      <td>578.0</td>\n",
       "      <td>83.274201</td>\n",
       "      <td>83.989488</td>\n",
       "      <td>93.867718</td>\n",
       "      <td>96.539641</td>\n",
       "      <td>90.582567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1800</td>\n",
       "      <td>1049400</td>\n",
       "      <td>583.0</td>\n",
       "      <td>83.682222</td>\n",
       "      <td>83.955000</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>96.611111</td>\n",
       "      <td>90.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      School Type  Total Students  Total School Budget  \\\n",
       "school_name                                                              \n",
       "Bailey High School       District            4976              3124928   \n",
       "Cabrera High School       Charter            1858              1081356   \n",
       "Figueroa High School     District            2949              1884411   \n",
       "Ford High School         District            2739              1763916   \n",
       "Griffin High School       Charter            1468               917500   \n",
       "Hernandez High School    District            4635              3022020   \n",
       "Holden High School        Charter             427               248087   \n",
       "Huang High School        District            2917              1910635   \n",
       "Johnson High School      District            4761              3094650   \n",
       "Pena High School          Charter             962               585858   \n",
       "Rodriguez High School    District            3999              2547363   \n",
       "Shelton High School       Charter            1761              1056600   \n",
       "Thomas High School        Charter            1635              1043130   \n",
       "Wilson High School        Charter            2283              1319574   \n",
       "Wright High School        Charter            1800              1049400   \n",
       "\n",
       "                       Per Student Budget  Average Math Score  \\\n",
       "school_name                                                     \n",
       "Bailey High School                  628.0           77.048432   \n",
       "Cabrera High School                 582.0           83.061895   \n",
       "Figueroa High School                639.0           76.711767   \n",
       "Ford High School                    644.0           77.102592   \n",
       "Griffin High School                 625.0           83.351499   \n",
       "Hernandez High School               652.0           77.289752   \n",
       "Holden High School                  581.0           83.803279   \n",
       "Huang High School                   655.0           76.629414   \n",
       "Johnson High School                 650.0           77.072464   \n",
       "Pena High School                    609.0           83.839917   \n",
       "Rodriguez High School               637.0           76.842711   \n",
       "Shelton High School                 600.0           83.359455   \n",
       "Thomas High School                  638.0           83.418349   \n",
       "Wilson High School                  578.0           83.274201   \n",
       "Wright High School                  583.0           83.682222   \n",
       "\n",
       "                       Average Reading Score  % Passing Math  \\\n",
       "school_name                                                    \n",
       "Bailey High School                 81.033963       66.680064   \n",
       "Cabrera High School                83.975780       94.133477   \n",
       "Figueroa High School               81.158020       65.988471   \n",
       "Ford High School                   80.746258       68.309602   \n",
       "Griffin High School                83.816757       93.392371   \n",
       "Hernandez High School              80.934412       66.752967   \n",
       "Holden High School                 83.814988       92.505855   \n",
       "Huang High School                  81.182722       65.683922   \n",
       "Johnson High School                80.966394       66.057551   \n",
       "Pena High School                   84.044699       94.594595   \n",
       "Rodriguez High School              80.744686       66.366592   \n",
       "Shelton High School                83.725724       93.867121   \n",
       "Thomas High School                 83.848930       93.272171   \n",
       "Wilson High School                 83.989488       93.867718   \n",
       "Wright High School                 83.955000       93.333333   \n",
       "\n",
       "                       % Passing Reading  % Overall Passing  \n",
       "school_name                                                  \n",
       "Bailey High School             81.933280          54.642283  \n",
       "Cabrera High School            97.039828          91.334769  \n",
       "Figueroa High School           80.739234          53.204476  \n",
       "Ford High School               79.299014          54.289887  \n",
       "Griffin High School            97.138965          90.599455  \n",
       "Hernandez High School          80.862999          53.527508  \n",
       "Holden High School             96.252927          89.227166  \n",
       "Huang High School              81.316421          53.513884  \n",
       "Johnson High School            81.222432          53.539172  \n",
       "Pena High School               95.945946          90.540541  \n",
       "Rodriguez High School          80.220055          52.988247  \n",
       "Shelton High School            95.854628          89.892107  \n",
       "Thomas High School             97.308869          90.948012  \n",
       "Wilson High School             96.539641          90.582567  \n",
       "Wright High School             96.611111          90.333333  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "per_school_summary_df = pd.DataFrame({\n",
    "             \"School Type\": per_school_types,\n",
    "             \"Total Students\": per_school_counts,\n",
    "             \"Total School Budget\": per_school_budget,\n",
    "             \"Per Student Budget\": per_school_capita,\n",
    "             \"Average Math Score\": per_school_math,\n",
    "           \"Average Reading Score\": per_school_reading,\n",
    "           \"% Passing Math\": per_school_passing_math,\n",
    "           \"% Passing Reading\": per_school_passing_reading,\n",
    "           \"% Overall Passing\": per_overall_passing_percentage})\n",
    "per_school_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "503cd80a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Bailey High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>$3,124,928.00</td>\n",
       "      <td>$628.00</td>\n",
       "      <td>77.048432</td>\n",
       "      <td>81.033963</td>\n",
       "      <td>66.680064</td>\n",
       "      <td>81.933280</td>\n",
       "      <td>54.642283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>$1,081,356.00</td>\n",
       "      <td>$582.00</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>94.133477</td>\n",
       "      <td>97.039828</td>\n",
       "      <td>91.334769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>$1,884,411.00</td>\n",
       "      <td>$639.00</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>$1,763,916.00</td>\n",
       "      <td>$644.00</td>\n",
       "      <td>77.102592</td>\n",
       "      <td>80.746258</td>\n",
       "      <td>68.309602</td>\n",
       "      <td>79.299014</td>\n",
       "      <td>54.289887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>$917,500.00</td>\n",
       "      <td>$625.00</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>93.392371</td>\n",
       "      <td>97.138965</td>\n",
       "      <td>90.599455</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     School Type  Total Students Total School Budget  \\\n",
       "school_name                                                            \n",
       "Bailey High School      District            4976       $3,124,928.00   \n",
       "Cabrera High School      Charter            1858       $1,081,356.00   \n",
       "Figueroa High School    District            2949       $1,884,411.00   \n",
       "Ford High School        District            2739       $1,763,916.00   \n",
       "Griffin High School      Charter            1468         $917,500.00   \n",
       "\n",
       "                     Per Student Budget  Average Math Score  \\\n",
       "school_name                                                   \n",
       "Bailey High School              $628.00           77.048432   \n",
       "Cabrera High School             $582.00           83.061895   \n",
       "Figueroa High School            $639.00           76.711767   \n",
       "Ford High School                $644.00           77.102592   \n",
       "Griffin High School             $625.00           83.351499   \n",
       "\n",
       "                      Average Reading Score  % Passing Math  \\\n",
       "school_name                                                   \n",
       "Bailey High School                81.033963       66.680064   \n",
       "Cabrera High School               83.975780       94.133477   \n",
       "Figueroa High School              81.158020       65.988471   \n",
       "Ford High School                  80.746258       68.309602   \n",
       "Griffin High School               83.816757       93.392371   \n",
       "\n",
       "                      % Passing Reading  % Overall Passing  \n",
       "school_name                                                 \n",
       "Bailey High School            81.933280          54.642283  \n",
       "Cabrera High School           97.039828          91.334769  \n",
       "Figueroa High School          80.739234          53.204476  \n",
       "Ford High School              79.299014          54.289887  \n",
       "Griffin High School           97.138965          90.599455  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Format the Total School Budget and the Per Student Budget columns.\n",
    "per_school_summary_df[\"Total School Budget\"] = per_school_summary_df[\"Total School Budget\"].map(\"${:,.2f}\".format)\n",
    "\n",
    "per_school_summary_df[\"Per Student Budget\"] = per_school_summary_df[\"Per Student Budget\"].map(\"${:,.2f}\".format)\n",
    "\n",
    "\n",
    "# Display the data frame\n",
    "per_school_summary_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "d61a2a63",
   "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>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>$1,081,356.00</td>\n",
       "      <td>$582.00</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>94.133477</td>\n",
       "      <td>97.039828</td>\n",
       "      <td>91.334769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>$1,043,130.00</td>\n",
       "      <td>$638.00</td>\n",
       "      <td>83.418349</td>\n",
       "      <td>83.848930</td>\n",
       "      <td>93.272171</td>\n",
       "      <td>97.308869</td>\n",
       "      <td>90.948012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>$917,500.00</td>\n",
       "      <td>$625.00</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>93.392371</td>\n",
       "      <td>97.138965</td>\n",
       "      <td>90.599455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>$1,319,574.00</td>\n",
       "      <td>$578.00</td>\n",
       "      <td>83.274201</td>\n",
       "      <td>83.989488</td>\n",
       "      <td>93.867718</td>\n",
       "      <td>96.539641</td>\n",
       "      <td>90.582567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>$585,858.00</td>\n",
       "      <td>$609.00</td>\n",
       "      <td>83.839917</td>\n",
       "      <td>84.044699</td>\n",
       "      <td>94.594595</td>\n",
       "      <td>95.945946</td>\n",
       "      <td>90.540541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1800</td>\n",
       "      <td>$1,049,400.00</td>\n",
       "      <td>$583.00</td>\n",
       "      <td>83.682222</td>\n",
       "      <td>83.955000</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>96.611111</td>\n",
       "      <td>90.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>$1,056,600.00</td>\n",
       "      <td>$600.00</td>\n",
       "      <td>83.359455</td>\n",
       "      <td>83.725724</td>\n",
       "      <td>93.867121</td>\n",
       "      <td>95.854628</td>\n",
       "      <td>89.892107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>427</td>\n",
       "      <td>$248,087.00</td>\n",
       "      <td>$581.00</td>\n",
       "      <td>83.803279</td>\n",
       "      <td>83.814988</td>\n",
       "      <td>92.505855</td>\n",
       "      <td>96.252927</td>\n",
       "      <td>89.227166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>$3,124,928.00</td>\n",
       "      <td>$628.00</td>\n",
       "      <td>77.048432</td>\n",
       "      <td>81.033963</td>\n",
       "      <td>66.680064</td>\n",
       "      <td>81.933280</td>\n",
       "      <td>54.642283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>$1,763,916.00</td>\n",
       "      <td>$644.00</td>\n",
       "      <td>77.102592</td>\n",
       "      <td>80.746258</td>\n",
       "      <td>68.309602</td>\n",
       "      <td>79.299014</td>\n",
       "      <td>54.289887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>$3,094,650.00</td>\n",
       "      <td>$650.00</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>66.057551</td>\n",
       "      <td>81.222432</td>\n",
       "      <td>53.539172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>$3,022,020.00</td>\n",
       "      <td>$652.00</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>66.752967</td>\n",
       "      <td>80.862999</td>\n",
       "      <td>53.527508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>$1,910,635.00</td>\n",
       "      <td>$655.00</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>65.683922</td>\n",
       "      <td>81.316421</td>\n",
       "      <td>53.513884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>$1,884,411.00</td>\n",
       "      <td>$639.00</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>$2,547,363.00</td>\n",
       "      <td>$637.00</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>66.366592</td>\n",
       "      <td>80.220055</td>\n",
       "      <td>52.988247</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      School Type  Total Students Total School Budget  \\\n",
       "school_name                                                             \n",
       "Cabrera High School       Charter            1858       $1,081,356.00   \n",
       "Thomas High School        Charter            1635       $1,043,130.00   \n",
       "Griffin High School       Charter            1468         $917,500.00   \n",
       "Wilson High School        Charter            2283       $1,319,574.00   \n",
       "Pena High School          Charter             962         $585,858.00   \n",
       "Wright High School        Charter            1800       $1,049,400.00   \n",
       "Shelton High School       Charter            1761       $1,056,600.00   \n",
       "Holden High School        Charter             427         $248,087.00   \n",
       "Bailey High School       District            4976       $3,124,928.00   \n",
       "Ford High School         District            2739       $1,763,916.00   \n",
       "Johnson High School      District            4761       $3,094,650.00   \n",
       "Hernandez High School    District            4635       $3,022,020.00   \n",
       "Huang High School        District            2917       $1,910,635.00   \n",
       "Figueroa High School     District            2949       $1,884,411.00   \n",
       "Rodriguez High School    District            3999       $2,547,363.00   \n",
       "\n",
       "                      Per Student Budget  Average Math Score  \\\n",
       "school_name                                                    \n",
       "Cabrera High School              $582.00           83.061895   \n",
       "Thomas High School               $638.00           83.418349   \n",
       "Griffin High School              $625.00           83.351499   \n",
       "Wilson High School               $578.00           83.274201   \n",
       "Pena High School                 $609.00           83.839917   \n",
       "Wright High School               $583.00           83.682222   \n",
       "Shelton High School              $600.00           83.359455   \n",
       "Holden High School               $581.00           83.803279   \n",
       "Bailey High School               $628.00           77.048432   \n",
       "Ford High School                 $644.00           77.102592   \n",
       "Johnson High School              $650.00           77.072464   \n",
       "Hernandez High School            $652.00           77.289752   \n",
       "Huang High School                $655.00           76.629414   \n",
       "Figueroa High School             $639.00           76.711767   \n",
       "Rodriguez High School            $637.00           76.842711   \n",
       "\n",
       "                       Average Reading Score  % Passing Math  \\\n",
       "school_name                                                    \n",
       "Cabrera High School                83.975780       94.133477   \n",
       "Thomas High School                 83.848930       93.272171   \n",
       "Griffin High School                83.816757       93.392371   \n",
       "Wilson High School                 83.989488       93.867718   \n",
       "Pena High School                   84.044699       94.594595   \n",
       "Wright High School                 83.955000       93.333333   \n",
       "Shelton High School                83.725724       93.867121   \n",
       "Holden High School                 83.814988       92.505855   \n",
       "Bailey High School                 81.033963       66.680064   \n",
       "Ford High School                   80.746258       68.309602   \n",
       "Johnson High School                80.966394       66.057551   \n",
       "Hernandez High School              80.934412       66.752967   \n",
       "Huang High School                  81.182722       65.683922   \n",
       "Figueroa High School               81.158020       65.988471   \n",
       "Rodriguez High School              80.744686       66.366592   \n",
       "\n",
       "                       % Passing Reading  % Overall Passing  \n",
       "school_name                                                  \n",
       "Cabrera High School            97.039828          91.334769  \n",
       "Thomas High School             97.308869          90.948012  \n",
       "Griffin High School            97.138965          90.599455  \n",
       "Wilson High School             96.539641          90.582567  \n",
       "Pena High School               95.945946          90.540541  \n",
       "Wright High School             96.611111          90.333333  \n",
       "Shelton High School            95.854628          89.892107  \n",
       "Holden High School             96.252927          89.227166  \n",
       "Bailey High School             81.933280          54.642283  \n",
       "Ford High School               79.299014          54.289887  \n",
       "Johnson High School            81.222432          53.539172  \n",
       "Hernandez High School          80.862999          53.527508  \n",
       "Huang High School              81.316421          53.513884  \n",
       "Figueroa High School           80.739234          53.204476  \n",
       "Rodriguez High School          80.220055          52.988247  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_schools = per_school_summary_df.sort_values(['% Overall Passing'], ascending= False)\n",
    "top_schools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "02e1ded4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>$2,547,363.00</td>\n",
       "      <td>$637.00</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>66.366592</td>\n",
       "      <td>80.220055</td>\n",
       "      <td>52.988247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>$1,884,411.00</td>\n",
       "      <td>$639.00</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>$1,910,635.00</td>\n",
       "      <td>$655.00</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>65.683922</td>\n",
       "      <td>81.316421</td>\n",
       "      <td>53.513884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>$3,022,020.00</td>\n",
       "      <td>$652.00</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>66.752967</td>\n",
       "      <td>80.862999</td>\n",
       "      <td>53.527508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>$3,094,650.00</td>\n",
       "      <td>$650.00</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>66.057551</td>\n",
       "      <td>81.222432</td>\n",
       "      <td>53.539172</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      School Type  Total Students Total School Budget  \\\n",
       "school_name                                                             \n",
       "Rodriguez High School    District            3999       $2,547,363.00   \n",
       "Figueroa High School     District            2949       $1,884,411.00   \n",
       "Huang High School        District            2917       $1,910,635.00   \n",
       "Hernandez High School    District            4635       $3,022,020.00   \n",
       "Johnson High School      District            4761       $3,094,650.00   \n",
       "\n",
       "                      Per Student Budget  Average Math Score  \\\n",
       "school_name                                                    \n",
       "Rodriguez High School            $637.00           76.842711   \n",
       "Figueroa High School             $639.00           76.711767   \n",
       "Huang High School                $655.00           76.629414   \n",
       "Hernandez High School            $652.00           77.289752   \n",
       "Johnson High School              $650.00           77.072464   \n",
       "\n",
       "                       Average Reading Score  % Passing Math  \\\n",
       "school_name                                                    \n",
       "Rodriguez High School              80.744686       66.366592   \n",
       "Figueroa High School               81.158020       65.988471   \n",
       "Huang High School                  81.182722       65.683922   \n",
       "Hernandez High School              80.934412       66.752967   \n",
       "Johnson High School                80.966394       66.057551   \n",
       "\n",
       "                       % Passing Reading  % Overall Passing  \n",
       "school_name                                                  \n",
       "Rodriguez High School          80.220055          52.988247  \n",
       "Figueroa High School           80.739234          53.204476  \n",
       "Huang High School              81.316421          53.513884  \n",
       "Hernandez High School          80.862999          53.527508  \n",
       "Johnson High School            81.222432          53.539172  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bottom_schools = per_school_summary_df.sort_values(['% Overall Passing'])\n",
    "bottom_schools.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "3a9dc5c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a grade level DataFrames.\n",
    "ninth_graders = school_data_complete_df[(school_data_complete_df[\"grade\"] == \"9th\")]\n",
    "\n",
    "tenth_graders = school_data_complete_df[(school_data_complete_df[\"grade\"] == \"10th\")]\n",
    "\n",
    "eleventh_graders = school_data_complete_df[(school_data_complete_df[\"grade\"] == \"11th\")]\n",
    "\n",
    "twelfth_graders = school_data_complete_df[(school_data_complete_df[\"grade\"] == \"12th\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "86ffcdfe",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Group each grade level DataFrame by the school name for the average math score.\n",
    "ninth_grade_math_scores = ninth_graders.groupby([\"school_name\"]).mean()[\"math_score\"]\n",
    "\n",
    "tenth_grade_math_scores = tenth_graders.groupby([\"school_name\"]).mean()[\"math_score\"]\n",
    "\n",
    "eleventh_grade_math_scores = eleventh_graders.groupby([\"school_name\"]).mean()[\"math_score\"]\n",
    "\n",
    "twelfth_grade_math_scores = twelfth_graders.groupby([\"school_name\"]).mean()[\"math_score\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "d2964aa9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Group each grade level DataFrame by the school name for the average reading score.\n",
    "ninth_grade_reading_scores = ninth_graders.groupby([\"school_name\"]).mean()[\"reading_score\"]\n",
    "\n",
    "tenth_grade_reading_scores = tenth_graders.groupby([\"school_name\"]).mean()[\"reading_score\"]\n",
    "\n",
    "eleventh_grade_reading_scores = eleventh_graders.groupby([\"school_name\"]).mean()[\"reading_score\"]\n",
    "\n",
    "twelfth_grade_reading_scores = twelfth_graders.groupby([\"school_name\"]).mean()[\"reading_score\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "cc23f9f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "school_name\n",
       "Bailey High School       80.912451\n",
       "Cabrera High School      84.287958\n",
       "Figueroa High School     81.384863\n",
       "Ford High School         80.662338\n",
       "Griffin High School      84.013699\n",
       "Hernandez High School    80.857143\n",
       "Holden High School       84.698795\n",
       "Huang High School        80.305983\n",
       "Johnson High School      81.227564\n",
       "Pena High School         84.591160\n",
       "Rodriguez High School    80.376426\n",
       "Shelton High School      82.781671\n",
       "Thomas High School       83.831361\n",
       "Wilson High School       84.317673\n",
       "Wright High School       84.073171\n",
       "Name: reading_score, dtype: float64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twelfth_grade_reading_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "331b4d73",
   "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>9th</th>\n",
       "      <th>10th</th>\n",
       "      <th>11th</th>\n",
       "      <th>12th</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>77.083676</td>\n",
       "      <td>76.996772</td>\n",
       "      <td>77.515588</td>\n",
       "      <td>76.492218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>83.094697</td>\n",
       "      <td>83.154506</td>\n",
       "      <td>82.765560</td>\n",
       "      <td>83.277487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>76.403037</td>\n",
       "      <td>76.539974</td>\n",
       "      <td>76.884344</td>\n",
       "      <td>77.151369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>77.361345</td>\n",
       "      <td>77.672316</td>\n",
       "      <td>76.918058</td>\n",
       "      <td>76.179963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>82.044010</td>\n",
       "      <td>84.229064</td>\n",
       "      <td>83.842105</td>\n",
       "      <td>83.356164</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            9th       10th       11th       12th\n",
       "school_name                                                     \n",
       "Bailey High School    77.083676  76.996772  77.515588  76.492218\n",
       "Cabrera High School   83.094697  83.154506  82.765560  83.277487\n",
       "Figueroa High School  76.403037  76.539974  76.884344  77.151369\n",
       "Ford High School      77.361345  77.672316  76.918058  76.179963\n",
       "Griffin High School   82.044010  84.229064  83.842105  83.356164"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "math_scores_by_grade = pd.DataFrame({\n",
    "                \"9th\": ninth_grade_math_scores,\n",
    "               \"10th\": tenth_grade_math_scores,\n",
    "               \"11th\": eleventh_grade_math_scores,\n",
    "               \"12th\": twelfth_grade_math_scores\n",
    "})\n",
    "\n",
    "math_scores_by_grade.head()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "cbc33125",
   "metadata": {},
   "source": [
    "# Combine each grade level Series for average reading scores by school into a single DataFrame.\n",
    "reading_scores_by_grade = pd.DataFrame({\n",
    "              \"9th\": ninth_grade_reading_scores,\n",
    "              \"10th\": tenth_grade_reading_scores,\n",
    "              \"11th\": eleventh_grade_reading_scores,\n",
    "              \"12th\": twelfth_grade_reading_scores})\n",
    "\n",
    "reading_scores_by_grade.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "987a2273",
   "metadata": {},
   "outputs": [],
   "source": [
    "gradeLevels = ['9th','10th','11th','12th']\n",
    "\n",
    "for grade in gradeLevels:\n",
    "    math_scores_by_grade[grade] =  math_scores_by_grade[grade].map('{:,.1f}'.format)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "69719d16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>9th</th>\n",
       "      <th>10th</th>\n",
       "      <th>11th</th>\n",
       "      <th>12th</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>77.1</td>\n",
       "      <td>77.0</td>\n",
       "      <td>77.5</td>\n",
       "      <td>76.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>83.1</td>\n",
       "      <td>83.2</td>\n",
       "      <td>82.8</td>\n",
       "      <td>83.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>76.4</td>\n",
       "      <td>76.5</td>\n",
       "      <td>76.9</td>\n",
       "      <td>77.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>77.4</td>\n",
       "      <td>77.7</td>\n",
       "      <td>76.9</td>\n",
       "      <td>76.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>82.0</td>\n",
       "      <td>84.2</td>\n",
       "      <td>83.8</td>\n",
       "      <td>83.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       9th  10th  11th  12th\n",
       "Bailey High School    77.1  77.0  77.5  76.5\n",
       "Cabrera High School   83.1  83.2  82.8  83.3\n",
       "Figueroa High School  76.4  76.5  76.9  77.2\n",
       "Ford High School      77.4  77.7  76.9  76.2\n",
       "Griffin High School   82.0  84.2  83.8  83.4"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make sure the columns are in the correct order.\n",
    "math_scores_by_grade = math_scores_by_grade[\n",
    "                 [\"9th\", \"10th\", \"11th\", \"12th\"]]\n",
    "\n",
    "# Remove the index name.\n",
    "math_scores_by_grade.index.name = None\n",
    "# Display the DataFrame.\n",
    "math_scores_by_grade.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "4d1c0b25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     15.000000\n",
       "mean     620.066667\n",
       "std       28.544368\n",
       "min      578.000000\n",
       "25%      591.500000\n",
       "50%      628.000000\n",
       "75%      641.500000\n",
       "max      655.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "per_school_capita.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "5efcd41d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 585]      4\n",
       "(585, 630]    4\n",
       "(630, 645]    4\n",
       "(645, 675]    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Cut the per_school_capita into the spending ranges.\n",
    "spending_bins = [0, 585, 630, 645, 675]\n",
    "per_school_capita.groupby(pd.cut(per_school_capita, spending_bins)).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "32b04339",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the spending bins and group names.\n",
    "spending_bins = [0, 585, 630, 645, 675]\n",
    "group_names = [\"<$584\", \"$585-629\", \"$630-644\", \"$645-675\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "7bb235a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "      <th>Spending Ranges (Per Student)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Bailey High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>$3,124,928.00</td>\n",
       "      <td>$628.00</td>\n",
       "      <td>77.048432</td>\n",
       "      <td>81.033963</td>\n",
       "      <td>66.680064</td>\n",
       "      <td>81.933280</td>\n",
       "      <td>54.642283</td>\n",
       "      <td>$585-629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>$1,081,356.00</td>\n",
       "      <td>$582.00</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>94.133477</td>\n",
       "      <td>97.039828</td>\n",
       "      <td>91.334769</td>\n",
       "      <td>&lt;$584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>$1,884,411.00</td>\n",
       "      <td>$639.00</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "      <td>$630-644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>$1,763,916.00</td>\n",
       "      <td>$644.00</td>\n",
       "      <td>77.102592</td>\n",
       "      <td>80.746258</td>\n",
       "      <td>68.309602</td>\n",
       "      <td>79.299014</td>\n",
       "      <td>54.289887</td>\n",
       "      <td>$630-644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>$917,500.00</td>\n",
       "      <td>$625.00</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>93.392371</td>\n",
       "      <td>97.138965</td>\n",
       "      <td>90.599455</td>\n",
       "      <td>$585-629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>$3,022,020.00</td>\n",
       "      <td>$652.00</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>66.752967</td>\n",
       "      <td>80.862999</td>\n",
       "      <td>53.527508</td>\n",
       "      <td>$645-675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>427</td>\n",
       "      <td>$248,087.00</td>\n",
       "      <td>$581.00</td>\n",
       "      <td>83.803279</td>\n",
       "      <td>83.814988</td>\n",
       "      <td>92.505855</td>\n",
       "      <td>96.252927</td>\n",
       "      <td>89.227166</td>\n",
       "      <td>&lt;$584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>$1,910,635.00</td>\n",
       "      <td>$655.00</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>65.683922</td>\n",
       "      <td>81.316421</td>\n",
       "      <td>53.513884</td>\n",
       "      <td>$645-675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>$3,094,650.00</td>\n",
       "      <td>$650.00</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>66.057551</td>\n",
       "      <td>81.222432</td>\n",
       "      <td>53.539172</td>\n",
       "      <td>$645-675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>$585,858.00</td>\n",
       "      <td>$609.00</td>\n",
       "      <td>83.839917</td>\n",
       "      <td>84.044699</td>\n",
       "      <td>94.594595</td>\n",
       "      <td>95.945946</td>\n",
       "      <td>90.540541</td>\n",
       "      <td>$585-629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>$2,547,363.00</td>\n",
       "      <td>$637.00</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>66.366592</td>\n",
       "      <td>80.220055</td>\n",
       "      <td>52.988247</td>\n",
       "      <td>$630-644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>$1,056,600.00</td>\n",
       "      <td>$600.00</td>\n",
       "      <td>83.359455</td>\n",
       "      <td>83.725724</td>\n",
       "      <td>93.867121</td>\n",
       "      <td>95.854628</td>\n",
       "      <td>89.892107</td>\n",
       "      <td>$585-629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>$1,043,130.00</td>\n",
       "      <td>$638.00</td>\n",
       "      <td>83.418349</td>\n",
       "      <td>83.848930</td>\n",
       "      <td>93.272171</td>\n",
       "      <td>97.308869</td>\n",
       "      <td>90.948012</td>\n",
       "      <td>$630-644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>$1,319,574.00</td>\n",
       "      <td>$578.00</td>\n",
       "      <td>83.274201</td>\n",
       "      <td>83.989488</td>\n",
       "      <td>93.867718</td>\n",
       "      <td>96.539641</td>\n",
       "      <td>90.582567</td>\n",
       "      <td>&lt;$584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1800</td>\n",
       "      <td>$1,049,400.00</td>\n",
       "      <td>$583.00</td>\n",
       "      <td>83.682222</td>\n",
       "      <td>83.955000</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>96.611111</td>\n",
       "      <td>90.333333</td>\n",
       "      <td>&lt;$584</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      School Type  Total Students Total School Budget  \\\n",
       "school_name                                                             \n",
       "Bailey High School       District            4976       $3,124,928.00   \n",
       "Cabrera High School       Charter            1858       $1,081,356.00   \n",
       "Figueroa High School     District            2949       $1,884,411.00   \n",
       "Ford High School         District            2739       $1,763,916.00   \n",
       "Griffin High School       Charter            1468         $917,500.00   \n",
       "Hernandez High School    District            4635       $3,022,020.00   \n",
       "Holden High School        Charter             427         $248,087.00   \n",
       "Huang High School        District            2917       $1,910,635.00   \n",
       "Johnson High School      District            4761       $3,094,650.00   \n",
       "Pena High School          Charter             962         $585,858.00   \n",
       "Rodriguez High School    District            3999       $2,547,363.00   \n",
       "Shelton High School       Charter            1761       $1,056,600.00   \n",
       "Thomas High School        Charter            1635       $1,043,130.00   \n",
       "Wilson High School        Charter            2283       $1,319,574.00   \n",
       "Wright High School        Charter            1800       $1,049,400.00   \n",
       "\n",
       "                      Per Student Budget  Average Math Score  \\\n",
       "school_name                                                    \n",
       "Bailey High School               $628.00           77.048432   \n",
       "Cabrera High School              $582.00           83.061895   \n",
       "Figueroa High School             $639.00           76.711767   \n",
       "Ford High School                 $644.00           77.102592   \n",
       "Griffin High School              $625.00           83.351499   \n",
       "Hernandez High School            $652.00           77.289752   \n",
       "Holden High School               $581.00           83.803279   \n",
       "Huang High School                $655.00           76.629414   \n",
       "Johnson High School              $650.00           77.072464   \n",
       "Pena High School                 $609.00           83.839917   \n",
       "Rodriguez High School            $637.00           76.842711   \n",
       "Shelton High School              $600.00           83.359455   \n",
       "Thomas High School               $638.00           83.418349   \n",
       "Wilson High School               $578.00           83.274201   \n",
       "Wright High School               $583.00           83.682222   \n",
       "\n",
       "                       Average Reading Score  % Passing Math  \\\n",
       "school_name                                                    \n",
       "Bailey High School                 81.033963       66.680064   \n",
       "Cabrera High School                83.975780       94.133477   \n",
       "Figueroa High School               81.158020       65.988471   \n",
       "Ford High School                   80.746258       68.309602   \n",
       "Griffin High School                83.816757       93.392371   \n",
       "Hernandez High School              80.934412       66.752967   \n",
       "Holden High School                 83.814988       92.505855   \n",
       "Huang High School                  81.182722       65.683922   \n",
       "Johnson High School                80.966394       66.057551   \n",
       "Pena High School                   84.044699       94.594595   \n",
       "Rodriguez High School              80.744686       66.366592   \n",
       "Shelton High School                83.725724       93.867121   \n",
       "Thomas High School                 83.848930       93.272171   \n",
       "Wilson High School                 83.989488       93.867718   \n",
       "Wright High School                 83.955000       93.333333   \n",
       "\n",
       "                       % Passing Reading  % Overall Passing  \\\n",
       "school_name                                                   \n",
       "Bailey High School             81.933280          54.642283   \n",
       "Cabrera High School            97.039828          91.334769   \n",
       "Figueroa High School           80.739234          53.204476   \n",
       "Ford High School               79.299014          54.289887   \n",
       "Griffin High School            97.138965          90.599455   \n",
       "Hernandez High School          80.862999          53.527508   \n",
       "Holden High School             96.252927          89.227166   \n",
       "Huang High School              81.316421          53.513884   \n",
       "Johnson High School            81.222432          53.539172   \n",
       "Pena High School               95.945946          90.540541   \n",
       "Rodriguez High School          80.220055          52.988247   \n",
       "Shelton High School            95.854628          89.892107   \n",
       "Thomas High School             97.308869          90.948012   \n",
       "Wilson High School             96.539641          90.582567   \n",
       "Wright High School             96.611111          90.333333   \n",
       "\n",
       "                      Spending Ranges (Per Student)  \n",
       "school_name                                          \n",
       "Bailey High School                         $585-629  \n",
       "Cabrera High School                           <$584  \n",
       "Figueroa High School                       $630-644  \n",
       "Ford High School                           $630-644  \n",
       "Griffin High School                        $585-629  \n",
       "Hernandez High School                      $645-675  \n",
       "Holden High School                            <$584  \n",
       "Huang High School                          $645-675  \n",
       "Johnson High School                        $645-675  \n",
       "Pena High School                           $585-629  \n",
       "Rodriguez High School                      $630-644  \n",
       "Shelton High School                        $585-629  \n",
       "Thomas High School                         $630-644  \n",
       "Wilson High School                            <$584  \n",
       "Wright High School                            <$584  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Categorize spending based on the bins.\n",
    "per_school_summary_df[\"Spending Ranges (Per Student)\"] = pd.cut(per_school_capita, spending_bins, labels=group_names)\n",
    "\n",
    "per_school_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "86ad7375",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns.\n",
    "spending_math_scores = per_school_summary_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"Average Math Score\"]\n",
    "\n",
    "spending_reading_scores = per_school_summary_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"Average Reading Score\"]\n",
    "\n",
    "spending_passing_math = per_school_summary_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"% Passing Math\"]\n",
    "\n",
    "spending_passing_reading = per_school_summary_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"% Passing Reading\"]\n",
    "\n",
    "overall_passing_spending = per_school_summary_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"% Overall Passing\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "c2e45bd8",
   "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>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spending Ranges (Per Student)</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>&lt;$584</th>\n",
       "      <td>83.455399</td>\n",
       "      <td>83.933814</td>\n",
       "      <td>93.460096</td>\n",
       "      <td>96.610877</td>\n",
       "      <td>90.369459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$585-629</th>\n",
       "      <td>81.899826</td>\n",
       "      <td>83.155286</td>\n",
       "      <td>87.133538</td>\n",
       "      <td>92.718205</td>\n",
       "      <td>81.418596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$630-644</th>\n",
       "      <td>78.518855</td>\n",
       "      <td>81.624473</td>\n",
       "      <td>73.484209</td>\n",
       "      <td>84.391793</td>\n",
       "      <td>62.857656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$645-675</th>\n",
       "      <td>76.997210</td>\n",
       "      <td>81.027843</td>\n",
       "      <td>66.164813</td>\n",
       "      <td>81.133951</td>\n",
       "      <td>53.526855</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Average Math Score  Average Reading Score  \\\n",
       "Spending Ranges (Per Student)                                              \n",
       "<$584                                   83.455399              83.933814   \n",
       "$585-629                                81.899826              83.155286   \n",
       "$630-644                                78.518855              81.624473   \n",
       "$645-675                                76.997210              81.027843   \n",
       "\n",
       "                               % Passing Math  % Passing Reading  \\\n",
       "Spending Ranges (Per Student)                                      \n",
       "<$584                               93.460096          96.610877   \n",
       "$585-629                            87.133538          92.718205   \n",
       "$630-644                            73.484209          84.391793   \n",
       "$645-675                            66.164813          81.133951   \n",
       "\n",
       "                               % Overall Passing  \n",
       "Spending Ranges (Per Student)                     \n",
       "<$584                                  90.369459  \n",
       "$585-629                               81.418596  \n",
       "$630-644                               62.857656  \n",
       "$645-675                               53.526855  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Assemble into DataFrame.\n",
    "spending_summary_df = pd.DataFrame({\n",
    "          \"Average Math Score\" : spending_math_scores,\n",
    "          \"Average Reading Score\": spending_reading_scores,\n",
    "          \"% Passing Math\": spending_passing_math,\n",
    "          \"% Passing Reading\": spending_passing_reading,\n",
    "          \"% Overall Passing\": overall_passing_spending})\n",
    "\n",
    "spending_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "29725d14",
   "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>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spending Ranges (Per Student)</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>&lt;$584</th>\n",
       "      <td>83.5</td>\n",
       "      <td>83.9</td>\n",
       "      <td>93</td>\n",
       "      <td>97</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$585-629</th>\n",
       "      <td>81.9</td>\n",
       "      <td>83.2</td>\n",
       "      <td>87</td>\n",
       "      <td>93</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$630-644</th>\n",
       "      <td>78.5</td>\n",
       "      <td>81.6</td>\n",
       "      <td>73</td>\n",
       "      <td>84</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$645-675</th>\n",
       "      <td>77.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>66</td>\n",
       "      <td>81</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              Average Math Score Average Reading Score  \\\n",
       "Spending Ranges (Per Student)                                            \n",
       "<$584                                       83.5                  83.9   \n",
       "$585-629                                    81.9                  83.2   \n",
       "$630-644                                    78.5                  81.6   \n",
       "$645-675                                    77.0                  81.0   \n",
       "\n",
       "                              % Passing Math % Passing Reading  \\\n",
       "Spending Ranges (Per Student)                                    \n",
       "<$584                                     93                97   \n",
       "$585-629                                  87                93   \n",
       "$630-644                                  73                84   \n",
       "$645-675                                  66                81   \n",
       "\n",
       "                              % Overall Passing  \n",
       "Spending Ranges (Per Student)                    \n",
       "<$584                                        90  \n",
       "$585-629                                     81  \n",
       "$630-644                                     63  \n",
       "$645-675                                     54  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Formatting\n",
    "spending_summary_df[\"Average Math Score\"] = spending_summary_df[\"Average Math Score\"].map(\"{:.1f}\".format)\n",
    "\n",
    "spending_summary_df[\"Average Reading Score\"] = spending_summary_df[\"Average Reading Score\"].map(\"{:.1f}\".format)\n",
    "\n",
    "spending_summary_df[\"% Passing Math\"] = spending_summary_df[\"% Passing Math\"].map(\"{:.0f}\".format)\n",
    "\n",
    "spending_summary_df[\"% Passing Reading\"] = spending_summary_df[\"% Passing Reading\"].map(\"{:.0f}\".format)\n",
    "\n",
    "spending_summary_df[\"% Overall Passing\"] = spending_summary_df[\"% Overall Passing\"].map(\"{:.0f}\".format)\n",
    "\n",
    "spending_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "6ba90e81",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the bins.\n",
    "size_bins = [0, 1000, 2000, 5000]\n",
    "group_names = [\"Small (<1000)\", \"Medium (1000-2000)\", \"Large (2000-5000)\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "023ccf2f",
   "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>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "      <th>Spending Ranges (Per Student)</th>\n",
       "      <th>School Size</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Bailey High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>$3,124,928.00</td>\n",
       "      <td>$628.00</td>\n",
       "      <td>77.048432</td>\n",
       "      <td>81.033963</td>\n",
       "      <td>66.680064</td>\n",
       "      <td>81.933280</td>\n",
       "      <td>54.642283</td>\n",
       "      <td>$585-629</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>$1,081,356.00</td>\n",
       "      <td>$582.00</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>94.133477</td>\n",
       "      <td>97.039828</td>\n",
       "      <td>91.334769</td>\n",
       "      <td>&lt;$584</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>$1,884,411.00</td>\n",
       "      <td>$639.00</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "      <td>$630-644</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>$1,763,916.00</td>\n",
       "      <td>$644.00</td>\n",
       "      <td>77.102592</td>\n",
       "      <td>80.746258</td>\n",
       "      <td>68.309602</td>\n",
       "      <td>79.299014</td>\n",
       "      <td>54.289887</td>\n",
       "      <td>$630-644</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>$917,500.00</td>\n",
       "      <td>$625.00</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>93.392371</td>\n",
       "      <td>97.138965</td>\n",
       "      <td>90.599455</td>\n",
       "      <td>$585-629</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>$3,022,020.00</td>\n",
       "      <td>$652.00</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>66.752967</td>\n",
       "      <td>80.862999</td>\n",
       "      <td>53.527508</td>\n",
       "      <td>$645-675</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>427</td>\n",
       "      <td>$248,087.00</td>\n",
       "      <td>$581.00</td>\n",
       "      <td>83.803279</td>\n",
       "      <td>83.814988</td>\n",
       "      <td>92.505855</td>\n",
       "      <td>96.252927</td>\n",
       "      <td>89.227166</td>\n",
       "      <td>&lt;$584</td>\n",
       "      <td>Small (&lt;1000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>$1,910,635.00</td>\n",
       "      <td>$655.00</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>65.683922</td>\n",
       "      <td>81.316421</td>\n",
       "      <td>53.513884</td>\n",
       "      <td>$645-675</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>$3,094,650.00</td>\n",
       "      <td>$650.00</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>66.057551</td>\n",
       "      <td>81.222432</td>\n",
       "      <td>53.539172</td>\n",
       "      <td>$645-675</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>$585,858.00</td>\n",
       "      <td>$609.00</td>\n",
       "      <td>83.839917</td>\n",
       "      <td>84.044699</td>\n",
       "      <td>94.594595</td>\n",
       "      <td>95.945946</td>\n",
       "      <td>90.540541</td>\n",
       "      <td>$585-629</td>\n",
       "      <td>Small (&lt;1000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>$2,547,363.00</td>\n",
       "      <td>$637.00</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>66.366592</td>\n",
       "      <td>80.220055</td>\n",
       "      <td>52.988247</td>\n",
       "      <td>$630-644</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>$1,056,600.00</td>\n",
       "      <td>$600.00</td>\n",
       "      <td>83.359455</td>\n",
       "      <td>83.725724</td>\n",
       "      <td>93.867121</td>\n",
       "      <td>95.854628</td>\n",
       "      <td>89.892107</td>\n",
       "      <td>$585-629</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>$1,043,130.00</td>\n",
       "      <td>$638.00</td>\n",
       "      <td>83.418349</td>\n",
       "      <td>83.848930</td>\n",
       "      <td>93.272171</td>\n",
       "      <td>97.308869</td>\n",
       "      <td>90.948012</td>\n",
       "      <td>$630-644</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>$1,319,574.00</td>\n",
       "      <td>$578.00</td>\n",
       "      <td>83.274201</td>\n",
       "      <td>83.989488</td>\n",
       "      <td>93.867718</td>\n",
       "      <td>96.539641</td>\n",
       "      <td>90.582567</td>\n",
       "      <td>&lt;$584</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1800</td>\n",
       "      <td>$1,049,400.00</td>\n",
       "      <td>$583.00</td>\n",
       "      <td>83.682222</td>\n",
       "      <td>83.955000</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>96.611111</td>\n",
       "      <td>90.333333</td>\n",
       "      <td>&lt;$584</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      School Type  Total Students Total School Budget  \\\n",
       "school_name                                                             \n",
       "Bailey High School       District            4976       $3,124,928.00   \n",
       "Cabrera High School       Charter            1858       $1,081,356.00   \n",
       "Figueroa High School     District            2949       $1,884,411.00   \n",
       "Ford High School         District            2739       $1,763,916.00   \n",
       "Griffin High School       Charter            1468         $917,500.00   \n",
       "Hernandez High School    District            4635       $3,022,020.00   \n",
       "Holden High School        Charter             427         $248,087.00   \n",
       "Huang High School        District            2917       $1,910,635.00   \n",
       "Johnson High School      District            4761       $3,094,650.00   \n",
       "Pena High School          Charter             962         $585,858.00   \n",
       "Rodriguez High School    District            3999       $2,547,363.00   \n",
       "Shelton High School       Charter            1761       $1,056,600.00   \n",
       "Thomas High School        Charter            1635       $1,043,130.00   \n",
       "Wilson High School        Charter            2283       $1,319,574.00   \n",
       "Wright High School        Charter            1800       $1,049,400.00   \n",
       "\n",
       "                      Per Student Budget  Average Math Score  \\\n",
       "school_name                                                    \n",
       "Bailey High School               $628.00           77.048432   \n",
       "Cabrera High School              $582.00           83.061895   \n",
       "Figueroa High School             $639.00           76.711767   \n",
       "Ford High School                 $644.00           77.102592   \n",
       "Griffin High School              $625.00           83.351499   \n",
       "Hernandez High School            $652.00           77.289752   \n",
       "Holden High School               $581.00           83.803279   \n",
       "Huang High School                $655.00           76.629414   \n",
       "Johnson High School              $650.00           77.072464   \n",
       "Pena High School                 $609.00           83.839917   \n",
       "Rodriguez High School            $637.00           76.842711   \n",
       "Shelton High School              $600.00           83.359455   \n",
       "Thomas High School               $638.00           83.418349   \n",
       "Wilson High School               $578.00           83.274201   \n",
       "Wright High School               $583.00           83.682222   \n",
       "\n",
       "                       Average Reading Score  % Passing Math  \\\n",
       "school_name                                                    \n",
       "Bailey High School                 81.033963       66.680064   \n",
       "Cabrera High School                83.975780       94.133477   \n",
       "Figueroa High School               81.158020       65.988471   \n",
       "Ford High School                   80.746258       68.309602   \n",
       "Griffin High School                83.816757       93.392371   \n",
       "Hernandez High School              80.934412       66.752967   \n",
       "Holden High School                 83.814988       92.505855   \n",
       "Huang High School                  81.182722       65.683922   \n",
       "Johnson High School                80.966394       66.057551   \n",
       "Pena High School                   84.044699       94.594595   \n",
       "Rodriguez High School              80.744686       66.366592   \n",
       "Shelton High School                83.725724       93.867121   \n",
       "Thomas High School                 83.848930       93.272171   \n",
       "Wilson High School                 83.989488       93.867718   \n",
       "Wright High School                 83.955000       93.333333   \n",
       "\n",
       "                       % Passing Reading  % Overall Passing  \\\n",
       "school_name                                                   \n",
       "Bailey High School             81.933280          54.642283   \n",
       "Cabrera High School            97.039828          91.334769   \n",
       "Figueroa High School           80.739234          53.204476   \n",
       "Ford High School               79.299014          54.289887   \n",
       "Griffin High School            97.138965          90.599455   \n",
       "Hernandez High School          80.862999          53.527508   \n",
       "Holden High School             96.252927          89.227166   \n",
       "Huang High School              81.316421          53.513884   \n",
       "Johnson High School            81.222432          53.539172   \n",
       "Pena High School               95.945946          90.540541   \n",
       "Rodriguez High School          80.220055          52.988247   \n",
       "Shelton High School            95.854628          89.892107   \n",
       "Thomas High School             97.308869          90.948012   \n",
       "Wilson High School             96.539641          90.582567   \n",
       "Wright High School             96.611111          90.333333   \n",
       "\n",
       "                      Spending Ranges (Per Student)         School Size  \n",
       "school_name                                                              \n",
       "Bailey High School                         $585-629   Large (2000-5000)  \n",
       "Cabrera High School                           <$584  Medium (1000-2000)  \n",
       "Figueroa High School                       $630-644   Large (2000-5000)  \n",
       "Ford High School                           $630-644   Large (2000-5000)  \n",
       "Griffin High School                        $585-629  Medium (1000-2000)  \n",
       "Hernandez High School                      $645-675   Large (2000-5000)  \n",
       "Holden High School                            <$584       Small (<1000)  \n",
       "Huang High School                          $645-675   Large (2000-5000)  \n",
       "Johnson High School                        $645-675   Large (2000-5000)  \n",
       "Pena High School                           $585-629       Small (<1000)  \n",
       "Rodriguez High School                      $630-644   Large (2000-5000)  \n",
       "Shelton High School                        $585-629  Medium (1000-2000)  \n",
       "Thomas High School                         $630-644  Medium (1000-2000)  \n",
       "Wilson High School                            <$584   Large (2000-5000)  \n",
       "Wright High School                            <$584  Medium (1000-2000)  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Categorize spending based on the bins.\n",
    "per_school_summary_df[\"School Size\"] = pd.cut(per_school_summary_df[\"Total Students\"], size_bins, labels=group_names)\n",
    "\n",
    "per_school_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "d9879195",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns.\n",
    "size_math_scores = per_school_summary_df.groupby([\"School Size\"]).mean()[\"Average Math Score\"]\n",
    "\n",
    "size_reading_scores = per_school_summary_df.groupby([\"School Size\"]).mean()[\"Average Reading Score\"]\n",
    "\n",
    "size_passing_math = per_school_summary_df.groupby([\"School Size\"]).mean()[\"% Passing Math\"]\n",
    "\n",
    "size_passing_reading = per_school_summary_df.groupby([\"School Size\"]).mean()[\"% Passing Reading\"]\n",
    "\n",
    "size_overall_passing = per_school_summary_df.groupby([\"School Size\"]).mean()[\"% Overall Passing\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "25237f45",
   "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>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>School Size</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>Small (&lt;1000)</th>\n",
       "      <td>83.821598</td>\n",
       "      <td>83.929843</td>\n",
       "      <td>93.550225</td>\n",
       "      <td>96.099437</td>\n",
       "      <td>89.883853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Medium (1000-2000)</th>\n",
       "      <td>83.374684</td>\n",
       "      <td>83.864438</td>\n",
       "      <td>93.599695</td>\n",
       "      <td>96.790680</td>\n",
       "      <td>90.621535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Large (2000-5000)</th>\n",
       "      <td>77.746417</td>\n",
       "      <td>81.344493</td>\n",
       "      <td>69.963361</td>\n",
       "      <td>82.766634</td>\n",
       "      <td>58.286003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Average Math Score  Average Reading Score  % Passing Math  \\\n",
       "School Size                                                                     \n",
       "Small (<1000)                83.821598              83.929843       93.550225   \n",
       "Medium (1000-2000)           83.374684              83.864438       93.599695   \n",
       "Large (2000-5000)            77.746417              81.344493       69.963361   \n",
       "\n",
       "                    % Passing Reading  % Overall Passing  \n",
       "School Size                                               \n",
       "Small (<1000)               96.099437          89.883853  \n",
       "Medium (1000-2000)          96.790680          90.621535  \n",
       "Large (2000-5000)           82.766634          58.286003  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Assemble into DataFrame.\n",
    "size_summary_df = pd.DataFrame({\n",
    "          \"Average Math Score\" : size_math_scores,\n",
    "          \"Average Reading Score\": size_reading_scores,\n",
    "          \"% Passing Math\": size_passing_math,\n",
    "          \"% Passing Reading\": size_passing_reading,\n",
    "          \"% Overall Passing\": size_overall_passing})\n",
    "\n",
    "size_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "68e830b0",
   "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>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>School Size</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>Small (&lt;1000)</th>\n",
       "      <td>83.8</td>\n",
       "      <td>83.9</td>\n",
       "      <td>94</td>\n",
       "      <td>96</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Medium (1000-2000)</th>\n",
       "      <td>83.4</td>\n",
       "      <td>83.9</td>\n",
       "      <td>94</td>\n",
       "      <td>97</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Large (2000-5000)</th>\n",
       "      <td>77.7</td>\n",
       "      <td>81.3</td>\n",
       "      <td>70</td>\n",
       "      <td>83</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Average Math Score Average Reading Score % Passing Math  \\\n",
       "School Size                                                                  \n",
       "Small (<1000)                    83.8                  83.9             94   \n",
       "Medium (1000-2000)               83.4                  83.9             94   \n",
       "Large (2000-5000)                77.7                  81.3             70   \n",
       "\n",
       "                   % Passing Reading % Overall Passing  \n",
       "School Size                                             \n",
       "Small (<1000)                     96                90  \n",
       "Medium (1000-2000)                97                91  \n",
       "Large (2000-5000)                 83                58  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Formatting.\n",
    "size_summary_df[\"Average Math Score\"] = size_summary_df[\"Average Math Score\"].map(\"{:.1f}\".format)\n",
    "\n",
    "size_summary_df[\"Average Reading Score\"] = size_summary_df[\"Average Reading Score\"].map(\"{:.1f}\".format)\n",
    "\n",
    "size_summary_df[\"% Passing Math\"] = size_summary_df[\"% Passing Math\"].map(\"{:.0f}\".format)\n",
    "\n",
    "size_summary_df[\"% Passing Reading\"] = size_summary_df[\"% Passing Reading\"].map(\"{:.0f}\".format)\n",
    "\n",
    "size_summary_df[\"% Overall Passing\"] = size_summary_df[\"% Overall Passing\"].map(\"{:.0f}\".format)\n",
    "\n",
    "size_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "c5521dbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns.\n",
    "type_math_scores = per_school_summary_df.groupby([\"School Type\"]).mean()[\"Average Math Score\"]\n",
    "\n",
    "type_reading_scores = per_school_summary_df.groupby([\"School Type\"]).mean()[\"Average Reading Score\"]\n",
    "\n",
    "type_passing_math = per_school_summary_df.groupby([\"School Type\"]).mean()[\"% Passing Math\"]\n",
    "\n",
    "type_passing_reading = per_school_summary_df.groupby([\"School Type\"]).mean()[\"% Passing Reading\"]\n",
    "\n",
    "type_overall_passing = per_school_summary_df.groupby([\"School Type\"]).mean()[\"% Overall Passing\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5f0f9099",
   "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>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>School Type</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>Charter</th>\n",
       "      <td>83.473852</td>\n",
       "      <td>83.896421</td>\n",
       "      <td>93.620830</td>\n",
       "      <td>96.586489</td>\n",
       "      <td>90.432244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District</th>\n",
       "      <td>76.956733</td>\n",
       "      <td>80.966636</td>\n",
       "      <td>66.548453</td>\n",
       "      <td>80.799062</td>\n",
       "      <td>53.672208</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Average Math Score  Average Reading Score  % Passing Math  \\\n",
       "School Type                                                              \n",
       "Charter               83.473852              83.896421       93.620830   \n",
       "District              76.956733              80.966636       66.548453   \n",
       "\n",
       "             % Passing Reading  % Overall Passing  \n",
       "School Type                                        \n",
       "Charter              96.586489          90.432244  \n",
       "District             80.799062          53.672208  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Assemble into DataFrame.\n",
    "type_summary_df = pd.DataFrame({\n",
    "          \"Average Math Score\" : type_math_scores,\n",
    "          \"Average Reading Score\": type_reading_scores,\n",
    "          \"% Passing Math\": type_passing_math,\n",
    "          \"% Passing Reading\": type_passing_reading,\n",
    "          \"% Overall Passing\": type_overall_passing})\n",
    "\n",
    "type_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "daef8a86",
   "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>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>School Type</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>Charter</th>\n",
       "      <td>83.5</td>\n",
       "      <td>83.9</td>\n",
       "      <td>94</td>\n",
       "      <td>97</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District</th>\n",
       "      <td>77.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>67</td>\n",
       "      <td>81</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Average Math Score Average Reading Score % Passing Math  \\\n",
       "School Type                                                           \n",
       "Charter                   83.5                  83.9             94   \n",
       "District                  77.0                  81.0             67   \n",
       "\n",
       "            % Passing Reading % Overall Passing  \n",
       "School Type                                      \n",
       "Charter                    97                90  \n",
       "District                   81                54  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Formatting\n",
    "type_summary_df[\"Average Math Score\"] = type_summary_df[\"Average Math Score\"].map(\"{:.1f}\".format)\n",
    "\n",
    "type_summary_df[\"Average Reading Score\"] = type_summary_df[\"Average Reading Score\"].map(\"{:.1f}\".format)\n",
    "\n",
    "type_summary_df[\"% Passing Math\"] = type_summary_df[\"% Passing Math\"].map(\"{:.0f}\".format)\n",
    "\n",
    "type_summary_df[\"% Passing Reading\"] = type_summary_df[\"% Passing Reading\"].map(\"{:.0f}\".format)\n",
    "\n",
    "type_summary_df[\"% Overall Passing\"] = type_summary_df[\"% Overall Passing\"].map(\"{:.0f}\".format)\n",
    "\n",
    "type_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "48d8a3f9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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