PyCitySchools_replaced_THS grades.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "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": 4,
     "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",
   "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": 37,
   "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": 54,
   "metadata": {
    "scrolled": true
   },
   "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[(student_data_df[\"grade\"] == \"9th\") & (student_data_df[\"school_name\"] == \"Thomas High School\"), \"reading_score\"] = np.nan\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>66.0</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>94.0</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>90.0</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>67.0</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>97.0</td>\n",
       "      <td>84</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",
       "    </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>99.0</td>\n",
       "      <td>90</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>95.0</td>\n",
       "      <td>70</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>NaN</td>\n",
       "      <td>84</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>99.0</td>\n",
       "      <td>90</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>95.0</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<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               66.0          79  \n",
       "1               94.0          61  \n",
       "2               90.0          60  \n",
       "3               67.0          58  \n",
       "4               97.0          84  \n",
       "...              ...         ...  \n",
       "39165           99.0          90  \n",
       "39166           95.0          70  \n",
       "39167            NaN          84  \n",
       "39168           99.0          90  \n",
       "39169           95.0          75  \n",
       "\n",
       "[39170 rows x 7 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student_data_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "#  Step 3. Refactor the code in Step 2 to replace the math scores with NaN.\n",
    "student_data_df.loc[(student_data_df[\"grade\"] == \"9th\") & (student_data_df[\"school_name\"] == \"Thomas High School\"), \"math_score\"] = np.nan\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>66.0</td>\n",
       "      <td>79.0</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>94.0</td>\n",
       "      <td>61.0</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>90.0</td>\n",
       "      <td>60.0</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>67.0</td>\n",
       "      <td>58.0</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>97.0</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </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>99.0</td>\n",
       "      <td>90.0</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>95.0</td>\n",
       "      <td>70.0</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>NaN</td>\n",
       "      <td>NaN</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>99.0</td>\n",
       "      <td>90.0</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>95.0</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<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               66.0        79.0  \n",
       "1               94.0        61.0  \n",
       "2               90.0        60.0  \n",
       "3               67.0        58.0  \n",
       "4               97.0        84.0  \n",
       "...              ...         ...  \n",
       "39165           99.0        90.0  \n",
       "39166           95.0        70.0  \n",
       "39167            NaN         NaN  \n",
       "39168           99.0        90.0  \n",
       "39169           95.0        75.0  \n",
       "\n",
       "[39170 rows x 7 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  Step 4. Check the student data for NaN's. \n",
    "\n",
    "student_data_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Deliverable 2 : Repeat the school district analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### District Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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",
       "      <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,
   "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,
   "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,
   "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,
   "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,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 3. Calculate the passing percentages with the new total student count.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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,
   "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",
   "metadata": {},
   "source": [
    "##  School Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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,
   "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,
   "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,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 5.  Get the number of 10th-12th graders from Thomas High School (THS).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 6. Get all the students passing math from THS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 7. Get all the students passing reading from THS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 8. Get all the students passing math and reading from THS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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,
   "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,
   "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,
   "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,
   "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,
   "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,
   "metadata": {},
   "outputs": [],
   "source": [
    "# per_school_summary_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## High and Low Performing Schools "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Sort and show top five schools.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sort and show top five schools.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Math and Reading Scores by Grade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine each Series for average math scores by school into single data frame.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine each Series for average reading scores by school into single data frame.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format each grade column.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove the index.\n",
    "\n",
    "\n",
    "# Display the data frame\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Remove the index.\n",
    "\n",
    "\n",
    "# Display the data frame\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scores by School Spending"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the DataFrame\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format the DataFrame \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scores by School Size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the bins.\n",
    "\n",
    "# Categorize spending based on the bins.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Assemble into DataFrame. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format the DataFrame  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scores by School Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate averages for the desired columns. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assemble into DataFrame. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Format the DataFrame \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Files to load\n",
    "school_data_to_load = \"Resources/schools_complete.csv\"\n",
    "student_data_to_load = \"Resources/students_complete.csv\"\n",
    "\n",
    "# files to load indirectly\n",
    "school_data = os.path.join(\"Resources\",\"school_complete.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "school_data_df= pd.read_csv(school_data_to_load)\n",
    "student_data_df= pd.read_csv(student_data_to_load)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>School ID</th>\n",
       "      <th>school_name</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>Huang High School</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>Figueroa High School</td>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>1884411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Shelton High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>1056600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Hernandez High School</td>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>3022020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Griffin High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>917500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   School ID            school_name      type  size   budget\n",
       "0          0      Huang High School  District  2917  1910635\n",
       "1          1   Figueroa High School  District  2949  1884411\n",
       "2          2    Shelton High School   Charter  1761  1056600\n",
       "3          3  Hernandez High School  District  4635  3022020\n",
       "4          4    Griffin High School   Charter  1468   917500"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_data_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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": 6,
     "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(student_data_to_load)\n",
    "student_data_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_data_df.count()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student_data_df.count()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student_data_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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\"]\n",
    "\n",
    "\n",
    "for word in prefixes_suffixes:\n",
    "    student_data_df[\"student_name\"] = student_data_df[\"student_name\"].str.replace(\"word\",\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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",
       "      <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>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",
       "      <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  \\\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  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  "
      ]
     },
     "execution_count": 11,
     "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.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "39170"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the total number of students.\n",
    "student_count = school_data_complete_df[\"Student ID\"].count()\n",
    "\n",
    "\n",
    "student_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the total number of schools\n",
    "school_count_2 = school_data_df[\"school_name\"].count()\n",
    "school_count_2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24649428"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#school_data_complete_df[\"budget\"].unique().sum()\n",
    "\n",
    "total_budget=school_data_df[\"budget\"].sum()\n",
    "total_budget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "81.87784018381414"
      ]
     },
     "execution_count": 15,
     "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": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "78.98537145774827"
      ]
     },
     "execution_count": 16,
     "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": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "passing_math= school_data_complete_df[\"math_score\"] >=70\n",
    "passing_reading= school_data_complete_df[\"reading_score\"] >= 70"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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",
       "      <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>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>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",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</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",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</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",
       "      <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",
       "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",
       "8           8   Michael Roth      M  10th  Huang High School             95   \n",
       "\n",
       "   math_score  School ID      type  size   budget  \n",
       "0          79          0  District  2917  1910635  \n",
       "4          84          0  District  2917  1910635  \n",
       "5          94          0  District  2917  1910635  \n",
       "6          80          0  District  2917  1910635  \n",
       "8          87          0  District  2917  1910635  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get all the students who are passing math in a new DataFrame.\n",
    "passing_math = school_data_complete_df[school_data_complete_df[\"math_score\"] >= 70]\n",
    "passing_math.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "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]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the number of students passing math.\n",
    "passing_math_count = passing_math[\"student_name\"].count()\n",
    "\n",
    "# Calculate the number of students passing reading.\n",
    "passing_reading_count = passing_reading[\"student_name\"].count()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "74.9808526933878\n",
      "85.80546336482001\n"
     ]
    }
   ],
   "source": [
    "# Calculate the percent that passed math.\n",
    "passing_math_percentage = passing_math_count / float(student_count) * 100\n",
    "\n",
    "# Calculate the percent that passed reading.\n",
    "passing_reading_percentage = passing_reading_count / float(student_count) * 100\n",
    "\n",
    "print(passing_math_percentage)\n",
    "print(passing_reading_percentage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>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>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",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</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",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</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",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</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",
       "      <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",
       "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",
       "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  School ID      type  size   budget  \n",
       "4          84          0  District  2917  1910635  \n",
       "5          94          0  District  2917  1910635  \n",
       "6          80          0  District  2917  1910635  \n",
       "8          87          0  District  2917  1910635  \n",
       "9          84          0  District  2917  1910635  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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) & \n",
    "                                               (school_data_complete_df[\"reading_score\"] >= 70)]\n",
    "\n",
    "passing_math_reading.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "overall_passing_math_reading_count = passing_math_reading[\"student_name\"].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65.17232575950983"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the overall passing percentage.\n",
    "overall_passing_percentage = overall_passing_math_reading_count / student_count * 100\n",
    "overall_passing_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>39170</td>\n",
       "      <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": [
    "# Adding a list of values with keys to create a new DataFrame.\n",
    "district_summary_df = pd.DataFrame(\n",
    "          [{\"Total Schools\": school_count_2,\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",
    "district_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    39,170\n",
       "Name: Total Students, dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 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",
    "\n",
    "district_summary_df[\"Total Students\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format \"Total Budget\" to have the comma for a thousands separator, a decimal separator, and a \"$\".\n",
    "\n",
    "district_summary_df[\"Total Budget\"] = district_summary_df[\"Total Budget\"].map(\"${:,.2f}\".format)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    $24,649,428.00\n",
       "Name: Total Budget, dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "district_summary_df[\"Total Budget\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Format the columns.\n",
    "district_summary_df[\"Average Math Score\"] = district_summary_df[\"Average Math Score\"].map(\"{:.1f}\".format)\n",
    "\n",
    "district_summary_df[\"Average Reading Score\"] = district_summary_df[\"Average Reading Score\"].map(\"{:.1f}\".format)\n",
    "\n",
    "district_summary_df[\"% Passing Math\"] = district_summary_df[\"% Passing Math\"].map(\"{:.0f}\".format)\n",
    "\n",
    "district_summary_df[\"% Passing Reading\"] = district_summary_df[\"% Passing Reading\"].map(\"{:.0f}\".format)\n",
    "\n",
    "district_summary_df[\"% Overall Passing\"] = district_summary_df[\"% Overall Passing\"].map(\"{:.0f}\".format)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total 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": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "district_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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": 31,
     "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": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add the per_school_types into a DataFrame for testing.\n",
    "df = pd.DataFrame(per_school_types)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     2917\n",
       "1     2949\n",
       "2     1761\n",
       "3     4635\n",
       "4     1468\n",
       "5     2283\n",
       "6     1858\n",
       "7     4976\n",
       "8      427\n",
       "9      962\n",
       "10    1800\n",
       "11    3999\n",
       "12    4761\n",
       "13    2739\n",
       "14    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[\"size\"]\n",
    "per_school_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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": 34,
     "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": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bailey High School       4976\n",
       "Johnson High School      4761\n",
       "Hernandez High School    4635\n",
       "Rodriguez High School    3999\n",
       "Figueroa High School     2949\n",
       "Huang High School        2917\n",
       "Ford High School         2739\n",
       "Wilson High School       2283\n",
       "Cabrera High School      1858\n",
       "Wright High School       1800\n",
       "Shelton High School      1761\n",
       "Thomas High School       1635\n",
       "Griffin High School      1468\n",
       "Pena High School          962\n",
       "Holden High School        427\n",
       "Name: school_name, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the total student count.\n",
    "per_school_counts = school_data_complete_df[\"school_name\"].value_counts()\n",
    "per_school_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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": 36,
     "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": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bailey High School       628.0\n",
       "Cabrera High School      582.0\n",
       "Figueroa High School     639.0\n",
       "Ford High School         644.0\n",
       "Griffin High School      625.0\n",
       "Hernandez High School    652.0\n",
       "Holden High School       581.0\n",
       "Huang High School        655.0\n",
       "Johnson High School      650.0\n",
       "Pena High School         609.0\n",
       "Rodriguez High School    637.0\n",
       "Shelton High School      600.0\n",
       "Thomas High School       638.0\n",
       "Wilson High School       578.0\n",
       "Wright High School       583.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 37,
     "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\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the math scores.\n",
    "student_school_math = student_data_df.set_index([\"school_name\"])[\"math_score\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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": 39,
     "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": 40,
   "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": 44,
   "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)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bailey High School       66.680064\n",
       "Cabrera High School      94.133477\n",
       "Figueroa High School     65.988471\n",
       "Ford High School         68.309602\n",
       "Griffin High School      93.392371\n",
       "Hernandez High School    66.752967\n",
       "Holden High School       92.505855\n",
       "Huang High School        65.683922\n",
       "Johnson High School      66.057551\n",
       "Pena High School         94.594595\n",
       "Rodriguez High School    66.366592\n",
       "Shelton High School      93.867121\n",
       "Thomas High School       93.272171\n",
       "Wilson High School       93.867718\n",
       "Wright High School       93.333333\n",
       "dtype: float64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "per_school_passing_math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>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>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",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</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",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</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",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</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",
       "      <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",
       "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",
       "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  School ID      type  size   budget  \n",
       "4          84          0  District  2917  1910635  \n",
       "5          94          0  District  2917  1910635  \n",
       "6          80          0  District  2917  1910635  \n",
       "8          87          0  District  2917  1910635  \n",
       "9          84          0  District  2917  1910635  "
      ]
     },
     "execution_count": 54,
     "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.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Calculate the overall passing percentage.\n",
    "per_overall_passing_percentage = per_passing_math_reading / per_school_counts * 100\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>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",
       "  </thead>\n",
       "  <tbody>\n",
       "    <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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     School Type  Total Students  Total School Budget  \\\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",
       "\n",
       "                      Per Student Budget  Average Math Score  \\\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",
       "\n",
       "                      Average Reading Score  % Passing Math  \\\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",
       "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": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adding a list of values with keys to create a new DataFrame.\n",
    "\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",
    "per_school_summary_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "  </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",
       "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",
       "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             $625.00           83.351499   \n",
       "\n",
       "                      Average Reading Score  % Passing Math  \\\n",
       "Bailey High School                81.033963       66.680064   \n",
       "Cabrera High School               83.975780       94.133477   \n",
       "Figueroa High School              81.158020       65.988471   \n",
       "Ford High School                  80.746258       68.309602   \n",
       "Griffin High School               83.816757       93.392371   \n",
       "\n",
       "                      % Passing Reading  % Overall Passing  \n",
       "Bailey High School            81.933280          54.642283  \n",
       "Cabrera High School           97.039828          91.334769  \n",
       "Figueroa High School          80.739234          53.204476  \n",
       "Ford High School              79.299014          54.289887  \n",
       "Griffin High School           97.138965          90.599455  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Format the Total School Budget and the Per Student Budget columns.\n",
    "per_school_summary_df[\"Total School Budget\"] = per_school_summary_df[\"Total School Budget\"].map(\"${:,.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": 59,
   "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>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",
       "  </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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    School Type  Total Students Total School Budget  \\\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",
       "\n",
       "                    Per Student Budget  Average Math Score  \\\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",
       "\n",
       "                     Average Reading Score  % Passing Math  % Passing Reading  \\\n",
       "Cabrera High School              83.975780       94.133477          97.039828   \n",
       "Thomas High School               83.848930       93.272171          97.308869   \n",
       "Griffin High School              83.816757       93.392371          97.138965   \n",
       "Wilson High School               83.989488       93.867718          96.539641   \n",
       "Pena High School                 84.044699       94.594595          95.945946   \n",
       "\n",
       "                     % Overall Passing  \n",
       "Cabrera High School          91.334769  \n",
       "Thomas High School           90.948012  \n",
       "Griffin High School          90.599455  \n",
       "Wilson High School           90.582567  \n",
       "Pena High School             90.540541  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sort and show top five schools.\n",
    "top_schools = per_school_summary_df.sort_values([\"% Overall Passing\"], ascending=False)\n",
    "\n",
    "top_schools.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>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",
       "  </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",
       "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",
       "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",
       "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",
       "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": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sort and show top five schools.\n",
    "bottom_schools = per_school_summary_df.sort_values([\"% Overall Passing\"], ascending=True)\n",
    "\n",
    "bottom_schools.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>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>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",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>Brittney Walker</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>64</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>13</th>\n",
       "      <td>13</td>\n",
       "      <td>William Long</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>71</td>\n",
       "      <td>79</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  \\\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",
       "12          12  Brittney Walker      F   9th  Huang High School   \n",
       "13          13     William Long      M   9th  Huang 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",
       "12             64          79          0  District  2917  1910635  \n",
       "13             71          79          0  District  2917  1910635  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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\")]\n",
    "\n",
    "ninth_graders.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "school_name\n",
       "Bailey High School       77.515588\n",
       "Cabrera High School      82.765560\n",
       "Figueroa High School     76.884344\n",
       "Ford High School         76.918058\n",
       "Griffin High School      83.842105\n",
       "Hernandez High School    77.136029\n",
       "Holden High School       85.000000\n",
       "Huang High School        76.446602\n",
       "Johnson High School      77.491653\n",
       "Pena High School         84.328125\n",
       "Rodriguez High School    76.395626\n",
       "Shelton High School      83.383495\n",
       "Thomas High School       83.498795\n",
       "Wilson High School       83.195326\n",
       "Wright High School       83.836782\n",
       "Name: math_score, dtype: float64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eleventh_grade_math_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "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\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "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": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twelfth_grade_reading_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "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>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": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combine each grade level Series for average math scores by school into a single DataFrame.\n",
    "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",
    "math_scores_by_grade.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "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>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>81.303155</td>\n",
       "      <td>80.907183</td>\n",
       "      <td>80.945643</td>\n",
       "      <td>80.912451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>83.676136</td>\n",
       "      <td>84.253219</td>\n",
       "      <td>83.788382</td>\n",
       "      <td>84.287958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>81.198598</td>\n",
       "      <td>81.408912</td>\n",
       "      <td>80.640339</td>\n",
       "      <td>81.384863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>80.632653</td>\n",
       "      <td>81.262712</td>\n",
       "      <td>80.403642</td>\n",
       "      <td>80.662338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>83.369193</td>\n",
       "      <td>83.706897</td>\n",
       "      <td>84.288089</td>\n",
       "      <td>84.013699</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            9th       10th       11th       12th\n",
       "school_name                                                     \n",
       "Bailey High School    81.303155  80.907183  80.945643  80.912451\n",
       "Cabrera High School   83.676136  84.253219  83.788382  84.287958\n",
       "Figueroa High School  81.198598  81.408912  80.640339  81.384863\n",
       "Ford High School      80.632653  81.262712  80.403642  80.662338\n",
       "Griffin High School   83.369193  83.706897  84.288089  84.013699"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read_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",
    "read_scores_by_grade.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "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>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": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " # Format each grade column.\n",
    "math_scores_by_grade[\"9th\"] = math_scores_by_grade[\"9th\"].map(\"{:.1f}\".format)\n",
    "\n",
    "math_scores_by_grade[\"10th\"] = math_scores_by_grade[\"10th\"].map(\"{:.1f}\".format)\n",
    "\n",
    "math_scores_by_grade[\"11th\"] = math_scores_by_grade[\"11th\"].map(\"{:.1f}\".format)\n",
    "\n",
    "math_scores_by_grade[\"12th\"] = math_scores_by_grade[\"12th\"].map(\"{:.1f}\".format)\n",
    "\n",
    "  # 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": 91,
   "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>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>81.3</td>\n",
       "      <td>80.9</td>\n",
       "      <td>80.9</td>\n",
       "      <td>80.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>83.7</td>\n",
       "      <td>84.3</td>\n",
       "      <td>83.8</td>\n",
       "      <td>84.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>81.2</td>\n",
       "      <td>81.4</td>\n",
       "      <td>80.6</td>\n",
       "      <td>81.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>80.6</td>\n",
       "      <td>81.3</td>\n",
       "      <td>80.4</td>\n",
       "      <td>80.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>83.4</td>\n",
       "      <td>83.7</td>\n",
       "      <td>84.3</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       9th  10th  11th  12th\n",
       "Bailey High School    81.3  80.9  80.9  80.9\n",
       "Cabrera High School   83.7  84.3  83.8  84.3\n",
       "Figueroa High School  81.2  81.4  80.6  81.4\n",
       "Ford High School      80.6  81.3  80.4  80.7\n",
       "Griffin High School   83.4  83.7  84.3  84.0"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read_scores_by_grade[\"9th\"] = read_scores_by_grade[\"9th\"].map(\"{:.1f}\".format)\n",
    "\n",
    "read_scores_by_grade[\"10th\"] = read_scores_by_grade[\"10th\"].map(\"{:.1f}\".format)\n",
    "\n",
    "read_scores_by_grade[\"11th\"] = read_scores_by_grade[\"11th\"].map(\"{:.1f}\".format)\n",
    "\n",
    "read_scores_by_grade[\"12th\"] = read_scores_by_grade[\"12th\"].map(\"{:.1f}\".format)\n",
    "\n",
    "read_scores_by_grade.index.name = None\n",
    "\n",
    "read_scores_by_grade.head()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "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": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the descriptive statistics for the per_school_capita.\n",
    "per_school_capita.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cut the per_school_capita into the spending ranges.\n",
    "spending_bins = [0, 585, 630, 645, 675]\n",
    "x=pd.cut(per_school_capita, spending_bins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "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": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "per_school_capita.groupby(x).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the spending bins and group names.\n",
    "spending_bins = [0, 585, 630, 645, 675]\n",
    "\n",
    "group_names = [\"<$584\", \"$585-629\", \"$630-644\", \"$645-675\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "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>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",
       "  </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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     School Type  Total Students Total School Budget  \\\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",
       "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",
       "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",
       "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",
       "\n",
       "                     Spending Ranges (Per Student)  \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  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "per_school_summary_df[\"Spending Ranges (Per Student)\"]= pd.cut(per_school_capita, spending_bins, labels = group_names)\n",
    "per_school_summary_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Spending Ranges (Per Student)\n",
       "<$584       90.369459\n",
       "$585-629    81.418596\n",
       "$630-644    62.857656\n",
       "$645-675    53.526855\n",
       "Name: % Overall Passing, dtype: float64"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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",
    "\n",
    "overall_passing_spending"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "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": 116,
     "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": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spending_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Establish the bins\n",
    "size_bins = [0,1000,2000,5000]\n",
    "group_names = [\"Small(<1000)\" , \"Medium(1000-2000)\",\"Large(2000-5000)\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "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>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",
       "  </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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     School Type  Total Students Total School Budget  \\\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",
       "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",
       "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",
       "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",
       "\n",
       "                     Spending Ranges (Per Student)        School Size  \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)  "
      ]
     },
     "execution_count": 130,
     "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.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "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": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "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})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "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": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Size_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "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",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Size_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "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": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "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",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "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": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type_summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "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": 168,
     "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,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "PythonData",
   "language": "python",
   "name": "pythondata"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}