Pyber_r0.3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2bfb388e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add Matplotlib inline magic command\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# Dependencies and Setup\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy.stats as sts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0447b721",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Files to load\n",
    "\n",
    "city_data_to_load = \"Resources/city_data.csv\"\n",
    "ride_data_to_load = \"Resources/ride_data.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fe411417",
   "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>city</th>\n",
       "      <th>driver_count</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Williamsstad</td>\n",
       "      <td>59</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Port Angela</td>\n",
       "      <td>67</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rodneyfort</td>\n",
       "      <td>34</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>West Robert</td>\n",
       "      <td>39</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>West Anthony</td>\n",
       "      <td>70</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>West Angela</td>\n",
       "      <td>48</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Martinezhaven</td>\n",
       "      <td>25</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Karenberg</td>\n",
       "      <td>22</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Barajasview</td>\n",
       "      <td>26</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            city  driver_count   type\n",
       "0    Richardfort            38  Urban\n",
       "1   Williamsstad            59  Urban\n",
       "2    Port Angela            67  Urban\n",
       "3     Rodneyfort            34  Urban\n",
       "4    West Robert            39  Urban\n",
       "5   West Anthony            70  Urban\n",
       "6    West Angela            48  Urban\n",
       "7  Martinezhaven            25  Urban\n",
       "8      Karenberg            22  Urban\n",
       "9    Barajasview            26  Urban"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the city data file and store it in a pandas DataFrame.\n",
    "\n",
    "city_data_df = pd.read_csv(city_data_to_load)\n",
    "city_data_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e68e596b",
   "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>city</th>\n",
       "      <th>date</th>\n",
       "      <th>fare</th>\n",
       "      <th>ride_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lake Jonathanshire</td>\n",
       "      <td>2019-01-14 10:14:22</td>\n",
       "      <td>13.83</td>\n",
       "      <td>5739410935873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>South Michelleport</td>\n",
       "      <td>2019-03-04 18:24:09</td>\n",
       "      <td>30.24</td>\n",
       "      <td>2343912425577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Port Samanthamouth</td>\n",
       "      <td>2019-02-24 04:29:00</td>\n",
       "      <td>33.44</td>\n",
       "      <td>2005065760003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rodneyfort</td>\n",
       "      <td>2019-02-10 23:22:03</td>\n",
       "      <td>23.44</td>\n",
       "      <td>5149245426178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>South Jack</td>\n",
       "      <td>2019-03-06 04:28:35</td>\n",
       "      <td>34.58</td>\n",
       "      <td>3908451377344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>South Latoya</td>\n",
       "      <td>2019-03-11 12:26:48</td>\n",
       "      <td>9.52</td>\n",
       "      <td>1994999424437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>New Paulville</td>\n",
       "      <td>2019-02-27 11:17:56</td>\n",
       "      <td>43.25</td>\n",
       "      <td>793208410091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Simpsonburgh</td>\n",
       "      <td>2019-04-26 00:43:24</td>\n",
       "      <td>35.98</td>\n",
       "      <td>111953927754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>South Karenland</td>\n",
       "      <td>2019-01-08 03:28:48</td>\n",
       "      <td>35.09</td>\n",
       "      <td>7995623208694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>North Jasmine</td>\n",
       "      <td>2019-03-09 06:26:29</td>\n",
       "      <td>42.81</td>\n",
       "      <td>5327642267789</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 city                 date   fare        ride_id\n",
       "0  Lake Jonathanshire  2019-01-14 10:14:22  13.83  5739410935873\n",
       "1  South Michelleport  2019-03-04 18:24:09  30.24  2343912425577\n",
       "2  Port Samanthamouth  2019-02-24 04:29:00  33.44  2005065760003\n",
       "3          Rodneyfort  2019-02-10 23:22:03  23.44  5149245426178\n",
       "4          South Jack  2019-03-06 04:28:35  34.58  3908451377344\n",
       "5        South Latoya  2019-03-11 12:26:48   9.52  1994999424437\n",
       "6       New Paulville  2019-02-27 11:17:56  43.25   793208410091\n",
       "7        Simpsonburgh  2019-04-26 00:43:24  35.98   111953927754\n",
       "8     South Karenland  2019-01-08 03:28:48  35.09  7995623208694\n",
       "9       North Jasmine  2019-03-09 06:26:29  42.81  5327642267789"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the ride data file and store it in a pandas DataFrame.\n",
    "\n",
    "ride_data_df = pd.read_csv(ride_data_to_load)\n",
    "ride_data_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "92a57e05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city            120\n",
       "driver_count    120\n",
       "type            120\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the columns and the rows that are not null.\n",
    "\n",
    "city_data_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6fdc1bde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city            0\n",
       "driver_count    0\n",
       "type            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the columns and the rows that are not null.\n",
    "\n",
    "city_data_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "37fc2685",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city            object\n",
       "driver_count     int64\n",
       "type            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the data types of each column.\n",
    "\n",
    "city_data_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8de53f1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Urban', 'Suburban', 'Rural'], dtype=object)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the unique values of the type of city.\n",
    "\n",
    "city_data_df[\"type\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "99b87943",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "66"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the number of data points from the Urban cities.\n",
    "\n",
    "sum(city_data_df[\"type\"] == \"Urban\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "829e1a1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city       2375\n",
       "date       2375\n",
       "fare       2375\n",
       "ride_id    2375\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the columns and the rows that are not null.\n",
    "\n",
    "ride_data_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "566c471a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city       0\n",
       "date       0\n",
       "fare       0\n",
       "ride_id    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the columns and the rows that are not null.\n",
    "\n",
    "ride_data_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c833d5eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city        object\n",
       "date        object\n",
       "fare       float64\n",
       "ride_id      int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the data types of each column.\n",
    "\n",
    "ride_data_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c1049fca",
   "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",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>fare</th>\n",
       "      <th>ride_id</th>\n",
       "      <th>driver_count</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lake Jonathanshire</td>\n",
       "      <td>2019-01-14 10:14:22</td>\n",
       "      <td>13.83</td>\n",
       "      <td>5739410935873</td>\n",
       "      <td>5</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>South Michelleport</td>\n",
       "      <td>2019-03-04 18:24:09</td>\n",
       "      <td>30.24</td>\n",
       "      <td>2343912425577</td>\n",
       "      <td>72</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Port Samanthamouth</td>\n",
       "      <td>2019-02-24 04:29:00</td>\n",
       "      <td>33.44</td>\n",
       "      <td>2005065760003</td>\n",
       "      <td>57</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rodneyfort</td>\n",
       "      <td>2019-02-10 23:22:03</td>\n",
       "      <td>23.44</td>\n",
       "      <td>5149245426178</td>\n",
       "      <td>34</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>South Jack</td>\n",
       "      <td>2019-03-06 04:28:35</td>\n",
       "      <td>34.58</td>\n",
       "      <td>3908451377344</td>\n",
       "      <td>46</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 city                 date   fare        ride_id  \\\n",
       "0  Lake Jonathanshire  2019-01-14 10:14:22  13.83  5739410935873   \n",
       "1  South Michelleport  2019-03-04 18:24:09  30.24  2343912425577   \n",
       "2  Port Samanthamouth  2019-02-24 04:29:00  33.44  2005065760003   \n",
       "3          Rodneyfort  2019-02-10 23:22:03  23.44  5149245426178   \n",
       "4          South Jack  2019-03-06 04:28:35  34.58  3908451377344   \n",
       "\n",
       "   driver_count   type  \n",
       "0             5  Urban  \n",
       "1            72  Urban  \n",
       "2            57  Urban  \n",
       "3            34  Urban  \n",
       "4            46  Urban  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combine the data into a single dataset\n",
    "\n",
    "pyber_data_df = pd.merge(ride_data_df, city_data_df, how=\"left\", on=[\"city\", \"city\"])\n",
    "\n",
    "# Display the DataFrame\n",
    "pyber_data_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bf5f995f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>city</th>\n",
       "      <th>date</th>\n",
       "      <th>fare</th>\n",
       "      <th>ride_id</th>\n",
       "      <th>driver_count</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lake Jonathanshire</td>\n",
       "      <td>2019-01-14 10:14:22</td>\n",
       "      <td>13.83</td>\n",
       "      <td>5739410935873</td>\n",
       "      <td>5</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>South Michelleport</td>\n",
       "      <td>2019-03-04 18:24:09</td>\n",
       "      <td>30.24</td>\n",
       "      <td>2343912425577</td>\n",
       "      <td>72</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Port Samanthamouth</td>\n",
       "      <td>2019-02-24 04:29:00</td>\n",
       "      <td>33.44</td>\n",
       "      <td>2005065760003</td>\n",
       "      <td>57</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rodneyfort</td>\n",
       "      <td>2019-02-10 23:22:03</td>\n",
       "      <td>23.44</td>\n",
       "      <td>5149245426178</td>\n",
       "      <td>34</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>South Jack</td>\n",
       "      <td>2019-03-06 04:28:35</td>\n",
       "      <td>34.58</td>\n",
       "      <td>3908451377344</td>\n",
       "      <td>46</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 city                 date   fare        ride_id  \\\n",
       "0  Lake Jonathanshire  2019-01-14 10:14:22  13.83  5739410935873   \n",
       "1  South Michelleport  2019-03-04 18:24:09  30.24  2343912425577   \n",
       "2  Port Samanthamouth  2019-02-24 04:29:00  33.44  2005065760003   \n",
       "3          Rodneyfort  2019-02-10 23:22:03  23.44  5149245426178   \n",
       "4          South Jack  2019-03-06 04:28:35  34.58  3908451377344   \n",
       "\n",
       "   driver_count   type  \n",
       "0             5  Urban  \n",
       "1            72  Urban  \n",
       "2            57  Urban  \n",
       "3            34  Urban  \n",
       "4            46  Urban  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create the Urban city DataFrame.\n",
    "\n",
    "urban_cities_df = pyber_data_df[pyber_data_df[\"type\"] == \"Urban\"]\n",
    "urban_cities_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5b601066",
   "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>city</th>\n",
       "      <th>date</th>\n",
       "      <th>fare</th>\n",
       "      <th>ride_id</th>\n",
       "      <th>driver_count</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2250</th>\n",
       "      <td>Randallchester</td>\n",
       "      <td>2019-04-13 11:13:31</td>\n",
       "      <td>43.22</td>\n",
       "      <td>1076079536213</td>\n",
       "      <td>9</td>\n",
       "      <td>Rural</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2251</th>\n",
       "      <td>North Holly</td>\n",
       "      <td>2019-02-02 14:54:00</td>\n",
       "      <td>12.42</td>\n",
       "      <td>1985256326182</td>\n",
       "      <td>8</td>\n",
       "      <td>Rural</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2252</th>\n",
       "      <td>Michaelberg</td>\n",
       "      <td>2019-03-27 18:27:34</td>\n",
       "      <td>54.85</td>\n",
       "      <td>4421836952718</td>\n",
       "      <td>6</td>\n",
       "      <td>Rural</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2253</th>\n",
       "      <td>Lake Latoyabury</td>\n",
       "      <td>2019-02-23 21:12:24</td>\n",
       "      <td>47.90</td>\n",
       "      <td>3269652929887</td>\n",
       "      <td>2</td>\n",
       "      <td>Rural</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2254</th>\n",
       "      <td>Lake Latoyabury</td>\n",
       "      <td>2019-05-06 08:57:56</td>\n",
       "      <td>51.80</td>\n",
       "      <td>4018025271936</td>\n",
       "      <td>2</td>\n",
       "      <td>Rural</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2370</th>\n",
       "      <td>Michaelberg</td>\n",
       "      <td>2019-04-29 17:04:39</td>\n",
       "      <td>13.38</td>\n",
       "      <td>8550365057598</td>\n",
       "      <td>6</td>\n",
       "      <td>Rural</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2371</th>\n",
       "      <td>Lake Latoyabury</td>\n",
       "      <td>2019-01-30 00:05:47</td>\n",
       "      <td>20.76</td>\n",
       "      <td>9018727594352</td>\n",
       "      <td>2</td>\n",
       "      <td>Rural</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2372</th>\n",
       "      <td>North Jaime</td>\n",
       "      <td>2019-02-10 21:03:50</td>\n",
       "      <td>11.11</td>\n",
       "      <td>2781339863778</td>\n",
       "      <td>1</td>\n",
       "      <td>Rural</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2373</th>\n",
       "      <td>West Heather</td>\n",
       "      <td>2019-05-07 19:22:15</td>\n",
       "      <td>44.94</td>\n",
       "      <td>4256853490277</td>\n",
       "      <td>4</td>\n",
       "      <td>Rural</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2374</th>\n",
       "      <td>Newtonview</td>\n",
       "      <td>2019-04-25 10:20:13</td>\n",
       "      <td>55.84</td>\n",
       "      <td>9990581345298</td>\n",
       "      <td>1</td>\n",
       "      <td>Rural</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>125 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 city                 date   fare        ride_id  \\\n",
       "2250   Randallchester  2019-04-13 11:13:31  43.22  1076079536213   \n",
       "2251      North Holly  2019-02-02 14:54:00  12.42  1985256326182   \n",
       "2252      Michaelberg  2019-03-27 18:27:34  54.85  4421836952718   \n",
       "2253  Lake Latoyabury  2019-02-23 21:12:24  47.90  3269652929887   \n",
       "2254  Lake Latoyabury  2019-05-06 08:57:56  51.80  4018025271936   \n",
       "...               ...                  ...    ...            ...   \n",
       "2370      Michaelberg  2019-04-29 17:04:39  13.38  8550365057598   \n",
       "2371  Lake Latoyabury  2019-01-30 00:05:47  20.76  9018727594352   \n",
       "2372      North Jaime  2019-02-10 21:03:50  11.11  2781339863778   \n",
       "2373     West Heather  2019-05-07 19:22:15  44.94  4256853490277   \n",
       "2374       Newtonview  2019-04-25 10:20:13  55.84  9990581345298   \n",
       "\n",
       "      driver_count   type  \n",
       "2250             9  Rural  \n",
       "2251             8  Rural  \n",
       "2252             6  Rural  \n",
       "2253             2  Rural  \n",
       "2254             2  Rural  \n",
       "...            ...    ...  \n",
       "2370             6  Rural  \n",
       "2371             2  Rural  \n",
       "2372             1  Rural  \n",
       "2373             4  Rural  \n",
       "2374             1  Rural  \n",
       "\n",
       "[125 rows x 6 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create the Suburban and Rural city DataFrames.\n",
    "\n",
    "suburban_cities_df = pyber_data_df[pyber_data_df[\"type\"] == \"Suburban\"]\n",
    "rural_cities_df = pyber_data_df[pyber_data_df[\"type\"] == \"Rural\"]\n",
    "\n",
    "rural_cities_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e068b47f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city\n",
       "Amandaburgh        18\n",
       "Barajasview        22\n",
       "Carriemouth        27\n",
       "Christopherfurt    27\n",
       "Deanville          19\n",
       "Name: ride_id, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the number of rides for urban cities.\n",
    "\n",
    "urban_ride_count = urban_cities_df.groupby([\"city\"]).count()[\"ride_id\"]\n",
    "urban_ride_count.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "40ee175a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the suburban and rural ride count.\n",
    "\n",
    "suburban_ride_count = suburban_cities_df.groupby([\"city\"]).count()[\"ride_id\"]\n",
    "\n",
    "rural_ride_count = rural_cities_df.groupby([\"city\"]).count()[\"ride_id\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ebede879",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city\n",
       "Amandaburgh        24.641667\n",
       "Barajasview        25.332273\n",
       "Carriemouth        28.314444\n",
       "Christopherfurt    24.501852\n",
       "Deanville          25.842632\n",
       "Name: fare, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get average fare for each city in the urban cities.\n",
    "\n",
    "urban_avg_fare = urban_cities_df.groupby([\"city\"]).mean()[\"fare\"]\n",
    "urban_avg_fare.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "43bddd8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get average fare for each city in the suburban and rural cities.\n",
    "\n",
    "suburban_avg_fare = suburban_cities_df.groupby([\"city\"]).mean()[\"fare\"]\n",
    "rural_avg_fare = rural_cities_df.groupby([\"city\"]).mean()[\"fare\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "33fe6a04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city\n",
       "Amandaburgh        12.0\n",
       "Barajasview        26.0\n",
       "Carriemouth        52.0\n",
       "Christopherfurt    41.0\n",
       "Deanville          49.0\n",
       "Name: driver_count, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the average number of drivers for each urban city.\n",
    "\n",
    "urban_driver_count = urban_cities_df.groupby([\"city\"]).mean()[\"driver_count\"]\n",
    "urban_driver_count.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "0161dc1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the average number of drivers for each city for the suburban and rural cities.\n",
    "\n",
    "suburban_driver_count = suburban_cities_df.groupby([\"city\"]).mean()[\"driver_count\"]\n",
    "rural_driver_count = rural_cities_df.groupby([\"city\"]).mean()[\"driver_count\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "dcb9e122",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2d5b3c56448>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build the scatter plots for urban cities.\n",
    "\n",
    "plt.scatter(\n",
    "    urban_ride_count,\n",
    "    urban_avg_fare,\n",
    "    s=10 * urban_driver_count,\n",
    "    c=\"coral\",\n",
    "    edgecolor=\"black\",\n",
    "    linewidths=1,\n",
    "    alpha=0.8,\n",
    "    label=\"Urban\",\n",
    ")\n",
    "plt.title(\"PyBer Ride-Sharing Data (2019)\")\n",
    "plt.ylabel(\"Average Fare ($)\")\n",
    "plt.xlabel(\"Total Number of Rides (Per City)\")\n",
    "plt.grid(True)\n",
    "\n",
    "# Add the legend.\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "fef94c8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2d5b45fc9c8>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build the scatter plots for suburban cities.\n",
    "\n",
    "plt.scatter(\n",
    "    suburban_ride_count,\n",
    "    suburban_avg_fare,\n",
    "    s=10 * suburban_driver_count,\n",
    "    c=\"skyblue\",\n",
    "    edgecolor=\"black\",\n",
    "    linewidths=1,\n",
    "    alpha=0.8,\n",
    "    label=\"Suburban\",\n",
    ")\n",
    "plt.title(\"PyBer Ride-Sharing Data (2019)\")\n",
    "plt.ylabel(\"Average Fare ($)\")\n",
    "plt.xlabel(\"Total Number of Rides (Per City)\")\n",
    "plt.grid(True)\n",
    "\n",
    "# Add the legend.\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "2e392100",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2d5b44dc3c8>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build the scatter plots for rural cities.\n",
    "\n",
    "plt.scatter(\n",
    "    rural_ride_count,\n",
    "    rural_avg_fare,\n",
    "    s=10 * rural_driver_count,\n",
    "    c=\"gold\",\n",
    "    edgecolor=\"black\",\n",
    "    linewidths=1,\n",
    "    alpha=0.8,\n",
    "    label=\"Rural\",\n",
    ")\n",
    "plt.title(\"PyBer Ride-Sharing Data (2019)\")\n",
    "plt.ylabel(\"Average Fare ($)\")\n",
    "plt.xlabel(\"Total Number of Rides (Per City)\")\n",
    "plt.grid(True)\n",
    "\n",
    "# Add the legend.\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "37bd3f41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build the scatter charts for each city type.\n",
    "\n",
    "plt.subplots(figsize=(10, 6))\n",
    "\n",
    "plt.scatter(\n",
    "    urban_ride_count,\n",
    "    urban_avg_fare,\n",
    "    s=10 * urban_driver_count,\n",
    "    c=\"coral\",\n",
    "    edgecolor=\"black\",\n",
    "    linewidths=1,\n",
    "    alpha=0.8,\n",
    "    label=\"Urban\",\n",
    ")\n",
    "\n",
    "plt.scatter(\n",
    "    suburban_ride_count,\n",
    "    suburban_avg_fare,\n",
    "    s=10 * suburban_driver_count,\n",
    "    c=\"skyblue\",\n",
    "    edgecolor=\"black\",\n",
    "    linewidths=1,\n",
    "    alpha=0.8,\n",
    "    label=\"Suburban\",\n",
    ")\n",
    "\n",
    "plt.scatter(\n",
    "    rural_ride_count,\n",
    "    rural_avg_fare,\n",
    "    s=10 * rural_driver_count,\n",
    "    c=\"gold\",\n",
    "    edgecolor=\"black\",\n",
    "    linewidths=1,\n",
    "    alpha=0.8,\n",
    "    label=\"Rural\",\n",
    ")\n",
    "\n",
    "# Incorporate the other graph properties\n",
    "\n",
    "plt.title(\"PyBer Ride-Sharing Data (2019)\", fontsize=20)\n",
    "plt.ylabel(\"Average Fare ($)\", fontsize=12)\n",
    "plt.xlabel(\"Total Number of Rides (Per City)\", fontsize=12)\n",
    "plt.grid(True)\n",
    "\n",
    "# Create a legend\n",
    "\n",
    "lgnd = plt.legend(\n",
    "    fontsize=\"12\", mode=\"Expanded\", scatterpoints=1, loc=\"best\", title=\"City Types\"\n",
    ")\n",
    "lgnd.legendHandles[0]._sizes = [75]\n",
    "lgnd.legendHandles[1]._sizes = [75]\n",
    "lgnd.legendHandles[2]._sizes = [75]\n",
    "lgnd.get_title().set_fontsize(12)\n",
    "\n",
    "# Incorporate a text label about circle size.\n",
    "\n",
    "plt.text(\n",
    "    42, 35, \"Note: Circle size correlates with driver count per city.\", fontsize=\"12\"\n",
    ")\n",
    "\n",
    "# Save the figure.\n",
    "\n",
    "plt.savefig(\"analysis/Fig1.png\")\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b6f04197",
   "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>fare</th>\n",
       "      <th>ride_id</th>\n",
       "      <th>driver_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1625.000000</td>\n",
       "      <td>1.625000e+03</td>\n",
       "      <td>1625.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>24.525772</td>\n",
       "      <td>4.873485e+12</td>\n",
       "      <td>36.678154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>11.738649</td>\n",
       "      <td>2.907440e+12</td>\n",
       "      <td>20.075545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.050000</td>\n",
       "      <td>1.458810e+10</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>14.550000</td>\n",
       "      <td>2.400244e+12</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>24.640000</td>\n",
       "      <td>4.711188e+12</td>\n",
       "      <td>37.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>34.580000</td>\n",
       "      <td>7.451579e+12</td>\n",
       "      <td>52.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>44.970000</td>\n",
       "      <td>9.991538e+12</td>\n",
       "      <td>73.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              fare       ride_id  driver_count\n",
       "count  1625.000000  1.625000e+03   1625.000000\n",
       "mean     24.525772  4.873485e+12     36.678154\n",
       "std      11.738649  2.907440e+12     20.075545\n",
       "min       4.050000  1.458810e+10      3.000000\n",
       "25%      14.550000  2.400244e+12     22.000000\n",
       "50%      24.640000  4.711188e+12     37.000000\n",
       "75%      34.580000  7.451579e+12     52.000000\n",
       "max      44.970000  9.991538e+12     73.000000"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get summary statistics.\n",
    "urban_cities_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b4812d66",
   "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>fare</th>\n",
       "      <th>ride_id</th>\n",
       "      <th>driver_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>625.000000</td>\n",
       "      <td>6.250000e+02</td>\n",
       "      <td>625.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>30.970128</td>\n",
       "      <td>4.971015e+12</td>\n",
       "      <td>13.712000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>10.677508</td>\n",
       "      <td>2.912410e+12</td>\n",
       "      <td>8.042372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>12.050000</td>\n",
       "      <td>3.218337e+08</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>21.970000</td>\n",
       "      <td>2.364253e+12</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>30.750000</td>\n",
       "      <td>5.053221e+12</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>39.830000</td>\n",
       "      <td>7.551674e+12</td>\n",
       "      <td>21.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>49.960000</td>\n",
       "      <td>9.917744e+12</td>\n",
       "      <td>25.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             fare       ride_id  driver_count\n",
       "count  625.000000  6.250000e+02    625.000000\n",
       "mean    30.970128  4.971015e+12     13.712000\n",
       "std     10.677508  2.912410e+12      8.042372\n",
       "min     12.050000  3.218337e+08      1.000000\n",
       "25%     21.970000  2.364253e+12      5.000000\n",
       "50%     30.750000  5.053221e+12     16.000000\n",
       "75%     39.830000  7.551674e+12     21.000000\n",
       "max     49.960000  9.917744e+12     25.000000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suburban_cities_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "11e84865",
   "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>fare</th>\n",
       "      <th>ride_id</th>\n",
       "      <th>driver_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>125.000000</td>\n",
       "      <td>1.250000e+02</td>\n",
       "      <td>125.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>34.623440</td>\n",
       "      <td>4.647746e+12</td>\n",
       "      <td>4.296000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14.558046</td>\n",
       "      <td>2.887834e+12</td>\n",
       "      <td>2.691156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>10.110000</td>\n",
       "      <td>2.684873e+10</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>19.900000</td>\n",
       "      <td>2.275364e+12</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>37.050000</td>\n",
       "      <td>4.023962e+12</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>47.070000</td>\n",
       "      <td>7.118047e+12</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>58.550000</td>\n",
       "      <td>9.990581e+12</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             fare       ride_id  driver_count\n",
       "count  125.000000  1.250000e+02    125.000000\n",
       "mean    34.623440  4.647746e+12      4.296000\n",
       "std     14.558046  2.887834e+12      2.691156\n",
       "min     10.110000  2.684873e+10      1.000000\n",
       "25%     19.900000  2.275364e+12      1.000000\n",
       "50%     37.050000  4.023962e+12      4.000000\n",
       "75%     47.070000  7.118047e+12      7.000000\n",
       "max     58.550000  9.990581e+12      9.000000"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rural_cities_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "1c7334af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    66.000000\n",
       "mean     24.621212\n",
       "std       5.408726\n",
       "min      12.000000\n",
       "25%      21.000000\n",
       "50%      24.000000\n",
       "75%      28.000000\n",
       "max      39.000000\n",
       "Name: ride_id, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get summary statistics.\n",
    "urban_ride_count.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "876bdcfa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    36.000000\n",
       "mean     17.361111\n",
       "std       4.323707\n",
       "min       9.000000\n",
       "25%      14.000000\n",
       "50%      17.000000\n",
       "75%      19.250000\n",
       "max      27.000000\n",
       "Name: ride_id, dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suburban_ride_count.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c56b5aef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    18.000000\n",
       "mean      6.944444\n",
       "std       2.508157\n",
       "min       3.000000\n",
       "25%       5.250000\n",
       "50%       6.000000\n",
       "75%       8.750000\n",
       "max      12.000000\n",
       "Name: ride_id, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rural_ride_count.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "2615c082",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(24.62, 17.36, 6.94)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the mean of the ride count for each city type.\n",
    "round(urban_ride_count.mean(), 2), round(suburban_ride_count.mean(), 2), round(\n",
    "    rural_ride_count.mean(), 2\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "319021c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    22\n",
       "1    25\n",
       "dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the mode of the ride count for the urban cities.\n",
    "urban_ride_count.mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "59eb7af9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    17\n",
       "dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suburban_ride_count.mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e4da9d03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    6\n",
       "dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rural_ride_count.mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "c0c2c83a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean for the ride counts for urban trips is 24.62.\n",
      "The median for the ride counts for urban trips is 24.0.\n",
      "The mode for the ride counts for urban trips is ModeResult(mode=array([22], dtype=int64), count=array([7])).\n"
     ]
    }
   ],
   "source": [
    "# Calculate the measures of central tendency for the ride count for the urban cities.\n",
    "mean_urban_ride_count = np.mean(urban_ride_count)\n",
    "print(f\"The mean for the ride counts for urban trips is {mean_urban_ride_count:.2f}.\")\n",
    "\n",
    "median_urban_ride_count = np.median(urban_ride_count)\n",
    "print(f\"The median for the ride counts for urban trips is {median_urban_ride_count}.\")\n",
    "\n",
    "mode_urban_ride_count = sts.mode(urban_ride_count)\n",
    "print(f\"The mode for the ride counts for urban trips is {mode_urban_ride_count}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "232f3292",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean for the ride counts for urban trips is 17.36.\n",
      "The median for the ride counts for urban trips is 17.0.\n",
      "The mode for the ride counts for urban trips is ModeResult(mode=array([17], dtype=int64), count=array([7])).\n"
     ]
    }
   ],
   "source": [
    "# Calculate the measures of central tendency for the ride count for the suburban cities.\n",
    "mean_suburban_ride_count = np.mean(suburban_ride_count)\n",
    "print(\n",
    "    f\"The mean for the ride counts for urban trips is {mean_suburban_ride_count:.2f}.\"\n",
    ")\n",
    "\n",
    "median_suburban_ride_count = np.median(suburban_ride_count)\n",
    "print(\n",
    "    f\"The median for the ride counts for urban trips is {median_suburban_ride_count}.\"\n",
    ")\n",
    "\n",
    "mode_suburban_ride_count = sts.mode(suburban_ride_count)\n",
    "print(f\"The mode for the ride counts for urban trips is {mode_suburban_ride_count}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "819aa1da",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean for the ride counts for urban trips is 6.94.\n",
      "The median for the ride counts for urban trips is 6.0.\n",
      "The mode for the ride counts for urban trips is ModeResult(mode=array([6], dtype=int64), count=array([5])).\n"
     ]
    }
   ],
   "source": [
    "# Calculate the measures of central tendency for the ride count for the rural cities.\n",
    "mean_rural_ride_count = np.mean(rural_ride_count)\n",
    "print(f\"The mean for the ride counts for urban trips is {mean_rural_ride_count:.2f}.\")\n",
    "\n",
    "median_rural_ride_count = np.median(rural_ride_count)\n",
    "print(f\"The median for the ride counts for urban trips is {median_rural_ride_count}.\")\n",
    "\n",
    "mode_rural_ride_count = sts.mode(rural_ride_count)\n",
    "print(f\"The mode for the ride counts for urban trips is {mode_rural_ride_count}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "150a7720",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    13.83\n",
       "1    30.24\n",
       "2    33.44\n",
       "3    23.44\n",
       "4    34.58\n",
       "Name: fare, dtype: float64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the fares for the urban,suburban,and rural cities.\n",
    "urban_fares = urban_cities_df[\"fare\"]\n",
    "suburban_fares = suburban_cities_df[\"fare\"]\n",
    "rural_fares = rural_cities_df[\"fare\"]\n",
    "urban_fares.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "8ed2e59a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean fare price for urban trips is $24.53.\n",
      "The median fare price for urban trips is $24.64.\n",
      "The mode fare price for urban trips is ModeResult(mode=array([22.86]), count=array([5])).\n"
     ]
    }
   ],
   "source": [
    "# Calculate the measures of central tendency for the average fare for the urban cities.\n",
    "mean_urban_fares = np.mean(urban_fares)\n",
    "print(f\"The mean fare price for urban trips is ${mean_urban_fares:.2f}.\")\n",
    "\n",
    "median_urban_fares = np.median(urban_fares)\n",
    "print(f\"The median fare price for urban trips is ${median_urban_fares:.2f}.\")\n",
    "\n",
    "mode_urban_fares = sts.mode(urban_fares)\n",
    "print(f\"The mode fare price for urban trips is {mode_urban_fares}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "dd30e797",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean fare price for urban trips is $30.97.\n",
      "The median fare price for urban trips is $30.75.\n",
      "The mode fare price for urban trips is ModeResult(mode=array([17.99]), count=array([3])).\n"
     ]
    }
   ],
   "source": [
    "# Calculate the measures of central tendency for the average fare for the suburban cities.\n",
    "mean_suburban_fares = np.mean(suburban_fares)\n",
    "print(f\"The mean fare price for urban trips is ${mean_suburban_fares:.2f}.\")\n",
    "\n",
    "median_suburban_fares = np.median(suburban_fares)\n",
    "print(f\"The median fare price for urban trips is ${median_suburban_fares:.2f}.\")\n",
    "\n",
    "mode_suburban_fares = sts.mode(suburban_fares)\n",
    "print(f\"The mode fare price for urban trips is {mode_suburban_fares}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "d1bdc0d0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean fare price for urban trips is $34.62.\n",
      "The median fare price for urban trips is $37.05.\n",
      "The mode fare price for urban trips is ModeResult(mode=array([37.05]), count=array([2])).\n"
     ]
    }
   ],
   "source": [
    "# Calculate the measures of central tendency for the average fare for the rural cities.\n",
    "mean_rural_fares = np.mean(rural_fares)\n",
    "print(f\"The mean fare price for urban trips is ${mean_rural_fares:.2f}.\")\n",
    "\n",
    "median_rural_fares = np.median(rural_fares)\n",
    "print(f\"The median fare price for urban trips is ${median_rural_fares:.2f}.\")\n",
    "\n",
    "mode_rural_fares = sts.mode(rural_fares)\n",
    "print(f\"The mode fare price for urban trips is {mode_rural_fares}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "0bbe76c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     5\n",
       "1    72\n",
       "2    57\n",
       "3    34\n",
       "4    46\n",
       "Name: driver_count, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the driver count data from the urban,suburban,rural cities.\n",
    "urban_drivers = urban_cities_df[\"driver_count\"]\n",
    "suburban_drivers = suburban_cities_df[\"driver_count\"]\n",
    "rural_drivers = rural_cities_df[\"driver_count\"]\n",
    "urban_drivers.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "bd4456cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean fare price for urban trips is $36.68.\n",
      "The median fare price for urban trips is $37.00.\n",
      "The mode fare price for urban trips is ModeResult(mode=array([39], dtype=int64), count=array([86])).\n"
     ]
    }
   ],
   "source": [
    "# Calculate the measures of central tendency for the average drivers for the urban cities.\n",
    "mean_urban_drivers = np.mean(urban_drivers)\n",
    "print(f\"The mean fare price for urban trips is ${mean_urban_drivers:.2f}.\")\n",
    "\n",
    "median_urban_drivers = np.median(urban_drivers)\n",
    "print(f\"The median fare price for urban trips is ${median_urban_drivers:.2f}.\")\n",
    "\n",
    "mode_urban_drivers = sts.mode(urban_drivers)\n",
    "print(f\"The mode fare price for urban trips is {mode_urban_drivers}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "bd7056c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean fare price for urban trips is $13.71.\n",
      "The median fare price for urban trips is $16.00.\n",
      "The mode fare price for urban trips is ModeResult(mode=array([20], dtype=int64), count=array([79])).\n"
     ]
    }
   ],
   "source": [
    "# Calculate the measures of central tendency for the average drivers for the suburban cities.\n",
    "mean_suburban_drivers = np.mean(suburban_drivers)\n",
    "print(f\"The mean fare price for urban trips is ${mean_suburban_drivers:.2f}.\")\n",
    "\n",
    "median_suburban_drivers = np.median(suburban_drivers)\n",
    "print(f\"The median fare price for urban trips is ${median_suburban_drivers:.2f}.\")\n",
    "\n",
    "mode_suburban_drivers = sts.mode(suburban_drivers)\n",
    "print(f\"The mode fare price for urban trips is {mode_suburban_drivers}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "c68e1c62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean fare price for urban trips is $4.30.\n",
      "The median fare price for urban trips is $4.00.\n",
      "The mode fare price for urban trips is ModeResult(mode=array([1], dtype=int64), count=array([32])).\n"
     ]
    }
   ],
   "source": [
    "# Calculate the measures of central tendency for the average drivers for the rural cities.\n",
    "mean_rural_drivers = np.mean(rural_drivers)\n",
    "print(f\"The mean fare price for urban trips is ${mean_rural_drivers:.2f}.\")\n",
    "\n",
    "median_rural_drivers = np.median(rural_drivers)\n",
    "print(f\"The median fare price for urban trips is ${median_rural_drivers:.2f}.\")\n",
    "\n",
    "mode_rural_drivers = sts.mode(rural_drivers)\n",
    "print(f\"The mode fare price for urban trips is {mode_rural_drivers}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "9fe11382",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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F4dq1awIAYenSpU3W22DJkiVCx44d9T5h1nCzxKa+/libIAjC+vXrhZ49ewo2NjaCp6ensHTpUqGmpsag34PG/b3Y2Fihe/fugkKhEDp06CA8++yzQlZWVqPv4fLlywIAYe/evc2+X6KWJhOEPyz1JyKiFnXjxg14e3tj+/btjd5XSAqWLFmC7du3o6ioqNlP7hG1NIYZIiIRLFy4EEeOHEFBQYHRd+m1FHfv3kW3bt2wceNG3S0DiMTEOE1EJIJ//OMfsLe3x/Xr1+Hh4SF2OSYpLi5GTEyMwT2RiMTCmRkiIiKSNGnNbRIRERH9AcMMERERSRrDDBEREUlam18AXF9fjxs3bkCpVPLGTkRERBIhCALKy8vh5ubW/Cf+RLzHjZ6VK1cKAIQ333xT11ZfXy8sXbpU6NKli2BraysEBwcL58+fN2ncn3/++YE3jOIXv/jFL37xi1+W+/Xzzz83+7veImZmcnNz8a9//cvggWqrV6/GunXrsHXrVvTs2RPLly9HWFgYLl68+MBn0fxeQ7+ff/4ZKpXK7LUTkXi0Wi1SU1MRHh4OuVwudjlEZEZqtRoeHh5G/b4XPcxUVFRgwoQJ+Oyzz7B8+XJduyAIiI+Px+LFi3VPCt62bRs6d+6MnTt36h4c15yGS0sqlYphhqiN0Wq1sLe3h0qlYpghaqOMWSIiepiJjo7GiBEjMGzYML0wU1xcjJKSEoSHh+vaFAoFgoODceLEiSbDjEajgUaj0W2r1WoA93/oabXaFnoXRCSGhnOa5zZR22PKeS1qmNm1axfy8/ORm5trsK+kpAQADB4t37lzZ1y9erXJMePi4hAbG2vQnpqaCnt7+z9ZMRFZImOfWE1E0lFVVWV0X9HCzM8//4w333wTqampsLW1bbLfH6eXBEF44JRTTEwM5s6dq9tuuOYWHh7Oy0xEbYxWq0VaWhrCwsJ4mYmojWm4smIM0cLM6dOncevWLfzXf/2Xrq2urg5ZWVnYtGkTLl68COD+DE2XLl10fW7dumUwW/N7CoUCCoXCoF0ul/OHHVEbxfObqO0x5ZwW7aZ5zzzzDM6dO4eCggLd16BBgzBhwgQUFBSgW7ducHV11Zs+rqmpQWZmJp566imxyiYiIiILI9rMjFKpxJNPPqnX1r59ezg7O+va33rrLaxcuRI9evRAjx49sHLlStjb2/NJrURERKQj+qeZHmTBggWorq7GzJkzcefOHQQEBCA1NdXoe8wQERFR2ycTBEEQu4iWpFar4ejoiLKyMi4AJmpjtFot/vOf/yAyMpJrZojaGFN+f/NBk0QkSXV1dcjMzERWVhYyMzNRV1cndklEJBKGGSKSnH379sHHxwdhYWFYt24dwsLC4OPjg3379oldGhGJgGGGiCRl3759GDt2LPr27Ytjx47hiy++wLFjx9C3b1+MHTuWgYboEcQ1M0QkGXV1dfDx8UHfvn2RnJyMuro63ZoZKysrjB49GufPn8ePP/4IKysrscsloj+Ba2aIqE06duwYrly5gkWLFqFdO/0fX+3atUNMTAyKi4tx7NgxkSokIjEwzBCRZNy8eRMADO5R1aChvaEfET0aGGaISDIaHm1y/vz5Rvc3tP/+EShE1PYxzBCRZPz1r39F165dsXLlStTX1+vtq6+vR1xcHLy9vfHXv/5VpAqJSAwMM0QkGVZWVli7di0OHTqE0aNHIzs7G9XV1cjOzsbo0aNx6NAhrFmzhot/iR4xFv04AyKiPxozZgz27NmDefPmYejQobp2b29v7NmzB2PGjBGxOiISAz+aTUSSVFdXh/T0dBw5cgQREREIDQ3ljAxRG2LK72/OzBCRJFlZWSE4OBiVlZUIDg5mkCF6hHHNDBEREUmaqGEmISEBfn5+UKlUUKlUCAwMxJEjR3T7KyoqMGvWLLi7u8POzg69e/dGQkKCiBUTERGRpRH1MpO7uztWrVoFHx8fAMC2bdsQFRWFM2fO4IknnsCcOXOQnp6OHTt2oGvXrkhNTcXMmTPh5uaGqKgoMUsnIiIiCyHqzMzIkSMRGRmJnj17omfPnlixYgUcHByQnZ0NADh58iQmT56MkJAQdO3aFa+99hr69euHvLw8McsmIiIiC2IxC4Dr6uqwe/duVFZWIjAwEAAQFBSEAwcOYOrUqXBzc0NGRgYuXbqE9evXNzmORqOBRqPRbavVagCAVquFVqtt2TdBRM2qqqrCxYsXzTJWeXk5MjMz4eDgAKVSaZYxfX19YW9vb5axiOjhmfI7W/Qwc+7cOQQGBuLevXtwcHBAUlIS+vTpAwDYsGEDpk+fDnd3d1hbW6Ndu3bYvHkzgoKCmhwvLi4OsbGxBu2pqan8AUVkAYqKijBv3jyzjvnhhx+abay1a9eie/fuZhuPiB5OVVWV0X1Fv89MTU0Nrl27hrt372Lv3r3YvHkzMjMz0adPH6xZswafffYZ1qxZAy8vL2RlZSEmJgZJSUkYNmxYo+M1NjPj4eGB0tJS3meGyAKYc2bm/PnzmDZtGrZs2dLkwydNxZkZIsugVqvRqVMno+4zI3qY+aNhw4ahe/fuiI+Ph6OjI5KSkjBixAjd/ldffRW//PILUlJSjBqPN80jartOnTqFgIAA5OTkwN/fX+xyiMiMTPn9bXH3mREEARqNRrfGpV07/RKtrKwMHjBHREREjy5R18wsWrQIERER8PDwQHl5OXbt2oWMjAykpKRApVIhODgY8+fPh52dHby8vJCZmYnt27dj3bp1YpZNREREFkTUMPPrr79i4sSJuHnzJhwdHeHn54eUlBSEhYUBAHbt2oWYmBhMmDABt2/fhpeXF1asWIHXX39dzLKJiIjIgogaZrZs2fLA/a6urkhMTGylaoiIiEiKLG7NDBEREZEpGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0kQNMwkJCfDz84NKpYJKpUJgYCCOHDmi16ewsBCjRo2Co6MjlEolhgwZgmvXrolUMREREVkaUcOMu7s7Vq1ahby8POTl5eHpp59GVFQULly4AAAoKipCUFAQevXqhYyMDJw9exZLliyBra2tmGUTERGRBbEW88VHjhypt71ixQokJCQgOzsbTzzxBBYvXozIyEisXr1a16dbt26tXSYRERFZMFHDzO/V1dVh9+7dqKysRGBgIOrr63H48GEsWLAAw4cPx5kzZ+Dt7Y2YmBiMHj26yXE0Gg00Go1uW61WAwC0Wi20Wm1Lvw0iakUN5zTPb6K2x5RzWvQwc+7cOQQGBuLevXtwcHBAUlIS+vTpg5KSElRUVGDVqlVYvnw53n//faSkpGDMmDFIT09HcHBwo+PFxcUhNjbWoD01NRX29vYt/XaIqBUVFRUBAHJyclBaWipyNURkTlVVVUb3lQmCILRgLc2qqanBtWvXcPfuXezduxebN29GZmYmOnTogMcffxwvv/wydu7cqes/atQotG/fHl988UWj4zU2M+Ph4YHS0lKoVKoWfz9E1HpOnTqFoKAgHD9+HP7+/mKXQ0RmpFar0alTJ5SVlTX7+1v0mRkbGxv4+PgAAAYNGoTc3FysX78eGzduhLW1Nfr06aPXv3fv3jh+/HiT4ykUCigUCoN2uVwOuVxu3uKJSFQN5zTPb6K2x5Rz2uLuMyMIAjQaDWxsbDB48GBcvHhRb/+lS5fg5eUlUnVERERkaUSdmVm0aBEiIiLg4eGB8vJy7Nq1CxkZGUhJSQEAzJ8/H+PGjcPQoUMRGhqKlJQUHDx4EBkZGWKWTURERBZE1DDz66+/YuLEibh58yYcHR3h5+eHlJQUhIWFAQCef/55fPLJJ4iLi8Mbb7wBX19f7N27F0FBQWKWTURERBZE1DCzZcuWZvtMnToVU6dObYVqiIiISIosbs0MERERkSkYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNJEDTMJCQnw8/ODSqWCSqVCYGAgjhw50mjfGTNmQCaTIT4+vnWLJCIiIosmaphxd3fHqlWrkJeXh7y8PDz99NOIiorChQsX9PolJycjJycHbm5uIlVKRERElkrUMDNy5EhERkaiZ8+e6NmzJ1asWAEHBwdkZ2fr+ly/fh2zZs3C//zP/0Aul4tYLREREVkia7ELaFBXV4fdu3ejsrISgYGBAID6+npMnDgR8+fPxxNPPGHUOBqNBhqNRretVqsBAFqtFlqt1vyFE5FoGs5pnt9EbY8p57ToYebcuXMIDAzEvXv34ODggKSkJPTp0wcA8P7778Pa2hpvvPGG0ePFxcUhNjbWoD01NRX29vZmq5uIxFdUVAQAyMnJQWlpqcjVEJE5VVVVGd1X9DDj6+uLgoIC3L17F3v37sXkyZORmZmJ6upqrF+/Hvn5+ZDJZEaPFxMTg7lz5+q21Wo1PDw8EB4eDpVK1RJvgYhEcurUKQBAQEAA/P39Ra6GiMyp4cqKMUQPMzY2NvDx8QEADBo0CLm5uVi/fj169+6NW7duwdPTU9e3rq4O8+bNQ3x8PK5cudLoeAqFAgqFwqBdLpdzzQ1RG9NwTvP8Jmp7TDmnRQ8zfyQIAjQaDSZOnIhhw4bp7Rs+fDgmTpyIV155RaTqiIiIyNKIGmYWLVqEiIgIeHh4oLy8HLt27UJGRgZSUlLg7OwMZ2dnvf5yuRyurq7w9fUVqWIiIiKyNKKGmV9//RUTJ07EzZs34ejoCD8/P6SkpCAsLEzMsoiIiEhCRA0zW7ZsMal/U+tkiIiI6NHFZzMRERGRpDHMEBERkaQxzBAREZGkMcwQERGRpDHMEBERkaQxzBAREZGkMcwQERGRpDHMEBERkaQxzBAREZGkMcwQERGRpDHMEBERkaQxzBAREZGkMcwQERGRpDHMEBERkaSJGmYSEhLg5+cHlUoFlUqFwMBAHDlyBACg1WqxcOFC9O3bF+3bt4ebmxsmTZqEGzduiFkyERERWRhRw4y7uztWrVqFvLw85OXl4emnn0ZUVBQuXLiAqqoq5OfnY8mSJcjPz8e+fftw6dIljBo1SsySiYiIyMLIBEEQxC7i95ycnPDBBx9g2rRpBvtyc3Ph7++Pq1evwtPTs9HjNRoNNBqNblutVsPDwwOlpaVQqVQtVjcRtb5Tp04hKCgIx48fh7+/v9jlEJEZqdVqdOrUCWVlZc3+/rZupZqaVVdXh927d6OyshKBgYGN9ikrK4NMJkOHDh2aHCcuLg6xsbEG7ampqbC3tzdXuURkAYqKigAAOTk5KC0tFbkaIjKnqqoqo/uKPjNz7tw5BAYG4t69e3BwcMDOnTsRGRlp0O/evXsICgpCr169sGPHjibH48wM0aODMzNEbZekZmZ8fX1RUFCAu3fvYu/evZg8eTIyMzPRp08fXR+tVouXXnoJ9fX1+Pjjjx84nkKhgEKhMGiXy+WQy+Vmr5+IxNNwTvP8Jmp7TDmnRQ8zNjY28PHxAQAMGjQIubm5WL9+PT799FMA94PMiy++iOLiYnzzzTecXSEiIiI9ooeZPxIEQXeZqCHI/Pjjj0hPT4ezs7PI1REREZGlETXMLFq0CBEREfDw8EB5eTl27dqFjIwMpKSkoLa2FmPHjkV+fj4OHTqEuro6lJSUALj/iScbGxsxSyciIiILIWqY+fXXXzFx4kTcvHkTjo6O8PPzQ0pKCsLCwnDlyhUcOHAAANC/f3+949LT0xESEtL6BRMREZHFETXMbNmypcl9Xbt2hYXdAoeIiIgsEJ/NRERERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJImaphJSEiAn58fVCoVVCoVAgMDceTIEd1+QRCwbNkyuLm5wc7ODiEhIbhw4YKIFRMREZGlETXMuLu7Y9WqVcjLy0NeXh6efvppREVF6QLL6tWrsW7dOmzatAm5ublwdXVFWFgYysvLxSybiIiILIioYWbkyJGIjIxEz5490bNnT6xYsQIODg7Izs6GIAiIj4/H4sWLMWbMGDz55JPYtm0bqqqqsHPnTjHLJiIiIgtiLXYBDerq6rB7925UVlYiMDAQxcXFKCkpQXh4uK6PQqFAcHAwTpw4gRkzZjQ6jkajgUaj0W2r1WoAgFarhVarbdk3QUStquGc5vlN1PaYck6LHmbOnTuHwMBA3Lt3Dw4ODkhKSkKfPn1w4sQJAEDnzp31+nfu3BlXr15tcry4uDjExsYatKempsLe3t68xRORqIqKigAAOTk5KC0tFbkaIjKnqqoqo/uKHmZ8fX1RUFCAu3fvYu/evZg8eTIyMzN1+2UymV5/QRAM2n4vJiYGc+fO1W2r1Wp4eHggPDwcKpXK/G+AiERz6tQpAEBAQAD8/f1FroaIzKnhyooxTA4z1dXVEARBN8tx9epV3WzK7y8JGcvGxgY+Pj4AgEGDBiE3Nxfr16/HwoULAQAlJSXo0qWLrv+tW7cMZmt+T6FQQKFQGLTL5XLI5XKT6yMiy9VwTvP8Jmp7TDmnTV4AHBUVhe3btwMA7t69i4CAAKxduxZRUVFISEgwdTgDgiBAo9HA29sbrq6uSEtL0+2rqalBZmYmnnrqqT/9OkRERNQ2mBxm8vPz8de//hUAsGfPHt0alu3bt2PDhg0mjbVo0SIcO3YMV65cwblz57B48WJkZGRgwoQJkMlkeOutt7By5UokJSXh/PnzmDJlCuzt7TF+/HhTyyYiIqI2yuTLTFVVVVAqlQDuL6odM2YM2rVrhyFDhjxwYW5jfv31V0ycOBE3b96Eo6Mj/Pz8kJKSgrCwMADAggULUF1djZkzZ+LOnTsICAhAamqq7vWJiIiITA4zPj4+SE5OxvPPP4+jR49izpw5AO6vZTF1ge2WLVseuF8mk2HZsmVYtmyZqWUSERHRI8Lky0zvvvsu3n77bXTt2hX+/v4IDAwEcH+WZsCAAWYvkIiIiOhBTJ6ZGTt2LIKCgnDz5k3069dP1/7MM8/g+eefN2txRERERM15qMcZuLq6QqlUIi0tDdXV1QCAwYMHo1evXmYtjoiIiKg5JoeZ3377Dc888wx69uyJyMhI3Lx5EwDw6quvYt68eWYvkIiIiOhBTA4zc+bMgVwux7Vr1/QeDzBu3DikpKSYtTgiIiKi5pi8ZiY1NRVHjx6Fu7u7XnuPHj1M/mg2ERER0Z9l8sxMZWVlow9sLC0tbfQxAkREREQtyeQwM3ToUN3jDID794Kpr6/HBx98gNDQULMWR0RERNQcky8zffDBBwgJCUFeXh5qamqwYMECXLhwAbdv38a3337bEjUSERERNcnkmZk+ffrgu+++g7+/P8LCwlBZWYkxY8bgzJkz6N69e0vUSERERNQkk2dmgPv3mYmNjTV3LUREREQmMyrMfPfdd0YP6Ofn99DFEBEREZnKqDDTv39/yGQyCIIAmUymaxcEAQD02urq6sxcIhEREVHTjFozU1xcjJ9++gnFxcXYu3cvvL298fHHH6OgoAAFBQX4+OOP0b17d+zdu9ekF4+Li8PgwYOhVCrh4uKC0aNH4+LFi3p9KioqMGvWLLi7u8POzg69e/dGQkKCSa9DREREbZdRMzNeXl66P7/wwgvYsGEDIiMjdW1+fn7w8PDAkiVLMHr0aKNfPDMzE9HR0Rg8eDBqa2uxePFihIeH4/vvv0f79u0B3L/jcHp6Onbs2IGuXbsiNTUVM2fOhJubG6Kioox+LSIiImqbTF4AfO7cOXh7exu0e3t74/vvvzdprD8+/iAxMREuLi44ffo0hg4dCgA4efIkJk+ejJCQEADAa6+9hk8//RR5eXkMM0RERGR6mOnduzeWL1+OLVu2wNbWFgCg0WiwfPly9O7d+08VU1ZWBgBwcnLStQUFBeHAgQOYOnUq3NzckJGRgUuXLmH9+vWNjqHRaKDRaHTbarUaAKDVaqHVav9UfUSPuh9//BEVFRVil6Fz/vx5vf9aCgcHB/To0UPsMogkzZTf2TKhYRWvkU6dOoWRI0eivr4e/fr1AwCcPXsWMpkMhw4dgr+/v2nV/v8EQUBUVBTu3LmDY8eO6dpramowffp0bN++HdbW1mjXrh02b96MiRMnNjrOsmXLGv3Y+M6dOxt9DAMRGefGjRuYOXOm2GVIxscffww3NzexyyCSrKqqKowfPx5lZWVQqVQP7GtymGl4gR07duCHH36AIAjo06cPxo8fr1vn8jCio6Nx+PBhHD9+XO8hlmvWrMFnn32GNWvWwMvLC1lZWYiJiUFSUhKGDRtmME5jMzMeHh4oLS1t9ptBRE07c+YMAgICsHXr1j89C2su5eXlOHz4MEaMGAGlUil2OQCAwsJCTJkyBTk5ORgwYIDY5RBJllqtRqdOnYwKMw910zx7e3u89tprD1VcY2bPno0DBw4gKytLL8hUV1dj0aJFSEpKwogRIwDcX2xcUFCANWvWNBpmFApFow+8lMvlkMvlZquZ6FFjbX3/x0Xfvn0xcOBAkau5T6vVoqKiAkOHDrWY87vh+2RtbW0xNRFJkSnnj1Fh5sCBA4iIiIBcLseBAwce2HfUqFFGv7ggCJg9ezaSkpKQkZFhsLC4YZ1Lu3b6nyC3srJCfX290a9DREREbZdRYWb06NEoKSnR3QumKTKZzKSb5kVHR2Pnzp3Yv38/lEolSkpKAACOjo6ws7ODSqVCcHAw5s+fDzs7O3h5eSEzMxPbt2/HunXrjH4dIiIiaruMCjO/nwUx54xIw83vGj523SAxMRFTpkwBAOzatQsxMTGYMGECbt++DS8vL6xYsQKvv/662eogIiIi6XqoNTNNuX79Oh5//HGj+xuz9tjV1RWJiYl/piwiIiJqw4x6nEFzSkpKMHv2bPj4+JhjOCIiIiKjGR1m7t69iwkTJuCxxx6Dm5sbNmzYgPr6erz77rvo1q0bsrOz8fnnn7dkrUREREQGjL7MtGjRImRlZWHy5MlISUnBnDlzkJKSgnv37uHIkSMIDg5uyTqJiIiIGmV0mDl8+DASExMxbNgwzJw5Ez4+PujZsyfi4+NbsDwiIiKiBzP6MtONGzfQp08fAEC3bt1ga2uLV199tcUKIyIiIjKG0WGmvr5e7258VlZWf+rxBURERETmYPRlJkEQMGXKFN2jAu7du4fXX3/dINDs27fPvBUSERERPYDRYWby5Ml623//+9/NXgwRERGRqYwOM7xxHREREVkis9w0j4iIiEgsDDNEREQkaQwzREREJGkMM0RERCRpRoWZgQMH4s6dOwCAf/7zn6iqqmrRooiIiIiMZVSYKSwsRGVlJQAgNjYWFRUVZnnxuLg4DB48GEqlEi4uLhg9ejQuXrzY6OuPGjUKjo6OUCqVGDJkCK5du2aWGoiIiEjajPpodv/+/fHKK68gKCgIgiBgzZo1cHBwaLTvu+++a/SLZ2ZmIjo6GoMHD0ZtbS0WL16M8PBwfP/997qb8RUVFSEoKAjTpk1DbGwsHB0dUVhYCFtbW6Nfh4iIiNouo8LM1q1bsXTpUhw6dAgymQxHjhyBtbXhoTKZzKQwk5KSoredmJgIFxcXnD59GkOHDgUALF68GJGRkVi9erWuX7du3ZocU6PRQKPR6LbVajUAQKvVQqvVGl0bEemrra3V/ddSzqWGOiylHsAyv09EUmTK+WNUmPH19cWuXbsAAO3atcPXX38NFxeXh6vuAcrKygAATk5OAO4/D+rw4cNYsGABhg8fjjNnzsDb2xsxMTEYPXp0o2PExcUhNjbWoD01NRX29vZmr5noUVFUVAQAOH78OG7evClyNfrS0tLELkHHkr9PRFJiyvpcmSAIQgvWYjRBEBAVFYU7d+7g2LFjAICSkhJ06dIF9vb2WL58OUJDQ5GSkoJFixYhPT0dwcHBBuM0NjPj4eGB0tJSqFSqVns/RG3NmTNnEBAQgJycHAwYMEDscgDc/5dbWloawsLC9B6EKyZL/D4RSZFarUanTp1QVlbW7O9vox9n8HtFRUWIj49HYWEhZDIZevfujTfffBPdu3d/qIIBYNasWfjuu+9w/PhxXVt9fT0AICoqCnPmzAFwf/3OiRMn8MknnzQaZhQKhe5hmL8nl8st5ocdkRQ1XFq2tra2uHPJks5vS/4+EUmJKeePyfeZOXr0KPr06YNTp07Bz88PTz75JHJycvDEE0889FTv7NmzceDAAaSnp8Pd3V3X3qlTJ1hbW6NPnz56/Xv37s1PMxERERGAh5iZeeeddzBnzhysWrXKoH3hwoUICwszeixBEDB79mwkJSUhIyMD3t7eevttbGwwePBgg49rX7p0CV5eXqaWTkRERG2QyWGmsLAQX331lUH71KlTER8fb9JY0dHR2LlzJ/bv3w+lUomSkhIAgKOjI+zs7AAA8+fPx7hx4zB06FDdmpmDBw8iIyPD1NKJiIioDTL5MtNjjz2GgoICg/aCggKTP+GUkJCAsrIyhISEoEuXLrqvL7/8Utfn+eefxyeffILVq1ejb9++2Lx5M/bu3YugoCBTSyciIqI2yOSZmenTp+O1117DTz/9hKeeegoymQzHjx/H+++/j3nz5pk0lrEfpJo6dSqmTp1qaqlERET0CDA5zCxZsgRKpRJr165FTEwMAMDNzQ3Lli3DG2+8YfYCiYiIiB7E5DAjk8kwZ84czJkzB+Xl5QAApVJp9sKIiIiIjPFQ95lpwBBDREREYjN5ATARERGRJWGYISIiIkljmCEiIiJJMynMaLVahIaG4tKlSy1VDxEREZFJTAozcrkc58+fh0wma6l6iIiIiExi8mWmSZMmYcuWLS1RCxEREZHJTP5odk1NDTZv3oy0tDQMGjQI7du319u/bt06sxVHRERE1ByTw8z58+cxcOBAADBYO8PLT0RERNTaTA4z6enpLVEHERER0UN56I9mX758GUePHkV1dTUA4x8aSURERGROJoeZ3377Dc888wx69uyJyMhI3Lx5EwDw6quvmvzU7Li4OAwePBhKpRIuLi4YPXo0Ll682GT/GTNmQCaTIT4+3tSyiYiIqI0yOczMmTMHcrkc165dg729va593LhxSElJMWmszMxMREdHIzs7G2lpaaitrUV4eDgqKysN+iYnJyMnJwdubm6mlkxERERtmMlrZlJTU3H06FG4u7vrtffo0QNXr141aaw/hp/ExES4uLjg9OnTGDp0qK79+vXrmDVrFo4ePYoRI0aYWjIRERG1YSaHmcrKSr0ZmQalpaVQKBR/qpiysjIAgJOTk66tvr4eEydOxPz58/HEE080O4ZGo4FGo9Ftq9VqAPfvXqzVav9UfUSPsnpNBQa4toPNb4XQXqsXuxwAQG1tLRyrrqD259OAtck/zlqEzW8XMcC1Heo1FfyZQ/QnmHL+mHz2Dx06FNu3b8d7770H4P7Hsevr6/HBBx8gNDTU1OF0BEHA3LlzERQUhCeffFLX/v7778Pa2hpvvPGGUePExcUhNjbWoD01NbXREEZExim/dBz5MxyAb2cC34pdzX1yACEA0PRSu1b3JID8GQ7Ycfwgrt+6I3Y5RJJVVVVldF+Tw8wHH3yAkJAQ5OXloaamBgsWLMCFCxdw+/ZtfPvtw/+EmzVrFr777jscP35c13b69GmsX78e+fn5Rt/DJiYmBnPnztVtq9VqeHh4IDw8HCqV6qHrI3rUnXXpiIFj1mH79u3w9fUVuxwA92dmcnJyEBAQAGsLmZm5ePEiJk2ahH/tG4l+gwLFLodIshqurBjD5LO/T58++O6775CQkAArKytUVlZizJgxiI6ORpcuXUwdDgAwe/ZsHDhwAFlZWXprcY4dO4Zbt27B09NT11ZXV4d58+YhPj4eV65cMRhLoVA0erlLLpdDLpc/VH1EBLRTOOBMST1qnHtD7jlQ7HLu02pRdu5XWHv8l8Wc3zWl7XCmpB7tFA4WUxORFJly/jzUP2VcXV0bvZRjKkEQMHv2bCQlJSEjIwPe3t56+ydOnIhhw4bptQ0fPhwTJ07EK6+88qdfn4iIiKTvocLMnTt3sGXLFhQWFkImk6F379545ZVX9BbuGiM6Oho7d+7E/v37oVQqUVJSAgBwdHSEnZ0dnJ2d4ezsrHeMXC6Hq6urxUxzExERkbhMvs9MZmYmvL29sWHDBty5cwe3b9/Ghg0b4O3tjczMTJPGSkhIQFlZGUJCQtClSxfd15dffmlqWURERPSIMnlmJjo6Gi+++KJuzQxwfx3LzJkzER0djfPnzxs91sM8AqGxdTJERET06DJ5ZqaoqAjz5s3TBRkAsLKywty5c1FUVGTW4oiIiIiaY3KYGThwIAoLCw3aCwsL0b9/f3PURERERGQ0oy4zfffdd7o/v/HGG3jzzTdx+fJlDBkyBACQnZ2Njz76CKtWrWqZKomIiIiaYFSY6d+/P2Qymd4alwULFhj0Gz9+PMaNG2e+6oiIiIiaYVSYKS4ubuk6iIiIiB6KUWHGy8urpesgIiIieigPddO869ev49tvv8WtW7dQX6//9FxjHwhJREREZA4mh5nExES8/vrrsLGxgbOzs94DIGUyGcMMERERtSqTw8y7776Ld999FzExMWjXzuRPdhMRERGZlclppKqqCi+99BKDDBEREVkEkxPJtGnTsHv37paohYiIiMhkJl9miouLw3PPPYeUlBT07dsXcrlcb/+6devMVhwRERFRc0wOMytXrsTRo0fh6+sLAAYLgImIiIhak8mXmdatW4fPP/8chYWFyMjIQHp6uu7rm2++MWmsuLg4DB48GEqlEi4uLhg9ejQuXryo26/VarFw4UL07dsX7du3h5ubGyZNmoQbN26YWjYRERG1USaHGYVCgb/85S9mefHMzExER0cjOzsbaWlpqK2tRXh4OCorKwHcX2ycn5+PJUuWID8/H/v27cOlS5cwatQos7w+ERERSZ/Jl5nefPNNbNy4ERs2bPjTL56SkqK3nZiYCBcXF5w+fRpDhw6Fo6Mj0tLS9Pps3LgR/v7+uHbtGjw9Pf90DURERCRtJoeZU6dO4ZtvvsGhQ4fwxBNPGCwA3rdv30MXU1ZWBgBwcnJ6YB+ZTIYOHTo0ul+j0UCj0ei21Wo1gPuXrLRa7UPXRvSoq62t1f3XUs6lhjospR7AMr9PRFJkyvljcpjp0KEDxowZY+phzRIEAXPnzkVQUBCefPLJRvvcu3cP77zzDsaPHw+VStVon7i4OMTGxhq0p6amwt7e3qw1Ez1KioqKAADHjx/HzZs3Ra5G3x9ncMVkyd8nIimpqqoyuq9MEAShBWsxWnR0NA4fPozjx4/D3d3dYL9Wq8ULL7yAa9euISMjo8kw09jMjIeHB0pLS5s8hoiad+bMGQQEBCAnJwcDBgwQuxwA938upKWlISwszGCWWCyW+H0ikiK1Wo1OnTqhrKys2d/fD/WgSXObPXs2Dhw4gKysrCaDzIsvvoji4mJ88803D3xTCoUCCoXCoF0ul1vMDzsiKbK2ttb919LOJUs6vy35+0QkJaacPyaHGW9v7wfeT+ann34yeixBEDB79mwkJSUhIyMD3t7eBn0agsyPP/6I9PR0ODs7m1oyERERtWEmh5m33npLb1ur1eLMmTNISUnB/PnzTRorOjoaO3fuxP79+6FUKlFSUgIAcHR0hJ2dHWprazF27Fjk5+fj0KFDqKur0/VxcnKCjY2NqeUTERFRG/NQH81uzEcffYS8vDyTxkpISAAAhISE6LUnJiZiypQp+OWXX3DgwAEAQP/+/fX6pKenGxxHREREjx6zrZmJiIhATEwMEhMTjT6mubXHXbt2bbYPERERPdpMvgNwU/bs2fPA+8MQERERtQSTZ2YGDBigtwBYEASUlJTg//7v//Dxxx+btTgiIiKi5pgcZkaPHq233a5dOzz22GMICQlBr169zFUXERERkVFMDjNLly5tiTqIiIiIHopF3DSPiCxfw63F8/PzRa7k/6moqEBmZiY6duwIBwcHscsBABQWFopdAtEjx+gw065duwfeLA8AZDKZ7iFrRNS2/PDDDwCA6dOni1yJoQ8//FDsEgwolUqxSyB6ZBgdZpKSkprcd+LECWzcuJEfoyZqwxrWy/Xq1ctiHtp6/vx5TJ48Gdu2bWvyAbViUCqV6NGjh9hlED0yjA4zUVFRBm0//PADYmJicPDgQUyYMAHvvfeeWYsjIsvRqVMnvPrqq2KXoadhJrhXr14YOHCgyNUQkVge6j4zN27cwPTp0+Hn54fa2loUFBRg27Zt8PT0NHd9RERERA9kUpgpKyvDwoUL4ePjgwsXLuDrr7/GwYMHLWp6l4iIiB4tRl9mWr16Nd5//324urriiy++aPSyExEREVFrMzrMvPPOO7Czs4OPjw+2bduGbdu2Ndpv3759ZiuOiIiIqDlGh5lJkyY1+9FsIiIiotZmdJjZunVrC5ZBRERE9HDM9tTshxEXF4fBgwdDqVTCxcUFo0ePxsWLF/X6CIKAZcuWwc3NDXZ2dggJCcGFCxdEqpiIiIgsjahhJjMzE9HR0cjOzkZaWhpqa2sRHh6OyspKXZ/Vq1dj3bp12LRpE3Jzc+Hq6oqwsDCUl5eLWDkRERFZClGfzZSSkqK3nZiYCBcXF5w+fRpDhw6FIAiIj4/H4sWLMWbMGADAtm3b0LlzZ+zcuRMzZswwGFOj0UCj0ei21Wo1AECr1UKr1bbguyGi1tZwTvP8Jmp7TDmnLepBk2VlZQAAJycnAEBxcTFKSkoQHh6u66NQKBAcHIwTJ040Gmbi4uIQGxtr0J6ammoxt2AnIvMoKioCAOTk5KC0tFTkaojInBoebmsMiwkzgiBg7ty5CAoK0t2Er6SkBADQuXNnvb6dO3fG1atXGx0nJiYGc+fO1W2r1Wp4eHggPDwcKpWqhaonIjGcOnUKABAQEAB/f3+RqyEic2q4smIMiwkzs2bNwnfffYfjx48b7PvjR8IFQWjyY+IKhQIKhcKgXS6XQy6Xm6dYIrIIDec0z2+itseUc1rUBcANZs+ejQMHDiA9PR3u7u66dldXVwD/b4amwa1btwxma4iIiOjRJGqYEQQBs2bNwr59+/DNN9/A29tbb7+3tzdcXV2Rlpama6upqUFmZiaeeuqp1i6XiIiILJCol5mio6Oxc+dO7N+/H0qlUjcD4+joCDs7O8hkMrz11ltYuXIlevTogR49emDlypWwt7fH+PHjxSydiIiILISoYSYhIQEAEBISoteemJiIKVOmAAAWLFiA6upqzJw5E3fu3EFAQABSU1OhVCpbuVoiIiKyRKKGGUEQmu0jk8mwbNkyLFu2rOULIiIiIsmxiAXARERERA+LYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCRN1DCTlZWFkSNHws3NDTKZDMnJyXr7KyoqMGvWLLi7u8POzg69e/dGQkKCOMUSERGRRRI1zFRWVqJfv37YtGlTo/vnzJmDlJQU7NixA4WFhZgzZw5mz56N/fv3t3KlREREZKmsxXzxiIgIRERENLn/5MmTmDx5MkJCQgAAr732Gj799FPk5eUhKiqqlaokIiIiSyZqmGlOUFAQDhw4gKlTp8LNzQ0ZGRm4dOkS1q9f3+QxGo0GGo1Gt61WqwEAWq0WWq22xWsmotbTcE7z/CZqe0w5py06zGzYsAHTp0+Hu7s7rK2t0a5dO2zevBlBQUFNHhMXF4fY2FiD9tTUVNjb27dkuUTUyoqKigAAOTk5KC0tFbkaIjKnqqoqo/tafJjJzs7GgQMH4OXlhaysLMycORNdunTBsGHDGj0mJiYGc+fO1W2r1Wp4eHggPDwcKpWqtUonolZw6tQpAEBAQAD8/f1FroaIzKnhyooxLDbMVFdXY9GiRUhKSsKIESMAAH5+figoKMCaNWuaDDMKhQIKhcKgXS6XQy6Xt2jNRNS6Gs5pnt9EbY8p57TF3mem4Rp4u3b6JVpZWaG+vl6kqoiIiMjSiDozU1FRgcuXL+u2i4uLUVBQACcnJ3h6eiI4OBjz58+HnZ0dvLy8kJmZie3bt2PdunUiVk1ERESWRNQwk5eXh9DQUN12w1qXyZMnY+vWrdi1axdiYmIwYcIE3L59G15eXlixYgVef/11sUomIiIiCyNqmAkJCYEgCE3ud3V1RWJiYitWRERERFJjsWtmiIiIiIzBMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJImapjJysrCyJEj4ebmBplMhuTkZIM+hYWFGDVqFBwdHaFUKjFkyBBcu3at9YslIiIiiyRqmKmsrES/fv2wadOmRvcXFRUhKCgIvXr1QkZGBs6ePYslS5bA1ta2lSslIiIiS2Ut5otHREQgIiKiyf2LFy9GZGQkVq9erWvr1q1ba5RGREREEiFqmHmQ+vp6HD58GAsWLMDw4cNx5swZeHt7IyYmBqNHj27yOI1GA41Go9tWq9UAAK1WC61W29JlE1ErajineX4TtT2mnNMWG2Zu3bqFiooKrFq1CsuXL8f777+PlJQUjBkzBunp6QgODm70uLi4OMTGxhq0p6amwt7evqXLJqJWVFRUBADIyclBaWmpyNUQkTlVVVUZ3VcmCILQgrUYTSaTISkpSTfrcuPGDTz++ON4+eWXsXPnTl2/UaNGoX379vjiiy8aHaexmRkPDw+UlpZCpVK16HsgotZ16tQpBAUF4fjx4/D39xe7HCIyI7VajU6dOqGsrKzZ398WOzPTqVMnWFtbo0+fPnrtvXv3xvHjx5s8TqFQQKFQGLTL5XLI5XKz10lE4mk4p3l+E7U9ppzTFnufGRsbGwwePBgXL17Ua7906RK8vLxEqoqIiIgsjagzMxUVFbh8+bJuu7i4GAUFBXBycoKnpyfmz5+PcePGYejQoQgNDUVKSgoOHjyIjIwM8YomIiIiiyJqmMnLy0NoaKhue+7cuQCAyZMnY+vWrXj++efxySefIC4uDm+88QZ8fX2xd+9eBAUFiVUyERERWRhRw0xISAiaW388depUTJ06tZUqIiIiIqmx2DUzRERERMZgmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJEzXMZGVlYeTIkXBzc4NMJkNycnKTfWfMmAGZTIb4+PhWq4+IiIgsn6hhprKyEv369cOmTZse2C85ORk5OTlwc3NrpcqIiIhIKqzFfPGIiAhEREQ8sM/169cxa9YsHD16FCNGjGilyoiIiEgqRA0zzamvr8fEiRMxf/58PPHEE0Ydo9FooNFodNtqtRoAoNVqodVqW6ROIhJHwznN85uo7THlnLboMPP+++/D2toab7zxhtHHxMXFITY21qA9NTUV9vb25iyPiERWVFQEAMjJyUFpaanI1RCROVVVVRnd12LDzOnTp7F+/Xrk5+dDJpMZfVxMTAzmzp2r21ar1fDw8EB4eDhUKlVLlEpEIjl16hQAICAgAP7+/iJXQ0Tm1HBlxRgWG2aOHTuGW7duwdPTU9dWV1eHefPmIT4+HleuXGn0OIVCAYVCYdAul8shl8tbqlwiEkHDOc3zm6jtMeWcttgwM3HiRAwbNkyvbfjw4Zg4cSJeeeUVkaoiIiIiSyNqmKmoqMDly5d128XFxSgoKICTkxM8PT3h7Oys118ul8PV1RW+vr6tXSoRERFZKFHDTF5eHkJDQ3XbDWtdJk+ejK1bt4pUFREREUmJqGEmJCQEgiAY3b+pdTJERET06OKzmYiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSRA0zWVlZGDlyJNzc3CCTyZCcnKzbp9VqsXDhQvTt2xft27eHm5sbJk2ahBs3bohXMBEREVkcUcNMZWUl+vXrh02bNhnsq6qqQn5+PpYsWYL8/Hzs27cPly5dwqhRo0SolIiIiCyVtZgvHhERgYiIiEb3OTo6Ii0tTa9t48aN8Pf3x7Vr1+Dp6dkaJRIREZGFEzXMmKqsrAwymQwdOnRoso9Go4FGo9Ftq9VqAPcvW2m12pYukYiaUVVVhYsXL5plrPPnz+v91xx8fX1hb29vtvGI6OGY8jtbMmHm3r17eOeddzB+/HioVKom+8XFxSE2NtagPTU1lT+giCxAUVER5s2bZ9Yxp02bZrax1q5di+7du5ttPCJ6OFVVVUb3lQmCILRgLUaTyWRISkrC6NGjDfZptVq88MILuHbtGjIyMh4YZhqbmfHw8EBpaekDjyOi1mHOmZny8nIcPnwYI0aMgFKpNMuYnJkhsgxqtRqdOnVCWVlZs7+/LX5mRqvV4sUXX0RxcTG++eabZt+QQqGAQqEwaJfL5ZDL5S1VJhEZydHREf7+/mYZS6vVoqKiAkOHDuX5TdTGmHJOW3SYaQgyP/74I9LT0+Hs7Cx2SURERGRhRA0zFRUVuHz5sm67uLgYBQUFcHJygpubG8aOHYv8/HwcOnQIdXV1KCkpAQA4OTnBxsZGrLKJiIjIgogaZvLy8hAaGqrbnjt3LgBg8uTJWLZsGQ4cOAAA6N+/v95x6enpCAkJaa0yiYiIyIKJGmZCQkLwoPXHFrI2mYiIiCwYn81EREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREkiZqmMnKysLIkSPh5uYGmUyG5ORkvf2CIGDZsmVwc3ODnZ0dQkJCcOHCBXGKJSIiIoskapiprKxEv379sGnTpkb3r169GuvWrcOmTZuQm5sLV1dXhIWFoby8vJUrJSIiIktlLeaLR0REICIiotF9giAgPj4eixcvxpgxYwAA27ZtQ+fOnbFz507MmDGjNUslIiIiCyVqmHmQ4uJilJSUIDw8XNemUCgQHByMEydONBlmNBoNNBqNbrusrAwAcPv2bWi12pYtmohalVarRVVVFX777TfI5XKxyyEiM2q4CiMIQrN9LTbMlJSUAAA6d+6s1965c2dcvXq1yePi4uIQGxtr0O7t7W3eAomIiKjFlZeXw9HR8YF9LDbMNJDJZHrbgiAYtP1eTEwM5s6dq9uur6/H7du34ezs/MDjiEh61Go1PDw88PPPP0OlUoldDhGZkSAIKC8vh5ubW7N9LTbMuLq6Arg/Q9OlSxdd+61btwxma35PoVBAoVDotXXo0KFFaiQiy6BSqRhmiNqg5mZkGljsfWa8vb3h6uqKtLQ0XVtNTQ0yMzPx1FNPiVgZERERWRJRZ2YqKipw+fJl3XZxcTEKCgrg5OQET09PvPXWW1i5ciV69OiBHj16YOXKlbC3t8f48eNFrJqIiIgsiahhJi8vD6GhobrthrUukydPxtatW7FgwQJUV1dj5syZuHPnDgICApCamgqlUilWyURkQRQKBZYuXWpwaZmIHi0ywZjPPBERERFZKItdM0NERERkDIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIpKMkJAQvPXWW2KXQUQWhmGGiFpVU4EkOTmZjxwhoofCMENEFo9PvCeiB2GYISKLs2zZMvTv3x+ff/45unXrBoVCgYZbYtXW1mLWrFno0KEDnJ2d8Y9//AO/v13Wjh07MGjQICiVSri6umL8+PG4deuWbn9GRgZkMhm+/vprDBo0CPb29njqqadw8eLFVn+fRGQeDDNEZJEuX76Mr776Cnv37kVBQYGufdu2bbC2tkZOTg42bNiADz/8EJs3b9btr6mpwXvvvYezZ88iOTkZxcXFmDJlisH4ixcvxtq1a5GXlwdra2tMnTq1Fd4VEbUEi31qNhE92mpqavDvf/8bjz32mF67h4cHPvzwQ8hkMvj6+uLcuXP48MMPMX36dADQCyXdunXDhg0b4O/vj4qKCjg4OOj2rVixAsHBwQCAd955ByNGjMC9e/dga2vbCu+OiMyJMzNEZJG8vLwMggwADBkyRG+hcGBgIH788UfU1dUBAM6cOYOoqCh4eXlBqVQiJCQEAHDt2jW9cfz8/HR/7tKlCwDoXY4iIulgmCGiVqVSqVBWVmbQfvfuXahUKt12+/btTR67srIS4eHhcHBwwI4dO5Cbm4ukpCQA92d6fk8ul+v+3BCO6uvrTX5NIhIfLzMRUavq1asXjhw5YtCem5sLX1/fZo/Pzs422O7RowesrKzwww8/oLS0FKtWrYKHhwcAIC8vzzyFE5HF4swMEbWqmTNnoqioCNHR0Th79iwuXbqEjz76CFu2bMH8+fObPf7nn3/G3LlzcfHiRXzxxRfYuHEj3nzzTQCAp6cnbGxssHHjRvz00084cOAA3nvvvZZ+S0QkMs7MEFGr6tq1K44dO4bFixcjPDwc9+7dQ8+ePbF161a88MILzR4/adIkVFdXw9/fH1ZWVpg9ezZee+01AMBjjz2GrVu3YtGiRdiwYQMGDhyINWvWYNSoUS39tohIRDLh9zdoICIiIpIYXmYiIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkn7/wB4bzvcLd/coAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a box-and-whisker plot for the urban cities ride count.\n",
    "x_labels = [\"Urban\"]\n",
    "fig, ax = plt.subplots()\n",
    "ax.boxplot(urban_ride_count, labels=x_labels)\n",
    "# Add the title, y-axis label and grid.\n",
    "ax.set_title(\"Ride Count Data (2019)\")\n",
    "ax.set_ylabel(\"Number of Rides\")\n",
    "ax.set_yticks(np.arange(10, 41, step=2.0))\n",
    "ax.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "ed3c5d64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a box-and-whisker plot for the suburban cities ride count.\n",
    "x_labels = [\"Suburban\"]\n",
    "fig, ax = plt.subplots()\n",
    "ax.boxplot(suburban_ride_count, labels=x_labels)\n",
    "# Add the title, y-axis label and grid.\n",
    "ax.set_title(\"Ride Count Data (2019)\")\n",
    "ax.set_ylabel(\"Number of Rides\")\n",
    "ax.set_yticks(np.arange(10, 41, step=2.0))\n",
    "ax.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "0558dc22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a box-and-whisker plot for the rural cities ride count.\n",
    "x_labels = [\"Rural\"]\n",
    "fig, ax = plt.subplots()\n",
    "ax.boxplot(rural_ride_count, labels=x_labels)\n",
    "# Add the title, y-axis label and grid.\n",
    "ax.set_title(\"Ride Count Data (2019)\")\n",
    "ax.set_ylabel(\"Number of Rides\")\n",
    "ax.set_yticks(np.arange(10, 41, step=2.0))\n",
    "ax.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "1f233d6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add all ride count box-and-whisker plots to the same graph.\n",
    "x_labels = [\"Urban\", \"Suburban\", \"Rural\"]\n",
    "ride_count_data = [urban_ride_count, suburban_ride_count, rural_ride_count]\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "ax.set_title(\"Ride Count Data (2019)\", fontsize=20)\n",
    "ax.set_ylabel(\"Number of Rides\", fontsize=14)\n",
    "ax.set_xlabel(\"City Types\", fontsize=14)\n",
    "ax.boxplot(ride_count_data, labels=x_labels)\n",
    "ax.set_yticks(np.arange(0, 45, step=3.0))\n",
    "ax.grid()\n",
    "# Save the figure.\n",
    "# plt.savefig(\"analysis/Fig2.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "396a70be",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "West Angela has the highest rider count.\n"
     ]
    }
   ],
   "source": [
    "# Get the city that matches 39.\n",
    "urban_city_outlier = urban_ride_count[urban_ride_count == 39].index[0]\n",
    "print(f\"{urban_city_outlier} has the highest rider count.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "082f871f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add all fare box-and-whisker plots to the same graph.\n",
    "x_labels = [\"Urban\", \"Suburban\", \"Rural\"]\n",
    "ride_fare_data = [urban_fares, suburban_fares, rural_fares]\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "ax.set_title(\"Ride Fare Data (2019)\", fontsize=20)\n",
    "ax.set_ylabel(\"Fare ($USD)\", fontsize=14)\n",
    "ax.set_xlabel(\"City Types\", fontsize=14)\n",
    "ax.boxplot(ride_fare_data, labels=x_labels)\n",
    "ax.set_yticks(np.arange(0, 45, step=3.0))\n",
    "ax.grid()\n",
    "# Save the figure.\n",
    "# plt.savefig(\"analysis/Fig.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "0813e1d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add all driver count box-and-whisker plots to the same graph.\n",
    "x_labels = [\"Urban\", \"Suburban\", \"Rural\"]\n",
    "driver_data = [urban_drivers, suburban_drivers, rural_drivers]\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "ax.set_title(\"Driver Count Data (2019)\", fontsize=20)\n",
    "ax.set_ylabel(\"Number of Drivers\", fontsize=14)\n",
    "ax.set_xlabel(\"City Types\", fontsize=14)\n",
    "ax.boxplot(driver_data, labels=x_labels)\n",
    "ax.set_yticks(np.arange(0, 45, step=3.0))\n",
    "ax.grid()\n",
    "# Save the figure.\n",
    "# plt.savefig(\"analysis/Fig2.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "ab00443e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type\n",
       "Rural        4327.93\n",
       "Suburban    19356.33\n",
       "Urban       39854.38\n",
       "Name: fare, dtype: float64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the sum of the fares for each city type.\n",
    "sum_fares_by_type = pyber_data_df.groupby([\"type\"]).sum()[\"fare\"]\n",
    "sum_fares_by_type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "a4ac92de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "63538.64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the sum of all the fares.\n",
    "total_fares = pyber_data_df[\"fare\"].sum()\n",
    "total_fares"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "8a12bdcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type\n",
       "Rural        6.811493\n",
       "Suburban    30.463872\n",
       "Urban       62.724635\n",
       "Name: fare, dtype: float64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the percentage of fare for each city type.\n",
    "type_percents = 100 * sum_fares_by_type / total_fares\n",
    "type_percents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "b2a4ef07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import mpl to change the plot configurations using rcParams.\n",
    "import matplotlib as mpl\n",
    "\n",
    "# Build Pie Chart\n",
    "plt.subplots(figsize=(10, 6))\n",
    "plt.pie(\n",
    "    type_percents,\n",
    "    labels=[\"Rural\", \"Suburban\", \"Urban\"],\n",
    "    colors=[\"gold\", \"lightskyblue\", \"lightcoral\"],\n",
    "    explode=[0, 0, 0.1],\n",
    "    autopct=\"%1.1f%%\",\n",
    "    shadow=True,\n",
    "    startangle=150,\n",
    ")\n",
    "plt.title(\"% of Total Fares by City Type\")\n",
    "# Change the default font size from 10 to 14.\n",
    "mpl.rcParams[\"font.size\"] = 14\n",
    "# Save Figure\n",
    "# plt.savefig(\"analysis/Fig5.png\")\n",
    "# Show Figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "8af0aad1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type\n",
       "Rural        0.781557\n",
       "Suburban    12.472893\n",
       "Urban       86.745550\n",
       "Name: driver_count, dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the percentage driver count for each city type.\n",
    "type_percents = (\n",
    "    100\n",
    "    * pyber_data_df.groupby([\"type\"]).sum()[\"driver_count\"]\n",
    "    / pyber_data_df[\"driver_count\"].sum()\n",
    ")\n",
    "type_percents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "b835d309",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build Pie Chart\n",
    "plt.subplots(figsize=(10, 6))\n",
    "plt.pie(\n",
    "    type_percents,\n",
    "    labels=[\"Rural\", \"Suburban\", \"Urban\"],\n",
    "    colors=[\"gold\", \"lightskyblue\", \"lightcoral\"],\n",
    "    explode=[0.1, 0, 0],\n",
    "    autopct=\"%1.1f%%\",\n",
    "    shadow=True,\n",
    "    startangle=150,\n",
    ")\n",
    "plt.title(\"% of Drivers by City Type\")\n",
    "# Change the default font size from 10 to 14.\n",
    "mpl.rcParams[\"font.size\"] = 14\n",
    "# Save Figure\n",
    "# plt.savefig(\"analysis/Fig6.png\")\n",
    "# Show Figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "14447544",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type\n",
       "Rural        5.005212\n",
       "Suburban    26.766722\n",
       "Urban       68.228066\n",
       "Name: ride_id, dtype: float64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the percentage driver count for each city type.\n",
    "type_percents = (\n",
    "    100\n",
    "    * pyber_data_df.groupby([\"type\"]).sum()[\"ride_id\"]\n",
    "    / pyber_data_df[\"ride_id\"].sum()\n",
    ")\n",
    "type_percents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "453c5a52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build Pie Chart\n",
    "plt.subplots(figsize=(10, 6))\n",
    "plt.pie(\n",
    "    type_percents,\n",
    "    labels=[\"Rural\", \"Suburban\", \"Urban\"],\n",
    "    colors=[\"gold\", \"lightskyblue\", \"lightcoral\"],\n",
    "    explode=[0, 0.1, 0],\n",
    "    autopct=\"%1.1f%%\",\n",
    "    shadow=True,\n",
    "    startangle=150,\n",
    ")\n",
    "plt.title(\"% of Total Fares by City Type\")\n",
    "# Change the default font size from 10 to 14.\n",
    "mpl.rcParams[\"font.size\"] = 14\n",
    "# Save Figure\n",
    "# plt.savefig(\"analysis/Fig7.png\")\n",
    "# Show Figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "767b88c9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}