pyber_code.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "# Dependencies and Setup\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# File to Load (Remember to change these)\n",
    "city_data_to_load = \"city_data.csv\"\n",
    "ride_data_to_load = \"ride_data.csv\"\n",
    "\n",
    "# Read the City and Ride Data\n",
    "got_city_df = pd.read_csv(city_data_to_load)\n",
    "got_ride_df = pd.read_csv(ride_data_to_load)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\n",
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       "        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",
       "  </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"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "got_city_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>2018-01-14 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>2018-03-04 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>2018-02-24 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>2018-02-10 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>2018-03-06 04:28:35</td>\n",
       "      <td>34.58</td>\n",
       "      <td>3908451377344</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 city                 date   fare        ride_id\n",
       "0  Lake Jonathanshire  2018-01-14 10:14:22  13.83  5739410935873\n",
       "1  South Michelleport  2018-03-04 18:24:09  30.24  2343912425577\n",
       "2  Port Samanthamouth  2018-02-24 04:29:00  33.44  2005065760003\n",
       "3          Rodneyfort  2018-02-10 23:22:03  23.44  5149245426178\n",
       "4          South Jack  2018-03-06 04:28:35  34.58  3908451377344"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "got_ride_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "        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",
       "      <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>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-02-24 08:40:38</td>\n",
       "      <td>13.93</td>\n",
       "      <td>5628545007794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-02-13 12:46:07</td>\n",
       "      <td>14.00</td>\n",
       "      <td>910050116494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-02-16 13:52:19</td>\n",
       "      <td>17.92</td>\n",
       "      <td>820639054416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-02-01 20:18:28</td>\n",
       "      <td>10.26</td>\n",
       "      <td>9554935945413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-04-17 02:26:37</td>\n",
       "      <td>23.00</td>\n",
       "      <td>720020655850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          city  driver_count   type                 date   fare        ride_id\n",
       "0  Richardfort            38  Urban  2018-02-24 08:40:38  13.93  5628545007794\n",
       "1  Richardfort            38  Urban  2018-02-13 12:46:07  14.00   910050116494\n",
       "2  Richardfort            38  Urban  2018-02-16 13:52:19  17.92   820639054416\n",
       "3  Richardfort            38  Urban  2018-02-01 20:18:28  10.26  9554935945413\n",
       "4  Richardfort            38  Urban  2018-04-17 02:26:37  23.00   720020655850"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combine the data into a single dataset\n",
    "main_df = pd.merge(got_city_df, got_ride_df, on='city')\n",
    "\n",
    "# Display the data table for preview\n",
    "\n",
    "main_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bubble Plot of Ride Sharing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rural\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "2344  Bradshawfurt             7  Rural  2018-03-06 21:44:53  19.74   \n",
      "2345  Bradshawfurt             7  Rural  2018-03-24 18:53:18  57.51   \n",
      "2346  Bradshawfurt             7  Rural  2018-03-24 07:34:03  19.89   \n",
      "2347  Bradshawfurt             7  Rural  2018-02-18 22:21:26  34.32   \n",
      "2348  Bradshawfurt             7  Rural  2018-04-08 13:46:03  55.19   \n",
      "\n",
      "            ride_id  \n",
      "2344  6080367372860  \n",
      "2345  2301998876294  \n",
      "2346  7867402022145  \n",
      "2347  8881996813087  \n",
      "2348  1742954306812  \n",
      "10\n",
      "70\n",
      "40.06\n",
      "Rural\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "2341  Garzaport             7  Rural  2018-02-18 18:27:48  36.16   \n",
      "2342  Garzaport             7  Rural  2018-04-17 01:48:27  17.31   \n",
      "2343  Garzaport             7  Rural  2018-05-06 16:57:16  18.90   \n",
      "\n",
      "            ride_id  \n",
      "2341  2928337561347  \n",
      "2342  6092414045061  \n",
      "2343  8826696981094  \n",
      "3\n",
      "21\n",
      "24.12\n",
      "Rural\n",
      "                city  driver_count   type                 date   fare  \\\n",
      "2302  Harringtonfort             4  Rural  2018-01-06 07:38:40  47.33   \n",
      "2303  Harringtonfort             4  Rural  2018-02-17 04:42:56  30.58   \n",
      "2304  Harringtonfort             4  Rural  2018-04-16 16:30:50  17.39   \n",
      "2305  Harringtonfort             4  Rural  2018-03-10 10:11:37  19.02   \n",
      "2306  Harringtonfort             4  Rural  2018-02-26 07:03:11  54.66   \n",
      "\n",
      "            ride_id  \n",
      "2302  3849747342021  \n",
      "2303  6835140871685  \n",
      "2304  4023962353348  \n",
      "2305  6717313402790  \n",
      "2306  9201585331171  \n",
      "6\n",
      "24\n",
      "33.47\n",
      "Rural\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "2365  Jessicaport             1  Rural  2018-01-01 09:45:36  43.69   \n",
      "2366  Jessicaport             1  Rural  2018-01-14 07:09:17  18.05   \n",
      "2367  Jessicaport             1  Rural  2018-04-13 16:08:11  39.89   \n",
      "2368  Jessicaport             1  Rural  2018-03-18 16:59:40  33.72   \n",
      "2369  Jessicaport             1  Rural  2018-05-01 08:14:47  22.44   \n",
      "\n",
      "            ride_id  \n",
      "2365  2424875833354  \n",
      "2366  5405362355006  \n",
      "2367  6511242590852  \n",
      "2368  3046889917159  \n",
      "2369  3725278487786  \n",
      "6\n",
      "6\n",
      "36.01\n",
      "Rural\n",
      "            city  driver_count   type                 date   fare  \\\n",
      "2308  Lake Jamie             4  Rural  2018-03-13 06:41:49  26.09   \n",
      "2309  Lake Jamie             4  Rural  2018-04-30 21:26:22  37.33   \n",
      "2310  Lake Jamie             4  Rural  2018-01-18 07:36:46  43.57   \n",
      "2311  Lake Jamie             4  Rural  2018-02-25 23:46:02  28.65   \n",
      "2312  Lake Jamie             4  Rural  2018-04-19 04:32:47  16.29   \n",
      "\n",
      "            ride_id  \n",
      "2308  1599158550738  \n",
      "2309  6755483470287  \n",
      "2310  1174957961925  \n",
      "2311  5815763839331  \n",
      "2312  3518682119233  \n",
      "6\n",
      "24\n",
      "34.36\n",
      "Rural\n",
      "                 city  driver_count   type                 date   fare  \\\n",
      "2314  Lake Latoyabury             2  Rural  2018-02-23 21:12:24  47.90   \n",
      "2315  Lake Latoyabury             2  Rural  2018-05-06 08:57:56  51.80   \n",
      "2316  Lake Latoyabury             2  Rural  2018-04-02 21:00:22  13.46   \n",
      "2317  Lake Latoyabury             2  Rural  2018-01-22 12:42:55  13.50   \n",
      "2318  Lake Latoyabury             2  Rural  2018-04-22 16:56:46  38.46   \n",
      "\n",
      "            ride_id  \n",
      "2314  3269652929887  \n",
      "2315  4018025271936  \n",
      "2316  8232864757802  \n",
      "2317  8493335787500  \n",
      "2318  1671918742352  \n",
      "11\n",
      "22\n",
      "26.06\n",
      "Rural\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "2279  Michaelberg             6  Rural  2018-03-27 18:27:34  54.85   \n",
      "2280  Michaelberg             6  Rural  2018-01-18 00:46:28  15.12   \n",
      "2281  Michaelberg             6  Rural  2018-03-27 21:48:36  38.62   \n",
      "2282  Michaelberg             6  Rural  2018-01-11 04:39:27  16.42   \n",
      "2283  Michaelberg             6  Rural  2018-04-22 17:28:52  19.27   \n",
      "\n",
      "            ride_id  \n",
      "2279  4421836952718  \n",
      "2280  1031697508349  \n",
      "2281   364151831884  \n",
      "2282  8800556719157  \n",
      "2283    26848733115  \n",
      "12\n",
      "72\n",
      "35.0\n",
      "Rural\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "2354  New Ryantown             2  Rural  2018-01-27 17:33:41  42.68   \n",
      "2355  New Ryantown             2  Rural  2018-04-18 19:43:54  42.97   \n",
      "2356  New Ryantown             2  Rural  2018-02-04 23:54:51  45.70   \n",
      "2357  New Ryantown             2  Rural  2018-04-30 01:50:44  50.81   \n",
      "2358  New Ryantown             2  Rural  2018-04-05 21:38:18  50.98   \n",
      "\n",
      "            ride_id  \n",
      "2354  7994603753131  \n",
      "2355   230914178346  \n",
      "2356  3570428225530  \n",
      "2357  5357550405010  \n",
      "2358  4834855490008  \n",
      "6\n",
      "12\n",
      "43.28\n",
      "Rural\n",
      "            city  driver_count   type                 date   fare  \\\n",
      "2266  Newtonview             1  Rural  2018-01-08 06:19:45  19.39   \n",
      "2267  Newtonview             1  Rural  2018-02-05 22:53:21  45.02   \n",
      "2268  Newtonview             1  Rural  2018-04-01 13:39:13  26.73   \n",
      "2269  Newtonview             1  Rural  2018-04-25 10:20:13  55.84   \n",
      "\n",
      "            ride_id  \n",
      "2266  5350347217506  \n",
      "2267  7075366458478  \n",
      "2268  3723530332713  \n",
      "2269  9990581345298  \n",
      "4\n",
      "4\n",
      "36.75\n",
      "Rural\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "2270  North Holly             8  Rural  2018-02-02 14:54:00  12.42   \n",
      "2271  North Holly             8  Rural  2018-02-16 17:02:51  39.46   \n",
      "2272  North Holly             8  Rural  2018-01-04 03:31:26  24.88   \n",
      "2273  North Holly             8  Rural  2018-04-21 21:14:22  18.54   \n",
      "2274  North Holly             8  Rural  2018-03-28 00:12:09  35.45   \n",
      "\n",
      "            ride_id  \n",
      "2270  1985256326182  \n",
      "2271  4571476032148  \n",
      "2272  4195619112933  \n",
      "2273  6259094156900  \n",
      "2274  3262489198068  \n",
      "9\n",
      "72\n",
      "29.13\n",
      "Rural\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "2325  North Jaime             1  Rural  2018-03-06 09:09:23  44.17   \n",
      "2326  North Jaime             1  Rural  2018-03-12 13:05:56  23.21   \n",
      "2327  North Jaime             1  Rural  2018-04-04 13:13:40  51.83   \n",
      "2328  North Jaime             1  Rural  2018-02-01 08:59:24  17.05   \n",
      "2329  North Jaime             1  Rural  2018-05-06 00:58:17  41.18   \n",
      "\n",
      "            ride_id  \n",
      "2325  1152195873170  \n",
      "2326  5987447089759  \n",
      "2327  9116047435376  \n",
      "2328  9481117811603  \n",
      "2329  7328094869758  \n",
      "8\n",
      "8\n",
      "30.8\n",
      "Rural\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "2297  Penaborough             6  Rural  2018-02-24 00:44:00  21.89   \n",
      "2298  Penaborough             6  Rural  2018-04-27 06:02:10  38.33   \n",
      "2299  Penaborough             6  Rural  2018-01-14 15:58:48  54.10   \n",
      "2300  Penaborough             6  Rural  2018-02-03 17:15:31  51.80   \n",
      "2301  Penaborough             6  Rural  2018-01-22 15:36:24  10.11   \n",
      "\n",
      "            ride_id  \n",
      "2297  2069309881916  \n",
      "2298   547013925055  \n",
      "2299   432925983890  \n",
      "2300  5383427508621  \n",
      "2301  4129933467653  \n",
      "5\n",
      "30\n",
      "35.25\n",
      "Rural\n",
      "                city  driver_count   type                 date   fare  \\\n",
      "2360  Randallchester             9  Rural  2018-04-13 11:13:31  43.22   \n",
      "2361  Randallchester             9  Rural  2018-02-19 03:52:47  58.55   \n",
      "2362  Randallchester             9  Rural  2018-02-11 05:42:29  25.78   \n",
      "2363  Randallchester             9  Rural  2018-03-25 13:36:46  10.37   \n",
      "2364  Randallchester             9  Rural  2018-04-07 23:42:07  10.79   \n",
      "\n",
      "            ride_id  \n",
      "2360  1076079536213  \n",
      "2361  8004803682564  \n",
      "2362  9010611749008  \n",
      "2363  3216382725494  \n",
      "2364  1615474447641  \n",
      "5\n",
      "45\n",
      "29.74\n",
      "Rural\n",
      "                city  driver_count   type                 date   fare  \\\n",
      "2250  South Jennifer             7  Rural  2018-04-01 09:32:45  21.63   \n",
      "2251  South Jennifer             7  Rural  2018-03-07 19:10:13  48.79   \n",
      "2252  South Jennifer             7  Rural  2018-04-05 14:35:42  32.20   \n",
      "2253  South Jennifer             7  Rural  2018-04-02 10:26:50  14.11   \n",
      "2254  South Jennifer             7  Rural  2018-04-10 20:46:11  43.25   \n",
      "\n",
      "            ride_id  \n",
      "2250  9135979586871  \n",
      "2251  9730627367446  \n",
      "2252   683983658392  \n",
      "2253  3828267773041  \n",
      "2254   623928772332  \n",
      "7\n",
      "49\n",
      "35.26\n",
      "Rural\n",
      "                   city  driver_count   type                 date   fare  \\\n",
      "2333  South Marychester             1  Rural  2018-02-19 00:23:09  32.72   \n",
      "2334  South Marychester             1  Rural  2018-01-02 11:18:32  52.12   \n",
      "2335  South Marychester             1  Rural  2018-02-21 19:16:48  55.40   \n",
      "2336  South Marychester             1  Rural  2018-01-15 21:44:26  30.26   \n",
      "2337  South Marychester             1  Rural  2018-03-27 12:07:50  34.42   \n",
      "\n",
      "            ride_id  \n",
      "2333  1481751072369  \n",
      "2334  3454018971635  \n",
      "2335  8822356392057  \n",
      "2336  3837056996776  \n",
      "2337  4230150157651  \n",
      "8\n",
      "8\n",
      "41.87\n",
      "Rural\n",
      "                 city  driver_count   type                 date   fare  \\\n",
      "2371  South Saramouth             7  Rural  2018-02-20 16:32:36  44.29   \n",
      "2372  South Saramouth             7  Rural  2018-01-28 15:55:33  31.25   \n",
      "2373  South Saramouth             7  Rural  2018-03-27 21:07:16  11.87   \n",
      "2374  South Saramouth             7  Rural  2018-04-12 18:11:50  57.23   \n",
      "\n",
      "            ride_id  \n",
      "2371  3622365199969  \n",
      "2372  7118046558393  \n",
      "2373   170351888128  \n",
      "2374  5081198789583  \n",
      "4\n",
      "28\n",
      "36.16\n",
      "Rural\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "2291  Taylorhaven             1  Rural  2018-04-06 01:01:29  45.31   \n",
      "2292  Taylorhaven             1  Rural  2018-03-05 21:19:53  38.18   \n",
      "2293  Taylorhaven             1  Rural  2018-04-03 05:41:37  38.92   \n",
      "2294  Taylorhaven             1  Rural  2018-04-01 16:37:45  54.65   \n",
      "2295  Taylorhaven             1  Rural  2018-03-05 04:46:17  29.45   \n",
      "\n",
      "            ride_id  \n",
      "2291  2275364435623  \n",
      "2292  8555320757742  \n",
      "2293  8300454322089  \n",
      "2294  9098060466868  \n",
      "2295  2159383884146  \n",
      "6\n",
      "6\n",
      "42.26\n",
      "Rural\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "2257  West Heather             4  Rural  2018-03-12 04:22:26  26.55   \n",
      "2258  West Heather             4  Rural  2018-02-22 09:01:37  17.40   \n",
      "2259  West Heather             4  Rural  2018-02-22 01:46:43  33.38   \n",
      "2260  West Heather             4  Rural  2018-02-04 16:29:23  13.97   \n",
      "2261  West Heather             4  Rural  2018-04-18 19:33:12  46.60   \n",
      "\n",
      "            ride_id  \n",
      "2257  7035849392668  \n",
      "2258  8702491506161  \n",
      "2259  5551691454078  \n",
      "2260  7118893881453  \n",
      "2261  3671003215967  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9\n",
      "36\n",
      "33.89\n",
      "Suburban\n",
      "               city  driver_count      type                 date   fare  \\\n",
      "2038  Barronchester            11  Suburban  2018-01-27 03:08:01  27.79   \n",
      "2039  Barronchester            11  Suburban  2018-05-05 04:03:11  30.38   \n",
      "2040  Barronchester            11  Suburban  2018-04-25 19:11:43  36.13   \n",
      "2041  Barronchester            11  Suburban  2018-03-31 06:05:30  44.24   \n",
      "2042  Barronchester            11  Suburban  2018-03-02 23:36:58  36.49   \n",
      "\n",
      "            ride_id  \n",
      "2038  6653622887913  \n",
      "2039  2281522828169  \n",
      "2040  2660177707065  \n",
      "2041  1252888806772  \n",
      "2042  4031573980778  \n",
      "16\n",
      "176\n",
      "36.42\n",
      "Suburban\n",
      "             city  driver_count      type                 date   fare  \\\n",
      "1996  Bethanyland            22  Suburban  2018-04-01 22:04:35  38.71   \n",
      "1997  Bethanyland            22  Suburban  2018-03-15 19:42:56  37.09   \n",
      "1998  Bethanyland            22  Suburban  2018-02-11 17:43:43  23.06   \n",
      "1999  Bethanyland            22  Suburban  2018-05-03 04:50:41  40.85   \n",
      "2000  Bethanyland            22  Suburban  2018-03-26 18:27:51  24.27   \n",
      "\n",
      "            ride_id  \n",
      "1996  8221076873967  \n",
      "1997  6243188816016  \n",
      "1998  4374740778403  \n",
      "1999  6700635166631  \n",
      "2000  7247229698318  \n",
      "18\n",
      "396\n",
      "32.96\n",
      "Suburban\n",
      "             city  driver_count      type                 date   fare  \\\n",
      "2054  Brandonfort            10  Suburban  2018-01-14 12:35:27  28.02   \n",
      "2055  Brandonfort            10  Suburban  2018-04-08 20:02:21  35.64   \n",
      "2056  Brandonfort            10  Suburban  2018-03-22 16:17:49  38.66   \n",
      "2057  Brandonfort            10  Suburban  2018-05-02 03:14:18  48.63   \n",
      "2058  Brandonfort            10  Suburban  2018-01-02 01:41:26  49.95   \n",
      "\n",
      "            ride_id  \n",
      "2054  8100258078935  \n",
      "2055  6109525300344  \n",
      "2056  4748541004175  \n",
      "2057  4443575880282  \n",
      "2058  1298465164057  \n",
      "19\n",
      "190\n",
      "35.44\n",
      "Suburban\n",
      "             city  driver_count      type                 date   fare  \\\n",
      "1674  Colemanland            23  Suburban  2018-04-20 02:52:45  20.83   \n",
      "1675  Colemanland            23  Suburban  2018-03-05 04:33:30  13.39   \n",
      "1676  Colemanland            23  Suburban  2018-03-02 02:11:21  36.81   \n",
      "1677  Colemanland            23  Suburban  2018-02-20 04:19:28  43.09   \n",
      "1678  Colemanland            23  Suburban  2018-01-01 00:46:46  47.74   \n",
      "\n",
      "            ride_id  \n",
      "1674  2981565641427  \n",
      "1675  8894920928658  \n",
      "1676   116923856607  \n",
      "1677  8700311126445  \n",
      "1678  2215912677020  \n",
      "22\n",
      "506\n",
      "30.89\n",
      "Suburban\n",
      "           city  driver_count      type                 date   fare  \\\n",
      "2178  Davidfurt            23  Suburban  2018-01-05 13:42:28  31.48   \n",
      "2179  Davidfurt            23  Suburban  2018-01-17 17:58:27  28.28   \n",
      "2180  Davidfurt            23  Suburban  2018-03-26 04:20:21  28.69   \n",
      "2181  Davidfurt            23  Suburban  2018-03-15 05:02:16  48.34   \n",
      "2182  Davidfurt            23  Suburban  2018-02-03 13:58:48  33.84   \n",
      "\n",
      "            ride_id  \n",
      "2178  1953915881204  \n",
      "2179  6647857817333  \n",
      "2180  5103497014248  \n",
      "2181  2406097680527  \n",
      "2182  7159296242243  \n",
      "17\n",
      "391\n",
      "32.0\n",
      "Suburban\n",
      "                city  driver_count      type                 date   fare  \\\n",
      "2214  East Aaronbury             7  Suburban  2018-03-19 10:43:53  20.04   \n",
      "2215  East Aaronbury             7  Suburban  2018-03-16 11:15:13  20.59   \n",
      "2216  East Aaronbury             7  Suburban  2018-01-27 09:53:22  28.56   \n",
      "2217  East Aaronbury             7  Suburban  2018-04-19 17:18:53  29.27   \n",
      "2218  East Aaronbury             7  Suburban  2018-04-08 18:59:12  21.29   \n",
      "\n",
      "            ride_id  \n",
      "2214  4117474421029  \n",
      "2215  6153017911679  \n",
      "2216  5981083119511  \n",
      "2217  7201712919915  \n",
      "2218   630560959632  \n",
      "9\n",
      "63\n",
      "25.66\n",
      "Suburban\n",
      "                 city  driver_count      type                 date   fare  \\\n",
      "2073  East Danielview            22  Suburban  2018-02-25 03:54:05  26.33   \n",
      "2074  East Danielview            22  Suburban  2018-04-19 10:36:41  28.28   \n",
      "2075  East Danielview            22  Suburban  2018-04-07 06:31:28  18.98   \n",
      "2076  East Danielview            22  Suburban  2018-03-02 02:47:45  14.32   \n",
      "2077  East Danielview            22  Suburban  2018-05-03 18:09:16  48.24   \n",
      "\n",
      "            ride_id  \n",
      "2073   513607352842  \n",
      "2074   149455664846  \n",
      "2075  6294116769232  \n",
      "2076  2106097871214  \n",
      "2077  3328095712316  \n",
      "17\n",
      "374\n",
      "31.56\n",
      "Suburban\n",
      "               city  driver_count      type                 date   fare  \\\n",
      "1983  East Kentstad            20  Suburban  2018-04-07 19:44:19  18.75   \n",
      "1984  East Kentstad            20  Suburban  2018-01-22 20:43:30  35.01   \n",
      "1985  East Kentstad            20  Suburban  2018-05-01 17:35:30  39.29   \n",
      "1986  East Kentstad            20  Suburban  2018-04-19 21:05:09  22.42   \n",
      "1987  East Kentstad            20  Suburban  2018-03-24 02:53:43  31.53   \n",
      "\n",
      "            ride_id  \n",
      "1983  6575961095852  \n",
      "1984  8750865857333  \n",
      "1985  1986613861926  \n",
      "1986  1136558207239  \n",
      "1987  1907259346172  \n",
      "13\n",
      "260\n",
      "29.82\n",
      "Suburban\n",
      "                city  driver_count      type                 date   fare  \\\n",
      "2090  East Marymouth             5  Suburban  2018-03-29 08:36:20  37.60   \n",
      "2091  East Marymouth             5  Suburban  2018-01-16 15:44:02  46.20   \n",
      "2092  East Marymouth             5  Suburban  2018-04-27 05:31:31  36.11   \n",
      "2093  East Marymouth             5  Suburban  2018-03-21 11:01:26  17.43   \n",
      "2094  East Marymouth             5  Suburban  2018-04-03 12:18:33  26.93   \n",
      "\n",
      "            ride_id  \n",
      "2090  6370863861570  \n",
      "2091  1181974978638  \n",
      "2092  8307460338356  \n",
      "2093  1621338088820  \n",
      "2094  3384028141202  \n",
      "27\n",
      "135\n",
      "30.84\n",
      "Suburban\n",
      "           city  driver_count      type                 date   fare  \\\n",
      "1756  Grayville             2  Suburban  2018-04-06 03:38:40  18.11   \n",
      "1757  Grayville             2  Suburban  2018-04-28 11:40:49  43.22   \n",
      "1758  Grayville             2  Suburban  2018-02-19 19:52:37  19.52   \n",
      "1759  Grayville             2  Suburban  2018-03-14 23:10:28  25.12   \n",
      "1760  Grayville             2  Suburban  2018-02-13 06:07:20  48.59   \n",
      "\n",
      "            ride_id  \n",
      "1756  6203774514474  \n",
      "1757  6018910939581  \n",
      "1758  9233978205608  \n",
      "1759  3752247297947  \n",
      "1760  4964947903977  \n",
      "15\n",
      "30\n",
      "27.76\n",
      "Suburban\n",
      "            city  driver_count      type                 date   fare  \\\n",
      "2151  Josephside            25  Suburban  2018-03-30 09:45:11  44.74   \n",
      "2152  Josephside            25  Suburban  2018-02-07 06:56:45  31.94   \n",
      "2153  Josephside            25  Suburban  2018-03-12 19:25:22  29.47   \n",
      "2154  Josephside            25  Suburban  2018-01-18 06:31:29  33.07   \n",
      "2155  Josephside            25  Suburban  2018-03-03 19:43:29  17.39   \n",
      "\n",
      "            ride_id  \n",
      "2151  5592692102803  \n",
      "2152  3185694946333  \n",
      "2153  1697181089451  \n",
      "2154  7129661940616  \n",
      "2155  1280375339328  \n",
      "27\n",
      "675\n",
      "32.86\n",
      "Suburban\n",
      "          city  driver_count      type                 date   fare  \\\n",
      "1644  Lake Ann             3  Suburban  2018-02-14 17:13:40  42.13   \n",
      "1645  Lake Ann             3  Suburban  2018-04-30 11:42:13  14.56   \n",
      "1646  Lake Ann             3  Suburban  2018-03-06 08:49:32  13.61   \n",
      "1647  Lake Ann             3  Suburban  2018-05-07 20:40:29  24.89   \n",
      "1648  Lake Ann             3  Suburban  2018-01-15 19:40:34  28.15   \n",
      "\n",
      "            ride_id  \n",
      "1644  6192401377301  \n",
      "1645  5470772614012  \n",
      "1646  1257553992293  \n",
      "1647  7356790519585  \n",
      "1648  3602888331541  \n",
      "12\n",
      "36\n",
      "30.89\n",
      "Suburban\n",
      "           city  driver_count      type                 date   fare  \\\n",
      "1941  Lake Omar            22  Suburban  2018-01-17 21:33:35  21.71   \n",
      "1942  Lake Omar            22  Suburban  2018-03-26 05:52:39  48.26   \n",
      "1943  Lake Omar            22  Suburban  2018-04-06 20:29:14  40.55   \n",
      "1944  Lake Omar            22  Suburban  2018-02-26 11:53:18  12.49   \n",
      "1945  Lake Omar            22  Suburban  2018-01-17 18:29:58  28.54   \n",
      "\n",
      "            ride_id  \n",
      "1941   966911700371  \n",
      "1942  5014086961990  \n",
      "1943  8969991191734  \n",
      "1944  4144926815389  \n",
      "1945  8212828472590  \n",
      "14\n",
      "308\n",
      "28.07\n",
      "Suburban\n",
      "                 city  driver_count      type                 date   fare  \\\n",
      "1771  Lake Robertside             4  Suburban  2018-01-11 20:17:36  46.51   \n",
      "1772  Lake Robertside             4  Suburban  2018-03-05 11:48:59  29.12   \n",
      "1773  Lake Robertside             4  Suburban  2018-04-30 20:45:11  22.26   \n",
      "1774  Lake Robertside             4  Suburban  2018-03-18 08:04:49  44.21   \n",
      "1775  Lake Robertside             4  Suburban  2018-01-13 18:22:18  28.37   \n",
      "\n",
      "            ride_id  \n",
      "1771  6574333011308  \n",
      "1772  4058488101142  \n",
      "1773   202043410246  \n",
      "1774  9839854233835  \n",
      "1775  5199680612896  \n",
      "25\n",
      "100\n",
      "31.26\n",
      "Suburban\n",
      "            city  driver_count      type                 date   fare  \\\n",
      "1656  Lake Scott            23  Suburban  2018-01-10 11:08:48  37.96   \n",
      "1657  Lake Scott            23  Suburban  2018-04-29 22:08:22  25.75   \n",
      "1658  Lake Scott            23  Suburban  2018-03-26 08:40:45  26.24   \n",
      "1659  Lake Scott            23  Suburban  2018-05-07 12:33:26  21.72   \n",
      "1660  Lake Scott            23  Suburban  2018-01-03 17:02:29  47.97   \n",
      "\n",
      "            ride_id  \n",
      "1656  8130669690525  \n",
      "1657  4959514979080  \n",
      "1658  1980313728671  \n",
      "1659  7626061808220  \n",
      "1660  8024881377404  \n",
      "18\n",
      "414\n",
      "31.89\n",
      "Suburban\n",
      "            city  driver_count      type                 date   fare  \\\n",
      "1796  Lewishaven            23  Suburban  2018-04-19 01:08:58  21.92   \n",
      "1797  Lewishaven            23  Suburban  2018-04-20 03:54:49  21.23   \n",
      "1798  Lewishaven            23  Suburban  2018-04-27 02:28:49  14.01   \n",
      "1799  Lewishaven            23  Suburban  2018-01-15 15:04:33  22.44   \n",
      "1800  Lewishaven            23  Suburban  2018-03-02 07:48:06  33.22   \n",
      "\n",
      "            ride_id  \n",
      "1796  7108986085790  \n",
      "1797  8139519107206  \n",
      "1798  6524982895248  \n",
      "1799  9661336278580  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1800   810001942984  \n",
      "12\n",
      "276\n",
      "25.24\n",
      "Suburban\n",
      "           city  driver_count      type                 date   fare  \\\n",
      "2134  Lewisland             4  Suburban  2018-02-14 17:38:17  42.31   \n",
      "2135  Lewisland             4  Suburban  2018-01-30 15:08:13  32.40   \n",
      "2136  Lewisland             4  Suburban  2018-01-25 20:46:18  32.38   \n",
      "2137  Lewisland             4  Suburban  2018-04-08 19:51:30  35.16   \n",
      "2138  Lewisland             4  Suburban  2018-01-28 11:38:16  35.60   \n",
      "\n",
      "            ride_id  \n",
      "2134   580385794188  \n",
      "2135  5099208436594  \n",
      "2136  8332226417129  \n",
      "2137  5715574777818  \n",
      "2138  9368246062437  \n",
      "17\n",
      "68\n",
      "34.61\n",
      "Suburban\n",
      "             city  driver_count      type                 date   fare  \\\n",
      "2117  Mezachester            14  Suburban  2018-03-25 12:57:21  21.89   \n",
      "2118  Mezachester            14  Suburban  2018-01-22 00:59:29  40.67   \n",
      "2119  Mezachester            14  Suburban  2018-03-18 02:32:55  40.81   \n",
      "2120  Mezachester            14  Suburban  2018-04-26 03:30:47  30.75   \n",
      "2121  Mezachester            14  Suburban  2018-01-06 02:08:30  39.83   \n",
      "\n",
      "            ride_id  \n",
      "2117  2294831365065  \n",
      "2118  1956901251838  \n",
      "2119  9431152912582  \n",
      "2120  3181640027590  \n",
      "2121  8422380883301  \n",
      "17\n",
      "238\n",
      "30.76\n",
      "Suburban\n",
      "            city  driver_count      type                 date   fare  \\\n",
      "1740  Myersshire            19  Suburban  2018-02-27 17:38:39  17.10   \n",
      "1741  Myersshire            19  Suburban  2018-04-29 06:08:03  17.99   \n",
      "1742  Myersshire            19  Suburban  2018-01-10 06:32:04  45.81   \n",
      "1743  Myersshire            19  Suburban  2018-01-06 11:43:01  22.80   \n",
      "1744  Myersshire            19  Suburban  2018-03-26 11:33:21  28.71   \n",
      "\n",
      "            ride_id  \n",
      "1740  5706770909868  \n",
      "1741  1127095356276  \n",
      "1742  7014255933887  \n",
      "1743   499304044207  \n",
      "1744  2180652304041  \n",
      "16\n",
      "304\n",
      "30.2\n",
      "Suburban\n",
      "            city  driver_count      type                 date   fare  \\\n",
      "1924  New Olivia            20  Suburban  2018-03-29 02:52:48  44.12   \n",
      "1925  New Olivia            20  Suburban  2018-02-05 19:25:58  47.15   \n",
      "1926  New Olivia            20  Suburban  2018-04-17 19:11:04  30.81   \n",
      "1927  New Olivia            20  Suburban  2018-03-27 01:37:59  34.65   \n",
      "1928  New Olivia            20  Suburban  2018-03-05 22:01:35  19.21   \n",
      "\n",
      "            ride_id  \n",
      "1924  7724469578438  \n",
      "1925  7736815814329  \n",
      "1926  1521286015117  \n",
      "1927  7345275995310  \n",
      "1928  8459793422858  \n",
      "17\n",
      "340\n",
      "34.05\n",
      "Suburban\n",
      "             city  driver_count      type                 date   fare  \\\n",
      "1696  New Raymond            17  Suburban  2018-02-25 21:40:18  20.44   \n",
      "1697  New Raymond            17  Suburban  2018-03-21 01:45:29  22.12   \n",
      "1698  New Raymond            17  Suburban  2018-03-18 12:07:10  36.26   \n",
      "1699  New Raymond            17  Suburban  2018-05-03 12:23:37  48.56   \n",
      "1700  New Raymond            17  Suburban  2018-01-05 17:58:39  22.50   \n",
      "\n",
      "            ride_id  \n",
      "1696  5984505117874  \n",
      "1697  6031755734913  \n",
      "1698  3151412877753  \n",
      "1699  9495029351539  \n",
      "1700  7832889931082  \n",
      "22\n",
      "374\n",
      "27.96\n",
      "Suburban\n",
      "                 city  driver_count      type                 date   fare  \\\n",
      "1892  New Shannonberg            20  Suburban  2018-03-19 08:13:37  25.46   \n",
      "1893  New Shannonberg            20  Suburban  2018-04-20 02:52:54  30.82   \n",
      "1894  New Shannonberg            20  Suburban  2018-02-01 04:31:15  34.09   \n",
      "1895  New Shannonberg            20  Suburban  2018-01-15 12:26:34  35.34   \n",
      "1896  New Shannonberg            20  Suburban  2018-05-05 05:25:56  16.77   \n",
      "\n",
      "            ride_id  \n",
      "1892   374752841670  \n",
      "1893  6829641849335  \n",
      "1894  8588717292946  \n",
      "1895  7445877019367  \n",
      "1896  8389782417445  \n",
      "17\n",
      "340\n",
      "28.38\n",
      "Suburban\n",
      "               city  driver_count      type                 date   fare  \\\n",
      "2195  Nicolechester            19  Suburban  2018-02-09 12:26:03  40.83   \n",
      "2196  Nicolechester            19  Suburban  2018-04-10 04:41:43  38.08   \n",
      "2197  Nicolechester            19  Suburban  2018-03-08 19:51:14  16.35   \n",
      "2198  Nicolechester            19  Suburban  2018-05-02 19:37:54  36.59   \n",
      "2199  Nicolechester            19  Suburban  2018-03-04 03:06:14  27.67   \n",
      "\n",
      "            ride_id  \n",
      "2195    85473064902  \n",
      "2196  8122088232004  \n",
      "2197  1045798809359  \n",
      "2198  6821451074310  \n",
      "2199  1790409286394  \n",
      "19\n",
      "361\n",
      "30.91\n",
      "Suburban\n",
      "               city  driver_count      type                 date   fare  \\\n",
      "2237  North Jeffrey            11  Suburban  2018-02-04 22:35:11  29.87   \n",
      "2238  North Jeffrey            11  Suburban  2018-02-28 08:46:35  31.14   \n",
      "2239  North Jeffrey            11  Suburban  2018-03-07 02:57:25  29.34   \n",
      "2240  North Jeffrey            11  Suburban  2018-02-28 05:55:43  46.40   \n",
      "2241  North Jeffrey            11  Suburban  2018-01-23 23:42:43  27.11   \n",
      "\n",
      "            ride_id  \n",
      "2237  7909567053548  \n",
      "2238  6795697365566  \n",
      "2239  2592274379299  \n",
      "2240  7546967271839  \n",
      "2241  6332047993934  \n",
      "13\n",
      "143\n",
      "29.24\n",
      "Suburban\n",
      "                    city  driver_count      type                 date   fare  \\\n",
      "2223  North Richardhaven             1  Suburban  2018-02-18 10:21:39  41.54   \n",
      "2224  North Richardhaven             1  Suburban  2018-04-07 00:32:23  36.32   \n",
      "2225  North Richardhaven             1  Suburban  2018-01-22 14:55:35  18.45   \n",
      "2226  North Richardhaven             1  Suburban  2018-03-03 06:14:36  18.17   \n",
      "2227  North Richardhaven             1  Suburban  2018-01-01 14:52:06  31.15   \n",
      "\n",
      "            ride_id  \n",
      "2223  4267383307027  \n",
      "2224  5014291527509  \n",
      "2225  2627726489605  \n",
      "2226  3252030700789  \n",
      "2227  7188584539017  \n",
      "14\n",
      "14\n",
      "24.7\n",
      "Suburban\n",
      "               city  driver_count      type                 date   fare  \\\n",
      "1909  North Timothy             7  Suburban  2018-04-06 10:06:34  38.39   \n",
      "1910  North Timothy             7  Suburban  2018-04-29 23:10:18  29.39   \n",
      "1911  North Timothy             7  Suburban  2018-04-20 07:06:27  46.24   \n",
      "1912  North Timothy             7  Suburban  2018-01-22 02:35:12  48.45   \n",
      "1913  North Timothy             7  Suburban  2018-01-14 16:59:57  15.06   \n",
      "\n",
      "            ride_id  \n",
      "1909  4781274767887  \n",
      "1910  6609337294720  \n",
      "1911  2785446996718  \n",
      "1912  5696833448345  \n",
      "1913  1236752354897  \n",
      "15\n",
      "105\n",
      "31.26\n",
      "Suburban\n",
      "            city  driver_count      type                 date   fare  \\\n",
      "1625  Port Shane             7  Suburban  2018-04-09 15:34:40  27.66   \n",
      "1626  Port Shane             7  Suburban  2018-04-23 16:05:47  42.26   \n",
      "1627  Port Shane             7  Suburban  2018-03-02 12:06:00  14.95   \n",
      "1628  Port Shane             7  Suburban  2018-03-26 04:33:30  19.03   \n",
      "1629  Port Shane             7  Suburban  2018-03-15 12:09:42  31.58   \n",
      "\n",
      "            ride_id  \n",
      "1625  4022340141966  \n",
      "1626  8341982666719  \n",
      "1627  2803204948363  \n",
      "1628  6010401984537  \n",
      "1629  2552978514662  \n",
      "19\n",
      "133\n",
      "31.08\n",
      "Suburban\n",
      "               city  driver_count      type                 date   fare  \\\n",
      "1808  Rodriguezview            20  Suburban  2018-03-27 19:44:37  49.65   \n",
      "1809  Rodriguezview            20  Suburban  2018-04-20 00:03:07  23.58   \n",
      "1810  Rodriguezview            20  Suburban  2018-02-17 14:10:00  22.76   \n",
      "1811  Rodriguezview            20  Suburban  2018-02-15 10:47:34  45.40   \n",
      "1812  Rodriguezview            20  Suburban  2018-01-09 11:55:20  29.19   \n",
      "\n",
      "            ride_id  \n",
      "1808  8748957571328  \n",
      "1809  3289957353125  \n",
      "1810  2750365542698  \n",
      "1811   520468701702  \n",
      "1812    38504866921  \n",
      "15\n",
      "300\n",
      "30.75\n",
      "Suburban\n",
      "           city  driver_count      type                 date   fare  \\\n",
      "1955  Sotoville            10  Suburban  2018-03-29 22:38:04  34.97   \n",
      "1956  Sotoville            10  Suburban  2018-04-22 01:33:03  46.50   \n",
      "1957  Sotoville            10  Suburban  2018-01-25 06:31:47  24.13   \n",
      "1958  Sotoville            10  Suburban  2018-04-23 20:31:04  34.87   \n",
      "1959  Sotoville            10  Suburban  2018-01-01 02:07:24  24.07   \n",
      "\n",
      "            ride_id  \n",
      "1955  7313956062903  \n",
      "1956  7088151468507  \n",
      "1957  7372157726656  \n",
      "1958    99483095214  \n",
      "1959  7827431948090  \n",
      "11\n",
      "110\n",
      "31.98\n",
      "Suburban\n",
      "              city  driver_count      type                 date   fare  \\\n",
      "2014  South Brenda             1  Suburban  2018-04-28 04:21:34  27.86   \n",
      "2015  South Brenda             1  Suburban  2018-04-21 03:08:39  17.80   \n",
      "2016  South Brenda             1  Suburban  2018-01-19 00:13:41  44.36   \n",
      "2017  South Brenda             1  Suburban  2018-01-10 00:17:24  47.52   \n",
      "2018  South Brenda             1  Suburban  2018-02-19 12:50:35  29.37   \n",
      "\n",
      "            ride_id  \n",
      "2014  5857212189710  \n",
      "2015  3500924024641  \n",
      "2016  6108194089857  \n",
      "2017  3069086465155  \n",
      "2018   676014632508  \n",
      "24\n",
      "24\n",
      "33.96\n",
      "Suburban\n",
      "              city  driver_count      type                 date   fare  \\\n",
      "1718  South Teresa            21  Suburban  2018-01-29 12:51:02  38.47   \n",
      "1719  South Teresa            21  Suburban  2018-02-23 04:35:04  46.02   \n",
      "1720  South Teresa            21  Suburban  2018-04-02 04:02:51  23.78   \n",
      "1721  South Teresa            21  Suburban  2018-03-28 04:27:58  17.50   \n",
      "1722  South Teresa            21  Suburban  2018-04-19 07:57:59  17.27   \n",
      "\n",
      "            ride_id  \n",
      "1718  5746182119035  \n",
      "1719  4623132352357  \n",
      "1720   295848311917  \n",
      "1721  9665109040886  \n",
      "1722  6681698470401  \n",
      "22\n",
      "462\n",
      "31.22\n",
      "Suburban\n",
      "              city  driver_count      type                 date   fare  \\\n",
      "1966  Veronicaberg            20  Suburban  2018-01-19 23:24:08  19.28   \n",
      "1967  Veronicaberg            20  Suburban  2018-04-24 19:16:19  49.45   \n",
      "1968  Veronicaberg            20  Suburban  2018-02-02 03:49:35  26.42   \n",
      "1969  Veronicaberg            20  Suburban  2018-01-18 10:33:29  33.04   \n",
      "1970  Veronicaberg            20  Suburban  2018-01-08 16:01:36  30.66   \n",
      "\n",
      "            ride_id  \n",
      "1966  2351082274727  \n",
      "1967  5877628036170  \n",
      "1968  8456789960080  \n",
      "1969  4341351420885  \n",
      "1970  7838733367694  \n",
      "17\n",
      "340\n",
      "32.83\n",
      "Suburban\n",
      "              city  driver_count      type                 date   fare  \\\n",
      "1823  Victoriaport            16  Suburban  2018-04-21 15:21:47  12.13   \n",
      "1824  Victoriaport            16  Suburban  2018-04-22 12:38:49  16.31   \n",
      "1825  Victoriaport            16  Suburban  2018-02-02 19:14:51  25.68   \n",
      "1826  Victoriaport            16  Suburban  2018-04-02 17:12:08  12.19   \n",
      "1827  Victoriaport            16  Suburban  2018-03-14 03:47:26  16.50   \n",
      "\n",
      "            ride_id  \n",
      "1823  3313120309203  \n",
      "1824  6069171955919  \n",
      "1825  8997392253805  \n",
      "1826  6988300070777  \n",
      "1827  7106912999135  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14\n",
      "224\n",
      "27.78\n",
      "Suburban\n",
      "             city  driver_count      type                 date   fare  \\\n",
      "1851  West Hannah            12  Suburban  2018-04-19 01:06:59  37.78   \n",
      "1852  West Hannah            12  Suburban  2018-03-22 20:18:32  25.86   \n",
      "1853  West Hannah            12  Suburban  2018-01-09 03:44:08  14.41   \n",
      "1854  West Hannah            12  Suburban  2018-02-01 02:36:34  33.85   \n",
      "1855  West Hannah            12  Suburban  2018-04-19 21:55:50  24.58   \n",
      "\n",
      "            ride_id  \n",
      "1851  2273047151891  \n",
      "1852  7624914034208  \n",
      "1853  1044914110317  \n",
      "1854  8296563108808  \n",
      "1855  2158777299955  \n",
      "21\n",
      "252\n",
      "29.55\n",
      "Suburban\n",
      "               city  driver_count      type                 date   fare  \\\n",
      "1872  West Kimmouth             4  Suburban  2018-01-04 10:24:04  20.69   \n",
      "1873  West Kimmouth             4  Suburban  2018-01-13 20:10:45  19.47   \n",
      "1874  West Kimmouth             4  Suburban  2018-02-08 21:11:13  27.93   \n",
      "1875  West Kimmouth             4  Suburban  2018-03-16 18:10:06  35.36   \n",
      "1876  West Kimmouth             4  Suburban  2018-02-06 00:42:46  13.59   \n",
      "\n",
      "            ride_id  \n",
      "1872  1687206700447  \n",
      "1873  6504880914159  \n",
      "1874   652476902663  \n",
      "1875  6758287550186  \n",
      "1876  8837906500110  \n",
      "20\n",
      "80\n",
      "29.87\n",
      "Suburban\n",
      "                 city  driver_count      type                 date   fare  \\\n",
      "1837  Williamsonville             2  Suburban  2018-01-09 23:59:36  48.73   \n",
      "1838  Williamsonville             2  Suburban  2018-02-01 17:54:05  38.90   \n",
      "1839  Williamsonville             2  Suburban  2018-01-17 01:26:36  28.65   \n",
      "1840  Williamsonville             2  Suburban  2018-02-12 17:54:17  26.49   \n",
      "1841  Williamsonville             2  Suburban  2018-03-19 08:30:01  44.85   \n",
      "\n",
      "            ride_id  \n",
      "1837  6507706939008  \n",
      "1838  1247989019244  \n",
      "1839  6114930962810  \n",
      "1840  8222482354071  \n",
      "1841  9120219182883  \n",
      "14\n",
      "28\n",
      "31.87\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "1520  Amandaburgh            12  Urban  2018-03-05 02:15:38  26.28   \n",
      "1521  Amandaburgh            12  Urban  2018-02-24 23:10:49  43.66   \n",
      "1522  Amandaburgh            12  Urban  2018-02-10 20:42:46  36.17   \n",
      "1523  Amandaburgh            12  Urban  2018-01-11 02:22:07  29.24   \n",
      "1524  Amandaburgh            12  Urban  2018-01-21 04:12:54   9.26   \n",
      "\n",
      "            ride_id  \n",
      "1520   906850928986  \n",
      "1521  6573820412437  \n",
      "1522  6455620849753  \n",
      "1523  7279902884763  \n",
      "1524  5528427024492  \n",
      "18\n",
      "216\n",
      "24.64\n",
      "Urban\n",
      "            city  driver_count   type                 date   fare  \\\n",
      "234  Barajasview            26  Urban  2018-01-15 02:59:07  19.52   \n",
      "235  Barajasview            26  Urban  2018-01-23 13:23:53  37.68   \n",
      "236  Barajasview            26  Urban  2018-02-08 18:07:22  24.49   \n",
      "237  Barajasview            26  Urban  2018-03-01 11:06:21  28.25   \n",
      "238  Barajasview            26  Urban  2018-02-19 02:25:34  26.83   \n",
      "\n",
      "           ride_id  \n",
      "234  8268107272481  \n",
      "235  4108452999906  \n",
      "236  2612169071005  \n",
      "237  7225827834994  \n",
      "238   937248382509  \n",
      "22\n",
      "572\n",
      "25.33\n",
      "Urban\n",
      "            city  driver_count   type                 date   fare  \\\n",
      "440  Carriemouth            52  Urban  2018-02-25 08:26:25  32.37   \n",
      "441  Carriemouth            52  Urban  2018-03-11 21:35:00  16.78   \n",
      "442  Carriemouth            52  Urban  2018-04-04 13:22:44  12.91   \n",
      "443  Carriemouth            52  Urban  2018-04-28 14:28:36  11.46   \n",
      "444  Carriemouth            52  Urban  2018-02-21 16:38:59  44.18   \n",
      "\n",
      "           ride_id  \n",
      "440  6918425016992  \n",
      "441  1519393006937  \n",
      "442  4276692439725  \n",
      "443  6991852632799  \n",
      "444  4528590417948  \n",
      "27\n",
      "1404\n",
      "28.31\n",
      "Urban\n",
      "                 city  driver_count   type                 date   fare  \\\n",
      "1241  Christopherfurt            41  Urban  2018-04-17 02:25:49  23.30   \n",
      "1242  Christopherfurt            41  Urban  2018-01-05 22:21:59  33.51   \n",
      "1243  Christopherfurt            41  Urban  2018-02-24 02:56:43  40.33   \n",
      "1244  Christopherfurt            41  Urban  2018-04-13 08:29:32  37.22   \n",
      "1245  Christopherfurt            41  Urban  2018-04-09 00:32:07  29.96   \n",
      "\n",
      "            ride_id  \n",
      "1241  7819057680096  \n",
      "1242  1901033209479  \n",
      "1243  9584185927129  \n",
      "1244  3288049380261  \n",
      "1245  9825842278797  \n",
      "27\n",
      "1107\n",
      "24.5\n",
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "1356  Deanville            49  Urban  2018-04-25 03:29:09  41.52   \n",
      "1357  Deanville            49  Urban  2018-05-01 21:53:42   8.28   \n",
      "1358  Deanville            49  Urban  2018-03-29 04:07:48   5.32   \n",
      "1359  Deanville            49  Urban  2018-03-24 00:26:39  30.55   \n",
      "1360  Deanville            49  Urban  2018-02-08 23:33:35  21.22   \n",
      "\n",
      "            ride_id  \n",
      "1356  6055928921559  \n",
      "1357   592955132597  \n",
      "1358  2612669233491  \n",
      "1359  5276110988605  \n",
      "1360  4786811969861  \n",
      "19\n",
      "931\n",
      "25.84\n",
      "Urban\n",
      "                city  driver_count   type                 date   fare  \\\n",
      "932  East Kaylahaven            65  Urban  2018-02-28 04:13:57  25.96   \n",
      "933  East Kaylahaven            65  Urban  2018-04-04 02:35:55  23.18   \n",
      "934  East Kaylahaven            65  Urban  2018-04-02 07:05:54   9.67   \n",
      "935  East Kaylahaven            65  Urban  2018-01-17 10:15:36  40.82   \n",
      "936  East Kaylahaven            65  Urban  2018-04-09 16:57:04  10.03   \n",
      "\n",
      "           ride_id  \n",
      "932  3662521920044  \n",
      "933    57422927996  \n",
      "934  2088463469235  \n",
      "935  6342488049671  \n",
      "936  8036811423686  \n",
      "29\n",
      "1885\n",
      "23.76\n",
      "Urban\n",
      "          city  driver_count   type                 date   fare        ride_id\n",
      "809  Erikaland            37  Urban  2018-02-18 07:47:15  20.62  3294151034077\n",
      "810  Erikaland            37  Urban  2018-03-11 02:19:28  27.39   132013691958\n",
      "811  Erikaland            37  Urban  2018-03-27 13:11:14  36.52  2195945483563\n",
      "812  Erikaland            37  Urban  2018-04-13 12:26:02  25.22  4847173431127\n",
      "813  Erikaland            37  Urban  2018-02-21 20:28:30  12.44  2705086825803\n",
      "12\n",
      "444\n",
      "24.91\n",
      "Urban\n",
      "            city  driver_count   type                 date   fare  \\\n",
      "643  Grahamburgh            61  Urban  2018-01-15 11:44:20  40.69   \n",
      "644  Grahamburgh            61  Urban  2018-04-06 13:48:54  23.87   \n",
      "645  Grahamburgh            61  Urban  2018-02-17 09:54:44  30.25   \n",
      "646  Grahamburgh            61  Urban  2018-03-12 02:44:01  22.97   \n",
      "647  Grahamburgh            61  Urban  2018-01-09 07:00:08  13.55   \n",
      "\n",
      "           ride_id  \n",
      "643   307021255892  \n",
      "644  1468249595739  \n",
      "645  4047930050046  \n",
      "646  4898014437105  \n",
      "647  5462604726666  \n",
      "25\n",
      "1525\n",
      "25.22\n",
      "Urban\n",
      "            city  driver_count   type                 date   fare  \\\n",
      "821  Huntermouth            37  Urban  2018-02-10 23:32:13  25.79   \n",
      "822  Huntermouth            37  Urban  2018-02-24 07:57:03  39.12   \n",
      "823  Huntermouth            37  Urban  2018-02-19 03:19:21   7.05   \n",
      "824  Huntermouth            37  Urban  2018-04-09 20:23:11  35.11   \n",
      "825  Huntermouth            37  Urban  2018-05-04 15:20:09  36.77   \n",
      "\n",
      "           ride_id  \n",
      "821  1880379662035  \n",
      "822   928039410570  \n",
      "823  1616522979657  \n",
      "824  3005607850321  \n",
      "825  7186624075617  \n",
      "24\n",
      "888\n",
      "28.99\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "1418  Hurleymouth            36  Urban  2018-05-04 21:50:30  21.44   \n",
      "1419  Hurleymouth            36  Urban  2018-03-22 11:19:58  32.85   \n",
      "1420  Hurleymouth            36  Urban  2018-03-03 11:28:17  36.31   \n",
      "1421  Hurleymouth            36  Urban  2018-03-26 20:22:28  41.15   \n",
      "1422  Hurleymouth            36  Urban  2018-02-20 10:47:47  17.07   \n",
      "\n",
      "            ride_id  \n",
      "1418  4039657784670  \n",
      "1419  8449290696111  \n",
      "1420   167035392736  \n",
      "1421  4707260150471  \n",
      "1422  7023698303898  \n",
      "28\n",
      "1008\n",
      "25.89\n",
      "Urban\n",
      "         city  driver_count   type                 date   fare        ride_id\n",
      "489  Jerryton            64  Urban  2018-03-03 17:50:23  28.08  6003411645536\n",
      "490  Jerryton            64  Urban  2018-01-04 16:38:59  37.20  5637872466976\n",
      "491  Jerryton            64  Urban  2018-01-05 15:36:46  37.91  1587079787234\n",
      "492  Jerryton            64  Urban  2018-04-13 21:47:30  32.08  8499177647057\n",
      "493  Jerryton            64  Urban  2018-03-27 12:48:21  13.29  8959844730593\n",
      "25\n",
      "1600\n",
      "25.65\n",
      "Urban\n",
      "        city  driver_count   type                 date   fare        ride_id\n",
      "348  Johnton            27  Urban  2018-01-17 02:12:01  32.19  8526302845313\n",
      "349  Johnton            27  Urban  2018-01-08 17:33:26  43.75   195318504552\n",
      "350  Johnton            27  Urban  2018-03-27 00:10:12  18.89  3634068282558\n",
      "351  Johnton            27  Urban  2018-04-05 07:12:55  22.87  1030619542522\n",
      "352  Johnton            27  Urban  2018-03-15 08:40:23  43.50  7134200570421\n",
      "21\n",
      "567\n",
      "26.79\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "276  Joneschester            39  Urban  2018-03-01 18:48:35  34.71   \n",
      "277  Joneschester            39  Urban  2018-01-30 17:41:45  36.78   \n",
      "278  Joneschester            39  Urban  2018-02-07 18:36:22   6.34   \n",
      "279  Joneschester            39  Urban  2018-01-03 05:45:12  25.47   \n",
      "280  Joneschester            39  Urban  2018-01-03 01:03:50  17.97   \n",
      "\n",
      "           ride_id  \n",
      "276  3343258153690  \n",
      "277  1664032953575  \n",
      "278  2605462716773  \n",
      "279  5540177253069  \n",
      "280  5439310968925  \n",
      "25\n",
      "975\n",
      "22.29\n",
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "845  Justinberg            39  Urban  2018-04-23 08:59:48  14.65   \n",
      "846  Justinberg            39  Urban  2018-04-26 08:41:02   8.83   \n",
      "847  Justinberg            39  Urban  2018-04-12 05:27:42  17.03   \n",
      "848  Justinberg            39  Urban  2018-05-03 02:49:42  36.06   \n",
      "849  Justinberg            39  Urban  2018-03-14 10:46:12  36.32   \n",
      "\n",
      "           ride_id  \n",
      "845  9878231118211  \n",
      "846  1823094898600  \n",
      "847  8374760616644  \n",
      "848   929541725138  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "849  6771691925128  \n",
      "30\n",
      "1170\n",
      "23.69\n",
      "Urban\n",
      "          city  driver_count   type                 date   fare        ride_id\n",
      "217  Karenberg            22  Urban  2018-03-11 17:26:12  36.15  7796761531541\n",
      "218  Karenberg            22  Urban  2018-04-29 20:54:19  28.41  9052850267417\n",
      "219  Karenberg            22  Urban  2018-03-30 11:38:39  24.64  4539326805168\n",
      "220  Karenberg            22  Urban  2018-03-05 01:38:53  44.10  9226782716583\n",
      "221  Karenberg            22  Urban  2018-04-27 14:57:38  44.73  3800715746753\n",
      "17\n",
      "374\n",
      "26.34\n",
      "Urban\n",
      "          city  driver_count   type                 date   fare        ride_id\n",
      "989  Karenside             5  Urban  2018-01-25 15:35:18  14.52  2652359361585\n",
      "990  Karenside             5  Urban  2018-04-02 19:22:47  41.93  4093612247143\n",
      "991  Karenside             5  Urban  2018-04-19 10:17:18  36.01  1322743709668\n",
      "992  Karenside             5  Urban  2018-04-14 05:11:17  13.13  3659608833762\n",
      "993  Karenside             5  Urban  2018-01-22 13:11:13  24.72  5326728612017\n",
      "28\n",
      "140\n",
      "27.45\n",
      "Urban\n",
      "                city  driver_count   type                 date   fare  \\\n",
      "906  Lake Danielberg            19  Urban  2018-02-24 12:05:12   9.63   \n",
      "907  Lake Danielberg            19  Urban  2018-02-13 11:01:59  43.96   \n",
      "908  Lake Danielberg            19  Urban  2018-03-17 19:23:29  10.18   \n",
      "909  Lake Danielberg            19  Urban  2018-02-24 19:34:24  34.82   \n",
      "910  Lake Danielberg            19  Urban  2018-02-28 15:08:06  44.96   \n",
      "\n",
      "           ride_id  \n",
      "906  9149328902854  \n",
      "907   100023890906  \n",
      "908  4714399161872  \n",
      "909  2442272882270  \n",
      "910  6319592522765  \n",
      "26\n",
      "494\n",
      "24.84\n",
      "Urban\n",
      "                    city  driver_count   type                 date   fare  \\\n",
      "1375  Lake Jonathanshire             5  Urban  2018-01-14 10:14:22  13.83   \n",
      "1376  Lake Jonathanshire             5  Urban  2018-04-07 20:51:11  31.25   \n",
      "1377  Lake Jonathanshire             5  Urban  2018-03-09 23:45:55  19.89   \n",
      "1378  Lake Jonathanshire             5  Urban  2018-04-07 18:09:21  24.28   \n",
      "1379  Lake Jonathanshire             5  Urban  2018-01-02 14:14:50  13.89   \n",
      "\n",
      "            ride_id  \n",
      "1375  5739410935873  \n",
      "1376  4441251834598  \n",
      "1377  2389495660448  \n",
      "1378  7796805191168  \n",
      "1379   424254840012  \n",
      "24\n",
      "120\n",
      "23.43\n",
      "Urban\n",
      "               city  driver_count   type                 date   fare  \\\n",
      "1139  Lake Scottton            58  Urban  2018-02-18 09:22:35  25.02   \n",
      "1140  Lake Scottton            58  Urban  2018-05-05 11:21:47  18.77   \n",
      "1141  Lake Scottton            58  Urban  2018-03-26 00:49:34   9.79   \n",
      "1142  Lake Scottton            58  Urban  2018-04-24 11:54:24   5.31   \n",
      "1143  Lake Scottton            58  Urban  2018-02-07 05:08:45  10.76   \n",
      "\n",
      "            ride_id  \n",
      "1139  3909343123179  \n",
      "1140   405381774029  \n",
      "1141  1827900502613  \n",
      "1142  9668336101351  \n",
      "1143  4201252290232  \n",
      "24\n",
      "1392\n",
      "23.81\n",
      "Urban\n",
      "        city  driver_count   type                 date   fare        ride_id\n",
      "301  Leahton            17  Urban  2018-02-26 18:42:15   8.85  6966668662612\n",
      "302  Leahton            17  Urban  2018-05-05 10:34:50  17.05  5846586406028\n",
      "303  Leahton            17  Urban  2018-04-02 17:39:37  22.76  5808733389189\n",
      "304  Leahton            17  Urban  2018-02-21 20:37:56  24.13  6759666489394\n",
      "305  Leahton            17  Urban  2018-02-13 11:40:59  16.79  4744794513785\n",
      "21\n",
      "357\n",
      "21.24\n",
      "Urban\n",
      "         city  driver_count   type                 date   fare        ride_id\n",
      "728  Liumouth            69  Urban  2018-01-11 17:15:17  36.78  1464517778842\n",
      "729  Liumouth            69  Urban  2018-01-15 07:55:34  14.55  4379351603939\n",
      "730  Liumouth            69  Urban  2018-04-12 03:38:12  43.34  7857233769715\n",
      "731  Liumouth            69  Urban  2018-02-01 20:17:16  24.81  5470070391967\n",
      "732  Liumouth            69  Urban  2018-03-30 03:13:00   4.66  3164443361610\n",
      "33\n",
      "2277\n",
      "26.15\n",
      "Urban\n",
      "          city  driver_count   type                 date   fare        ride_id\n",
      "514  Loganberg            23  Urban  2018-04-01 01:06:03   8.23   678728883160\n",
      "515  Loganberg            23  Urban  2018-01-07 19:02:38  16.26  9045377966666\n",
      "516  Loganberg            23  Urban  2018-01-21 16:26:37  22.86  1954301151475\n",
      "517  Loganberg            23  Urban  2018-03-16 11:46:25  23.99  9492898520301\n",
      "518  Loganberg            23  Urban  2018-03-27 13:32:59   4.72  6120689505628\n",
      "28\n",
      "644\n",
      "25.29\n",
      "Urban\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "193  Martinezhaven            25  Urban  2018-03-19 15:31:26   5.30   \n",
      "194  Martinezhaven            25  Urban  2018-02-20 19:32:45  13.34   \n",
      "195  Martinezhaven            25  Urban  2018-04-18 01:40:39  34.70   \n",
      "196  Martinezhaven            25  Urban  2018-04-18 18:37:14   5.81   \n",
      "197  Martinezhaven            25  Urban  2018-02-07 21:45:45   4.31   \n",
      "\n",
      "           ride_id  \n",
      "193   264337981979  \n",
      "194  2760692818274  \n",
      "195  2023088734313  \n",
      "196  2124254219877  \n",
      "197  9333328117367  \n",
      "24\n",
      "600\n",
      "22.65\n",
      "Urban\n",
      "                city  driver_count   type                 date   fare  \\\n",
      "1558  New Jacobville            50  Urban  2018-02-09 02:17:35   7.11   \n",
      "1559  New Jacobville            50  Urban  2018-01-05 05:02:35  34.11   \n",
      "1560  New Jacobville            50  Urban  2018-01-15 15:27:56  27.24   \n",
      "1561  New Jacobville            50  Urban  2018-02-04 04:57:28  27.63   \n",
      "1562  New Jacobville            50  Urban  2018-02-18 21:09:27  39.97   \n",
      "\n",
      "            ride_id  \n",
      "1558  3855046930326  \n",
      "1559  2828521502876  \n",
      "1560  3812959891670  \n",
      "1561  4329146429572  \n",
      "1562  8028701861067  \n",
      "18\n",
      "900\n",
      "26.77\n",
      "Urban\n",
      "                    city  driver_count   type                 date   fare  \\\n",
      "410  New Kimberlyborough            33  Urban  2018-02-07 01:10:11   9.34   \n",
      "411  New Kimberlyborough            33  Urban  2018-04-25 22:58:38  29.67   \n",
      "412  New Kimberlyborough            33  Urban  2018-03-14 16:47:25  27.90   \n",
      "413  New Kimberlyborough            33  Urban  2018-03-16 01:38:48  17.19   \n",
      "414  New Kimberlyborough            33  Urban  2018-05-01 13:56:38  22.59   \n",
      "\n",
      "           ride_id  \n",
      "410  7992781920789  \n",
      "411  4823568522144  \n",
      "412  6750798028086  \n",
      "413  2770472867019  \n",
      "414  9250925234627  \n",
      "30\n",
      "990\n",
      "22.59\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "1399  New Paulton            44  Urban  2018-05-01 03:12:49   8.28   \n",
      "1400  New Paulton            44  Urban  2018-05-03 12:09:12  21.67   \n",
      "1401  New Paulton            44  Urban  2018-03-10 01:07:52  28.00   \n",
      "1402  New Paulton            44  Urban  2018-02-20 16:59:35  24.29   \n",
      "1403  New Paulton            44  Urban  2018-02-08 17:11:44  39.65   \n",
      "\n",
      "            ride_id  \n",
      "1399  8527101897862  \n",
      "1400  9086555898522  \n",
      "1401  1067162551534  \n",
      "1402  7738134446199  \n",
      "1403  8505964159174  \n",
      "19\n",
      "836\n",
      "27.82\n",
      "Urban\n",
      "               city  driver_count   type                 date   fare  \\\n",
      "1498  New Paulville            44  Urban  2018-02-27 11:17:56  43.25   \n",
      "1499  New Paulville            44  Urban  2018-03-18 22:54:11  25.05   \n",
      "1500  New Paulville            44  Urban  2018-03-10 10:45:24   4.43   \n",
      "1501  New Paulville            44  Urban  2018-04-03 07:51:03  32.70   \n",
      "1502  New Paulville            44  Urban  2018-03-27 02:18:33   7.29   \n",
      "\n",
      "            ride_id  \n",
      "1498   793208410091  \n",
      "1499  5031803855561  \n",
      "1500  1213919861269  \n",
      "1501  9562561279062  \n",
      "1502  7046764870599  \n",
      "22\n",
      "968\n",
      "21.68\n",
      "Urban\n",
      "               city  driver_count   type                 date   fare  \\\n",
      "1117  North Barbara            18  Urban  2018-05-04 02:33:59  24.09   \n",
      "1118  North Barbara            18  Urban  2018-02-04 08:12:17  42.59   \n",
      "1119  North Barbara            18  Urban  2018-03-23 20:59:03  23.76   \n",
      "1120  North Barbara            18  Urban  2018-04-17 02:49:28  39.18   \n",
      "1121  North Barbara            18  Urban  2018-02-11 18:51:20  43.26   \n",
      "\n",
      "            ride_id  \n",
      "1117  9275090570165  \n",
      "1118  4971254409177  \n",
      "1119  5550267040448  \n",
      "1120  3503287273107  \n",
      "1121  8973500869212  \n",
      "22\n",
      "396\n",
      "23.49\n",
      "Urban\n",
      "               city  driver_count   type                 date   fare  \\\n",
      "1468  North Jasmine            33  Urban  2018-03-09 06:26:29  42.81   \n",
      "1469  North Jasmine            33  Urban  2018-02-08 19:03:17   4.86   \n",
      "1470  North Jasmine            33  Urban  2018-01-22 17:25:25  31.68   \n",
      "1471  North Jasmine            33  Urban  2018-02-22 01:56:17  25.33   \n",
      "1472  North Jasmine            33  Urban  2018-04-10 11:45:30  38.24   \n",
      "\n",
      "            ride_id  \n",
      "1468  5327642267789  \n",
      "1469  1276628602813  \n",
      "1470   712301571386  \n",
      "1471  1319966936025  \n",
      "1472  2954995327773  \n",
      "30\n",
      "990\n",
      "25.21\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "1321  North Jason             6  Urban  2018-03-28 22:28:44   9.19   \n",
      "1322  North Jason             6  Urban  2018-03-03 02:13:37  28.02   \n",
      "1323  North Jason             6  Urban  2018-03-08 20:06:21  25.21   \n",
      "1324  North Jason             6  Urban  2018-02-07 07:27:09  20.00   \n",
      "1325  North Jason             6  Urban  2018-03-18 10:10:37   6.41   \n",
      "\n",
      "            ride_id  \n",
      "1321  7007022521141  \n",
      "1322  2670554129601  \n",
      "1323  3180078116241  \n",
      "1324   473650019126  \n",
      "1325  2865826852282  \n",
      "35\n",
      "210\n",
      "22.74\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Urban\n",
      "               city  driver_count   type                 date   fare  \\\n",
      "684  North Madeline            19  Urban  2018-04-05 18:23:53  29.69   \n",
      "685  North Madeline            19  Urban  2018-02-25 04:32:14  13.58   \n",
      "686  North Madeline            19  Urban  2018-04-07 08:54:49  32.99   \n",
      "687  North Madeline            19  Urban  2018-03-04 17:20:57  21.38   \n",
      "688  North Madeline            19  Urban  2018-04-12 13:57:21   7.77   \n",
      "\n",
      "           ride_id  \n",
      "684   240702560536  \n",
      "685  4932836345153  \n",
      "686  1819348275778  \n",
      "687  9544488245764  \n",
      "688  9273340476908  \n",
      "25\n",
      "475\n",
      "22.62\n",
      "Urban\n",
      "                city  driver_count   type                 date   fare  \\\n",
      "1078  North Markport            22  Urban  2018-02-18 08:17:35  38.09   \n",
      "1079  North Markport            22  Urban  2018-04-26 04:45:54  44.37   \n",
      "1080  North Markport            22  Urban  2018-03-31 13:58:15  29.41   \n",
      "1081  North Markport            22  Urban  2018-01-21 11:49:50  27.68   \n",
      "1082  North Markport            22  Urban  2018-04-13 07:37:48  20.09   \n",
      "\n",
      "            ride_id  \n",
      "1078   925012921771  \n",
      "1079  1628416621603  \n",
      "1080  3093467204446  \n",
      "1081  4556759119631  \n",
      "1082  4311213165551  \n",
      "14\n",
      "308\n",
      "27.5\n",
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "1189  Pattyland            59  Urban  2018-01-30 12:35:37   8.57   \n",
      "1190  Pattyland            59  Urban  2018-02-01 22:43:37  32.03   \n",
      "1191  Pattyland            59  Urban  2018-02-15 15:13:00  44.03   \n",
      "1192  Pattyland            59  Urban  2018-04-26 08:31:23  19.99   \n",
      "1193  Pattyland            59  Urban  2018-04-03 03:29:52  14.06   \n",
      "\n",
      "            ride_id  \n",
      "1189  4688888414629  \n",
      "1190  2850242716720  \n",
      "1191  1556659025684  \n",
      "1192  8827777964944  \n",
      "1193  5399011565161  \n",
      "21\n",
      "1239\n",
      "23.98\n",
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "51  Port Angela            67  Urban  2018-04-17 06:23:18  16.34   \n",
      "52  Port Angela            67  Urban  2018-03-31 15:22:26  30.77   \n",
      "53  Port Angela            67  Urban  2018-04-09 14:34:27  11.90   \n",
      "54  Port Angela            67  Urban  2018-02-08 16:30:53  30.38   \n",
      "55  Port Angela            67  Urban  2018-03-04 03:26:39  40.35   \n",
      "\n",
      "          ride_id  \n",
      "51  7120534266772  \n",
      "52   662264490197  \n",
      "53  7009806605900  \n",
      "54  5165542108944  \n",
      "55  4930810733132  \n",
      "19\n",
      "1273\n",
      "23.84\n",
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "388  Port David             7  Urban  2018-03-17 14:42:43  33.11   \n",
      "389  Port David             7  Urban  2018-03-07 18:37:30  42.04   \n",
      "390  Port David             7  Urban  2018-03-27 11:56:08  15.64   \n",
      "391  Port David             7  Urban  2018-01-02 11:51:32   7.45   \n",
      "392  Port David             7  Urban  2018-01-07 20:03:19  20.49   \n",
      "\n",
      "           ride_id  \n",
      "388  1025683688009  \n",
      "389  9905958460368  \n",
      "390  5338482988567  \n",
      "391  6148349878448  \n",
      "392  5846260665949  \n",
      "22\n",
      "154\n",
      "25.85\n",
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "566  Port Frank            23  Urban  2018-02-02 14:14:37  41.47   \n",
      "567  Port Frank            23  Urban  2018-04-19 19:35:08  26.47   \n",
      "568  Port Frank            23  Urban  2018-04-06 21:38:50  18.08   \n",
      "569  Port Frank            23  Urban  2018-01-08 23:51:25  42.13   \n",
      "570  Port Frank            23  Urban  2018-02-05 10:34:09  20.10   \n",
      "\n",
      "           ride_id  \n",
      "566  6746609056348  \n",
      "567  6722706570956  \n",
      "568  5474889861628  \n",
      "569  2099160507410  \n",
      "570  4443074322856  \n",
      "33\n",
      "759\n",
      "27.2\n",
      "Urban\n",
      "               city  driver_count   type                 date   fare  \\\n",
      "1446  Port Johnbury             3  Urban  2018-04-27 16:22:23  25.67   \n",
      "1447  Port Johnbury             3  Urban  2018-05-05 06:26:50  25.30   \n",
      "1448  Port Johnbury             3  Urban  2018-03-21 02:20:43  32.80   \n",
      "1449  Port Johnbury             3  Urban  2018-04-11 10:26:44   9.10   \n",
      "1450  Port Johnbury             3  Urban  2018-05-02 12:46:00  42.42   \n",
      "\n",
      "            ride_id  \n",
      "1446  2746325666283  \n",
      "1447  2541021070088  \n",
      "1448  5450926790120  \n",
      "1449  7804751879143  \n",
      "1450  3245384693395  \n",
      "22\n",
      "66\n",
      "23.01\n",
      "Urban\n",
      "                    city  driver_count   type                 date   fare  \\\n",
      "1576  Port Samanthamouth            57  Urban  2018-02-24 04:29:00  33.44   \n",
      "1577  Port Samanthamouth            57  Urban  2018-04-16 18:34:44   9.20   \n",
      "1578  Port Samanthamouth            57  Urban  2018-01-23 09:08:20  35.51   \n",
      "1579  Port Samanthamouth            57  Urban  2018-02-03 07:07:01  18.03   \n",
      "1580  Port Samanthamouth            57  Urban  2018-04-22 03:32:37  29.67   \n",
      "\n",
      "            ride_id  \n",
      "1576  2005065760003  \n",
      "1577  8712247654732  \n",
      "1578  3116859378683  \n",
      "1579  9292190648631  \n",
      "1580  3154062122440  \n",
      "25\n",
      "1425\n",
      "25.64\n",
      "Urban\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "1092  Raymondhaven            11  Urban  2018-03-12 06:59:59  16.98   \n",
      "1093  Raymondhaven            11  Urban  2018-05-06 23:22:49  25.76   \n",
      "1094  Raymondhaven            11  Urban  2018-02-08 23:57:16   5.70   \n",
      "1095  Raymondhaven            11  Urban  2018-02-01 05:51:10  13.86   \n",
      "1096  Raymondhaven            11  Urban  2018-02-23 11:13:25   4.24   \n",
      "\n",
      "            ride_id  \n",
      "1092  6447701812060  \n",
      "1093  8721024233275  \n",
      "1094  3930029851451  \n",
      "1095  8721051413299  \n",
      "1096   294151163985  \n",
      "25\n",
      "275\n",
      "21.48\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "369  Reynoldsfurt            67  Urban  2018-03-25 14:33:27  34.06   \n",
      "370  Reynoldsfurt            67  Urban  2018-05-05 17:38:07  14.95   \n",
      "371  Reynoldsfurt            67  Urban  2018-01-17 21:35:17  24.84   \n",
      "372  Reynoldsfurt            67  Urban  2018-04-19 00:56:32  13.63   \n",
      "373  Reynoldsfurt            67  Urban  2018-04-11 09:09:53  42.97   \n",
      "\n",
      "           ride_id  \n",
      "369  6604420154219  \n",
      "370  1404730379464  \n",
      "371  5000179618056  \n",
      "372  7990078064277  \n",
      "373  1390651031898  \n",
      "19\n",
      "1273\n",
      "21.92\n",
      "Urban\n",
      "          city  driver_count   type                 date   fare        ride_id\n",
      "0  Richardfort            38  Urban  2018-02-24 08:40:38  13.93  5628545007794\n",
      "1  Richardfort            38  Urban  2018-02-13 12:46:07  14.00   910050116494\n",
      "2  Richardfort            38  Urban  2018-02-16 13:52:19  17.92   820639054416\n",
      "3  Richardfort            38  Urban  2018-02-01 20:18:28  10.26  9554935945413\n",
      "4  Richardfort            38  Urban  2018-04-17 02:26:37  23.00   720020655850\n",
      "28\n",
      "1064\n",
      "22.37\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "1601  Roberthaven            47  Urban  2018-05-04 14:48:56  25.66   \n",
      "1602  Roberthaven            47  Urban  2018-02-24 10:26:34   7.80   \n",
      "1603  Roberthaven            47  Urban  2018-03-06 22:56:31  12.38   \n",
      "1604  Roberthaven            47  Urban  2018-03-14 16:12:38  36.84   \n",
      "1605  Roberthaven            47  Urban  2018-03-14 15:24:44  35.27   \n",
      "\n",
      "            ride_id  \n",
      "1601  1026197778354  \n",
      "1602  2180566685151  \n",
      "1603  3372963379040  \n",
      "1604  4123408925006  \n",
      "1605  4034558003134  \n",
      "24\n",
      "1128\n",
      "23.73\n",
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "256  Robertport            12  Urban  2018-03-06 09:51:08   6.73   \n",
      "257  Robertport            12  Urban  2018-03-20 19:11:26  20.21   \n",
      "258  Robertport            12  Urban  2018-02-18 15:01:19  43.47   \n",
      "259  Robertport            12  Urban  2018-04-03 01:20:38  15.14   \n",
      "260  Robertport            12  Urban  2018-02-28 22:50:15  13.39   \n",
      "\n",
      "           ride_id  \n",
      "256  9679756863064  \n",
      "257  9630923585394  \n",
      "258  7995689882173  \n",
      "259  6669724727514  \n",
      "260   681044064878  \n",
      "20\n",
      "240\n",
      "23.06\n",
      "Urban\n",
      "          city  driver_count   type                 date   fare        ride_id\n",
      "70  Rodneyfort            34  Urban  2018-02-10 23:22:03  23.44  5149245426178\n",
      "71  Rodneyfort            34  Urban  2018-03-02 18:03:20  44.26  2494064867705\n",
      "72  Rodneyfort            34  Urban  2018-02-03 00:48:41  44.86  2325699544245\n",
      "73  Rodneyfort            34  Urban  2018-04-25 20:57:43  21.70  8534600667414\n",
      "74  Rodneyfort            34  Urban  2018-01-30 12:34:42  16.99  5778730523049\n",
      "23\n",
      "782\n",
      "28.62\n",
      "Urban\n",
      "          city  driver_count   type                 date   fare        ride_id\n",
      "467  Rogerston            25  Urban  2018-05-08 01:54:18  32.69  1643407853276\n",
      "468  Rogerston            25  Urban  2018-02-23 19:13:13  14.04  7647140329924\n",
      "469  Rogerston            25  Urban  2018-03-24 02:56:21  39.60  9196190355530\n",
      "470  Rogerston            25  Urban  2018-03-16 20:49:51  43.82  4718959573846\n",
      "471  Rogerston            25  Urban  2018-03-02 00:54:29  25.14  1722619288127\n",
      "22\n",
      "550\n",
      "22.1\n",
      "Urban\n",
      "        city  driver_count   type                 date   fare        ride_id\n",
      "779  Royland            64  Urban  2018-01-07 02:23:48  24.50  3620854074841\n",
      "780  Royland            64  Urban  2018-01-01 03:46:50   7.57  5815378003370\n",
      "781  Royland            64  Urban  2018-01-02 20:08:57  10.19   668201417968\n",
      "782  Royland            64  Urban  2018-04-19 00:05:32  25.40  9847755706013\n",
      "783  Royland            64  Urban  2018-01-17 14:08:06  27.92  3147266211478\n",
      "30\n",
      "1920\n",
      "20.57\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "542  Simpsonburgh            21  Urban  2018-04-26 00:43:24  35.98   \n",
      "543  Simpsonburgh            21  Urban  2018-01-19 23:06:27  15.83   \n",
      "544  Simpsonburgh            21  Urban  2018-03-22 08:56:23  22.05   \n",
      "545  Simpsonburgh            21  Urban  2018-04-03 08:47:52   4.74   \n",
      "546  Simpsonburgh            21  Urban  2018-02-05 16:02:12  25.58   \n",
      "\n",
      "           ride_id  \n",
      "542   111953927754  \n",
      "543   233191052705  \n",
      "544  3495175591045  \n",
      "545  8556334983479  \n",
      "546  2038696705617  \n",
      "24\n",
      "504\n",
      "23.36\n",
      "Urban\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "875  South Evanton            11  Urban  2018-02-14 05:55:36  42.50   \n",
      "876  South Evanton            11  Urban  2018-01-07 18:47:02  43.61   \n",
      "877  South Evanton            11  Urban  2018-01-24 07:08:44  17.83   \n",
      "878  South Evanton            11  Urban  2018-04-28 08:15:09  22.86   \n",
      "879  South Evanton            11  Urban  2018-03-06 03:56:20  30.87   \n",
      "\n",
      "           ride_id  \n",
      "875  9953662403430  \n",
      "876  9122502715686  \n",
      "877  2996657789222  \n",
      "878  7585355194527  \n",
      "879  5811915354455  \n",
      "31\n",
      "341\n",
      "26.73\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "709  South Jack            46  Urban  2018-03-06 04:28:35  34.58   \n",
      "710  South Jack            46  Urban  2018-04-24 19:33:56  38.04   \n",
      "711  South Jack            46  Urban  2018-03-30 20:21:59   4.20   \n",
      "712  South Jack            46  Urban  2018-02-01 22:32:07  28.37   \n",
      "713  South Jack            46  Urban  2018-01-31 02:51:29  21.75   \n",
      "\n",
      "           ride_id  \n",
      "709  3908451377344  \n",
      "710  2197989679742  \n",
      "711  4817670763151  \n",
      "712  3372008354124  \n",
      "713  6971155853312  \n",
      "19\n",
      "874\n",
      "22.97\n",
      "Urban\n",
      "                 city  driver_count   type                 date   fare  \\\n",
      "1017  South Karenland             4  Urban  2018-01-08 03:28:48  35.09   \n",
      "1018  South Karenland             4  Urban  2018-02-12 06:52:03  36.01   \n",
      "1019  South Karenland             4  Urban  2018-05-08 02:31:25  41.33   \n",
      "1020  South Karenland             4  Urban  2018-03-03 14:48:30  37.30   \n",
      "1021  South Karenland             4  Urban  2018-04-22 21:37:41  22.86   \n",
      "\n",
      "            ride_id  \n",
      "1017  7995623208694  \n",
      "1018  4015929454731  \n",
      "1019  5688921852912  \n",
      "1020  4104001937078  \n",
      "1021  6728151431002  \n",
      "38\n",
      "152\n",
      "26.54\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "599  South Latoya            10  Urban  2018-03-11 12:26:48   9.52   \n",
      "600  South Latoya            10  Urban  2018-01-11 18:44:14  27.41   \n",
      "601  South Latoya            10  Urban  2018-02-12 16:32:49  30.22   \n",
      "602  South Latoya            10  Urban  2018-03-02 06:06:17  10.35   \n",
      "603  South Latoya            10  Urban  2018-03-19 16:19:22  31.72   \n",
      "\n",
      "           ride_id  \n",
      "599  1994999424437  \n",
      "600  8662301917375  \n",
      "601  7388420725356  \n",
      "602   338288902823  \n",
      "603   363818381250  \n",
      "19\n",
      "190\n",
      "20.09\n",
      "Urban\n",
      "                    city  driver_count   type                 date   fare  \\\n",
      "1210  South Michelleport            72  Urban  2018-03-04 18:24:09  30.24   \n",
      "1211  South Michelleport            72  Urban  2018-03-02 09:54:50  33.12   \n",
      "1212  South Michelleport            72  Urban  2018-01-08 09:38:14  23.77   \n",
      "1213  South Michelleport            72  Urban  2018-04-22 03:15:33  43.62   \n",
      "1214  South Michelleport            72  Urban  2018-03-03 16:13:34  41.62   \n",
      "\n",
      "            ride_id  \n",
      "1210  2343912425577  \n",
      "1211   813844006721  \n",
      "1212  4916160406018  \n",
      "1213  4663606096929  \n",
      "1214  2339775503972  \n",
      "31\n",
      "2232\n",
      "24.45\n",
      "Urban\n",
      "               city  driver_count   type                 date   fare  \\\n",
      "1290  South Phillip            38  Urban  2018-02-09 16:46:59   7.89   \n",
      "1291  South Phillip            38  Urban  2018-05-04 09:10:40  28.30   \n",
      "1292  South Phillip            38  Urban  2018-01-29 11:26:47  35.23   \n",
      "1293  South Phillip            38  Urban  2018-04-18 06:03:51  39.95   \n",
      "1294  South Phillip            38  Urban  2018-05-06 05:05:46  43.43   \n",
      "\n",
      "            ride_id  \n",
      "1290  3203192947260  \n",
      "1291  8696571163934  \n",
      "1292  7418234487567  \n",
      "1293  9719024631848  \n",
      "1294  2435201344352  \n",
      "31\n",
      "1178\n",
      "28.57\n",
      "Urban\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "1268  Valentineton            45  Urban  2018-03-02 14:44:47  39.77   \n",
      "1269  Valentineton            45  Urban  2018-02-01 14:11:33   9.68   \n",
      "1270  Valentineton            45  Urban  2018-02-27 00:40:41  25.40   \n",
      "1271  Valentineton            45  Urban  2018-03-25 20:45:53  22.53   \n",
      "1272  Valentineton            45  Urban  2018-01-10 17:29:33  19.91   \n",
      "\n",
      "            ride_id  \n",
      "1268  6770387655387  \n",
      "1269  2132098607750  \n",
      "1270  6152363850717  \n",
      "1271  2335054032577  \n",
      "1272   774511223608  \n",
      "22\n",
      "990\n",
      "24.64\n",
      "Urban\n",
      "            city  driver_count   type                 date   fare  \\\n",
      "154  West Angela            48  Urban  2018-01-12 01:45:27  26.86   \n",
      "155  West Angela            48  Urban  2018-01-10 12:17:31  12.74   \n",
      "156  West Angela            48  Urban  2018-03-08 01:08:42  41.06   \n",
      "157  West Angela            48  Urban  2018-03-10 11:23:00  27.10   \n",
      "158  West Angela            48  Urban  2018-01-30 18:08:35  19.13   \n",
      "\n",
      "           ride_id  \n",
      "154  4820052223501  \n",
      "155  2108723916092  \n",
      "156  6204872968343  \n",
      "157  1365318639571  \n",
      "158  2078144834391  \n",
      "39\n",
      "1872\n",
      "25.99\n",
      "Urban\n",
      "             city  driver_count   type                 date   fare  \\\n",
      "124  West Anthony            70  Urban  2018-03-06 02:27:01  10.02   \n",
      "125  West Anthony            70  Urban  2018-01-23 12:32:46  23.24   \n",
      "126  West Anthony            70  Urban  2018-02-24 06:14:16  39.20   \n",
      "127  West Anthony            70  Urban  2018-03-17 00:30:34  35.42   \n",
      "128  West Anthony            70  Urban  2018-01-10 02:31:33  32.34   \n",
      "\n",
      "           ride_id  \n",
      "124  9396763280782  \n",
      "125   596601397101  \n",
      "126  8491405671407  \n",
      "127  4561324147940  \n",
      "128  1479317039864  \n",
      "30\n",
      "2100\n",
      "24.74\n",
      "Urban\n",
      "                     city  driver_count   type                 date   fare  \\\n",
      "322  West Christopherberg            32  Urban  2018-03-18 17:14:06  12.64   \n",
      "323  West Christopherberg            32  Urban  2018-01-17 14:30:56   9.04   \n",
      "324  West Christopherberg            32  Urban  2018-01-23 21:23:07  30.93   \n",
      "325  West Christopherberg            32  Urban  2018-01-08 08:25:29  37.78   \n",
      "326  West Christopherberg            32  Urban  2018-03-21 00:14:02  43.87   \n",
      "\n",
      "           ride_id  \n",
      "322  1061090771392  \n",
      "323  5154845220316  \n",
      "324  5335678989278  \n",
      "325  8767059547253  \n",
      "326  5085480897932  \n",
      "26\n",
      "832\n",
      "24.42\n",
      "Urban\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "761  West Ericstad            25  Urban  2018-04-24 03:20:14   7.31   \n",
      "762  West Ericstad            25  Urban  2018-04-04 13:03:16  28.52   \n",
      "763  West Ericstad            25  Urban  2018-01-25 12:29:55  20.03   \n",
      "764  West Ericstad            25  Urban  2018-01-08 09:03:12  32.99   \n",
      "765  West Ericstad            25  Urban  2018-03-28 13:29:17  22.28   \n",
      "\n",
      "           ride_id  \n",
      "761  4292477885655  \n",
      "762  6432849151942  \n",
      "763  3276480043173  \n",
      "764  6688341118130  \n",
      "765  3135272644045  \n",
      "18\n",
      "450\n",
      "22.35\n",
      "Urban\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "1055  West Gabriel            57  Urban  2018-04-29 01:22:02  36.70   \n",
      "1056  West Gabriel            57  Urban  2018-01-15 14:51:33  13.38   \n",
      "1057  West Gabriel            57  Urban  2018-04-21 04:50:53   4.96   \n",
      "1058  West Gabriel            57  Urban  2018-01-16 06:23:21  25.97   \n",
      "1059  West Gabriel            57  Urban  2018-05-01 02:18:03  27.45   \n",
      "\n",
      "            ride_id  \n",
      "1055  4103498186235  \n",
      "1056  7560918647139  \n",
      "1057  2694140247746  \n",
      "1058  6590477525761  \n",
      "1059  2827457582877  \n",
      "23\n",
      "1311\n",
      "20.35\n",
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "961  West Heidi            28  Urban  2018-03-14 23:46:50  24.40   \n",
      "962  West Heidi            28  Urban  2018-04-03 03:16:18  24.76   \n",
      "963  West Heidi            28  Urban  2018-03-30 10:46:05  22.41   \n",
      "964  West Heidi            28  Urban  2018-03-26 09:45:05  22.33   \n",
      "965  West Heidi            28  Urban  2018-01-30 12:59:43  30.84   \n",
      "\n",
      "           ride_id  \n",
      "961  4908573010166  \n",
      "962  1820229390169  \n",
      "963  1711351640331  \n",
      "964   826311164930  \n",
      "965  8936556138183  \n",
      "28\n",
      "784\n",
      "23.13\n",
      "Urban\n",
      "                 city  driver_count   type                 date   fare  \\\n",
      "1163  West Josephberg            45  Urban  2018-02-19 16:22:09  36.39   \n",
      "1164  West Josephberg            45  Urban  2018-03-05 03:27:34  12.91   \n",
      "1165  West Josephberg            45  Urban  2018-02-09 14:07:54   4.42   \n",
      "1166  West Josephberg            45  Urban  2018-01-16 16:17:05   7.04   \n",
      "1167  West Josephberg            45  Urban  2018-02-17 06:28:32  41.49   \n",
      "\n",
      "            ride_id  \n",
      "1163  3322126516683  \n",
      "1164   102684585771  \n",
      "1165  8303790674379  \n",
      "1166  2507076269228  \n",
      "1167  2821329685338  \n",
      "26\n",
      "1170\n",
      "21.72\n",
      "Urban\n",
      "                    city  driver_count   type                 date   fare  \\\n",
      "668  West Patrickchester            25  Urban  2018-03-19 05:46:20  40.86   \n",
      "669  West Patrickchester            25  Urban  2018-03-07 15:47:07  23.66   \n",
      "670  West Patrickchester            25  Urban  2018-01-14 01:15:16  24.82   \n",
      "671  West Patrickchester            25  Urban  2018-02-09 05:54:52  16.10   \n",
      "672  West Patrickchester            25  Urban  2018-03-06 04:19:59  32.37   \n",
      "\n",
      "           ride_id  \n",
      "668   898889456779  \n",
      "669  3066093529306  \n",
      "670  5934939559689  \n",
      "671  9112333244288  \n",
      "672  3684669591726  \n",
      "16\n",
      "400\n",
      "28.23\n",
      "Urban\n",
      "           city  driver_count   type                 date   fare  \\\n",
      "93  West Robert            39  Urban  2018-02-15 04:21:47  12.28   \n",
      "94  West Robert            39  Urban  2018-04-05 03:18:56  44.58   \n",
      "95  West Robert            39  Urban  2018-01-21 17:21:50  27.11   \n",
      "96  West Robert            39  Urban  2018-04-13 06:56:12  32.94   \n",
      "97  West Robert            39  Urban  2018-01-04 06:10:40  35.35   \n",
      "\n",
      "          ride_id  \n",
      "93  1442502460354  \n",
      "94  4246011046064  \n",
      "95  1369907297609  \n",
      "96  9603611942427  \n",
      "97  9554287895527  \n",
      "31\n",
      "1209\n",
      "25.12\n",
      "Urban\n",
      "                 city  driver_count   type                 date   fare  \\\n",
      "618  West Samuelburgh            73  Urban  2018-05-03 14:33:41  41.12   \n",
      "619  West Samuelburgh            73  Urban  2018-05-02 13:55:01  38.77   \n",
      "620  West Samuelburgh            73  Urban  2018-03-03 03:17:20  25.17   \n",
      "621  West Samuelburgh            73  Urban  2018-03-03 16:07:24  27.48   \n",
      "622  West Samuelburgh            73  Urban  2018-03-07 01:51:26  14.55   \n",
      "\n",
      "           ride_id  \n",
      "618  7330842806458  \n",
      "619  2931685225267  \n",
      "620  1781749929829  \n",
      "621   100530645822  \n",
      "622  7160360480942  \n",
      "25\n",
      "1825\n",
      "21.77\n",
      "Urban\n",
      "            city  driver_count   type                 date   fare  \\\n",
      "28  Williamsstad            59  Urban  2018-01-23 17:51:24  19.62   \n",
      "29  Williamsstad            59  Urban  2018-03-29 21:43:04  35.58   \n",
      "30  Williamsstad            59  Urban  2018-02-13 20:07:49  33.72   \n",
      "31  Williamsstad            59  Urban  2018-05-01 01:26:21  26.81   \n",
      "32  Williamsstad            59  Urban  2018-02-23 17:42:40   4.68   \n",
      "\n",
      "          ride_id  \n",
      "28   125986195523  \n",
      "29  4747780858464  \n",
      "30  3796713212942  \n",
      "31  4542954169892  \n",
      "32  9109973457376  \n",
      "23\n",
      "1357\n",
      "24.36\n",
      "Urban\n",
      "              city  driver_count   type                 date   fare  \\\n",
      "1538  Williamsview            46  Urban  2018-01-03 16:19:25  18.93   \n",
      "1539  Williamsview            46  Urban  2018-03-12 06:47:43   8.35   \n",
      "1540  Williamsview            46  Urban  2018-01-09 15:24:41  44.46   \n",
      "1541  Williamsview            46  Urban  2018-01-15 00:10:14  44.33   \n",
      "1542  Williamsview            46  Urban  2018-04-07 00:32:37  18.92   \n",
      "\n",
      "            ride_id  \n",
      "1538  1979492913169  \n",
      "1539  1940440908308  \n",
      "1540  2195528331786  \n",
      "1541  4627033032394  \n",
      "1542    23948941587  \n",
      "20\n",
      "920\n",
      "26.6\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Obtain the x and y coordinates for each of the three city types\n",
    "\n",
    "colors = {\"Urban\":\"coral\", \"Suburban\":\"lightblue\", \"Rural\":\"yellow\"}\n",
    "city_labels = [\"Urban\", \"Suburban\", \"Rural\"]\n",
    "legend_color = [\"coral\", \"lightblue\", \"yellow\"] \n",
    "area_df = main_df.groupby([\"type\", \"city\"]) \n",
    "\n",
    "area_df.groups.keys()\n",
    "\n",
    "\n",
    "for type_key in area_df.groups.keys():\n",
    "    \n",
    "    city_type = type_key[0]\n",
    "    print(city_type)\n",
    "    print(area_df.get_group(type_key).head())\n",
    "\n",
    "    rides_per_city_ct = area_df.get_group(type_key).count()\n",
    "    print(rides_per_city_ct[0])\n",
    "\n",
    "    city_driver_ct_df = area_df[\"driver_count\"].get_group(type_key).sum() \n",
    "    print(city_driver_ct_df)\n",
    "\n",
    "    avg_fare_df = round(area_df[\"fare\"].get_group(type_key).mean(), 2)\n",
    "    print(avg_fare_df)\n",
    "    \n",
    "    # Build the scatter plots for each city types\n",
    "    #[0] getting first element of rides_per_city_ct so it will have the same dimesions as avg_fare_df\n",
    "    # alpha is a setting for the transparency of the circle\n",
    "    plt.scatter(rides_per_city_ct[0], avg_fare_df, s=city_driver_ct_df, marker=\"o\", facecolors=colors[city_type], alpha = 0.75, edgecolor = \"black\")\n",
    "    \n",
    "    index = index + 1\n",
    "   \n",
    "\n",
    "\n",
    "# Incorporate the other graph properties\n",
    "plt.grid(axis='both')\n",
    "plt.title(\"Pyber Ride Sharing Data (2016)\")\n",
    "plt.xlabel(\"Total Number of Rides (Per City)\")\n",
    "plt.ylabel(\"Average Fare ($)\")\n",
    "\n",
    "# Plotting text:  Coordinates based on grid\n",
    "plt.text(44, 37, \"Note: \\n\" \"Circle size correlates with driver count per city.\")\n",
    "\n",
    "# Create a legend\n",
    "handlelist = [plt.plot([], marker = \"o\", markeredgecolor = \"black\", ls = \"\", color=color)[0] for color in legend_color]\n",
    "plt.legend(city_labels, markerscale=1, scatterpoints=1)\n",
    "\n",
    "#Tight fit layout\n",
    "plt.tight_layout()\n",
    "\n",
    "# Save Figure\n",
    "plt.savefig(\"Pyber_Ride.png\")\n",
    "\n",
    "# Show plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Total Fares by City Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4327.93\n",
      "type\n",
      "Rural        4327.93\n",
      "Suburban    19356.33\n",
      "Urban       39854.38\n",
      "Name: fare, dtype: float64\n",
      "63538.63999999999\n"
     ]
    },
    {
     "data": {
      "image/png": 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H7Q6iPUhiPgaPR40dOZLbb72VWampHGvVtyDwNPA70HuadNwMd3/gAuAEoAQ49M33eg6ZN6LXLKngEOKY7sKb9Qe7g2hrkpiP4PEoB3D26adzw89+xrToaKKb8LBK4K/AfaBLG32ODLcCRgIXA32Ag0gFhxBNdR/erNta84BKqQHAm1rrUfXu8wLlWuv7j2j7tNX21daM4VvPIYn5Gx6PigOunDmTOddfzzSXC1czD3EQs3PwY6AbrcG0KjgmYio4UqhXwREf5XRdM2HAyZP7pU+RCg4hvuNvmCVEWyWBNTUxK6VcwL+RxNw+PB4VD9z0/e8z45prmO500pJqic3A7cDL0PgLbFVwTAXOA6IAH1YFR4+EmLjrJg6YOq5nilRwCPFtf8Wb9YvWOFBDiRk4B/gMc30oGxgNVGOGI3sAN2ut37SO8RxQt0jZDVrrz5RS0zAb1R4ERgHLgEt1A8m3zRKzUioIrMKUim0FLtNaF7fSsb0c5SPG8fJ4VCLw8zlzmH7FFUxzOnG0xnExFRy/Br24SXFkuLtgKji+zxEVHBnpiSlXje8/Y1h64mip4BDisN/izfpTSw/ShMS8Vmt9vXX/00BP4CxgMPAhMARwACGtdbVSaijwgtZ6opWYX8ck8j3Ap8CvtNZLjhVPayWgo6nSWo+zTrQI+GlzHqxU+/QOPR6VBNwyfz5n/OhHTG/FpAxmosmHoN4CNaqxxtkFvrLsAt+rwG3AUqAv5h2ZgsLy4l8tWrPgvk83PrGrtGprK8YoRCT7I965V7bCcY7VQ627/6Uj7n9Zax3SWm/EzPIdjvm0+y+l1CrgFcx1pDpLtda7tNYhzIJNAxoKpi0Tc32fA70BlFLTlFKH9/5SSv1NKXWF9fU2pdTvlFJLgPlKqauVUnlKqZVKqdeUUvGtGZTHo1KAX19yCdMvuYTTHQ7aqit6FrAS1JOgejfWOLvAdyC7wPdvzMefzZgfYirAZzuLfNe/tfLZfy3b9t+iqlpZZFwIeBzv3DktPEYh1t9YPWmY4QcwG8vWd2Qi18AvMGWwYzHXjuoXDtRf0jQIDV+/avPEbPV8z8CMzTRFtdZ6stb6RWCB1jpTaz0WWAe0xjsjAB6PSgNu/dGPmHbBBUxtw6RcxwH8CNgI6k+gGq24yC7wbQceAP4MlAEDgUSANzbs3fzj15c/vmDdnoXltYFGK0GE6MCcwIt4504+3gNorcsBn1LqDAClVBpmUtixhhvmK6UcSqnBwCCgALMEg8/qFV9mxXVc2jIxxyml8jHvRGnAoiY+rv5HhlFKqU+sjwaXYMZoWszjUV2B2669ltPnzmVSOw/ZxmGGKjaDuglUg+V42QU+nV3gWwvchVlQ3InpQceGNPrp/B0rr8pe8egHWw4sqgmEZIt40VnFAq/hndu3Bcf4IXCHlbdygd9rrTcfo20B8BHwDnCd1roa8/d5uVLqC2AY3+1lN1lbXvwr11onKqWSMbPkXtFaP6KUmgz8Vmt9ltXu38ASrfXTSqltwESt9UHre1uBc7XWK63hjmla6ytacvHP41E9gF9feikTLriA01vjXFtoC6aC46VmVHBMwVRwRHNEBcc1EwZMGe9OOUkqOEQntQyYgjeryu5AWqLNhzK01iXAjcAtSqkoYDswUikVYyXtMxp4eBfMx4soTI+5RTwe1Q24bcYMBp93HlNaerxWMgh4AVgKanpjjbMLfDXZBb73gV8DbwNuoBfg2FdRU3X3xwU5t76/5tGCg2WrpBRSdEITMD3XiNYuF/+01iuAlcBFWuudwMvA18D/gBUNPPRO4EvMMMj6lsTg8agE4Kbhw+nxk59wZitXX7SGiUAuqLebUcHxGmZY5EugH9AdYENhecmvFq1ZcO+SDY/vKq3a0qZRCxF+rsA79yq7g2iJTjHBxONRLuCG9HQm/PWvnJWcTJrdMTUiBDwL3Al6V1Me4Mlw98OswTEas1Ti4TU4zhnWc/B5I3rNTI+P7tkWwQoRhqqBk/BmrbI7kOPR4ROzx6MUcJHDwff+9jcm9+nDILtjaoYq4BHgT6BLGmtsrcExHLMGR3/gANYaHAq4bGzfMd8b0mNGYrQrue1CFiJsrMAk54DdgTRXZ0jM04Af33YbA047LWzGlZurELgH+Dvo2sYaW2twTMCswZGKqa2sBohzOZx1a3DEuJyxbRizEOEgIlej69CJ2eNRg4E75swh4cc/Zn4HmMm8FbgDeKEZFRyTgfOBGMx00ABA94To2GsnDJwy3p1yslRwiA7MD2TizVppdyDN0WETs8ejkgHv0KEk//GPXBwTQ0fqHS7DrMGR25TG1s7ddWtwaEyJXQhgWHpi8pUn9p+R0TVxtEMW4RAd00pMco6YXbc7ZGK2Lvb93OFg2BNPcFb37jQ6DTpCvYvZReXrpjT2ZLi7Ah5MHXQ1sB9raukpfVJ7Xjam78y+yfGD2ypYIWx0B96se+wOoqk6amI+F5h77bWkn302Z9sdTxsLYZYavBP0zqY8wKrgOB8zp78Es8gUAGcN7THo/JG9ZnWNj5EKDtGRVABD8Wb57A6kKcKtlrfFPB7VD5jTuzeFM2c2OHmlo3AAlwMbQN0H6ljbYB2WXeDbATwE3IsprTu8BsfbG/dtufL1FY+/unZ3VnltoNFKECEiRAJmE4uI0KF6zB6PcmJ2snbfdx+TR4xgjN0x2aCIbyo4ahprbFVwnIgpsUvHrAF9uILj6gkDTppiKjji2jBmIdpDCDgRb1aThv7s1NES8yTgmlmzCP3sZ1xhdzw224ap4Hi+iRUc0Zix5/Mxa3DsxVzRpmt8dOx1EwdOGe9OPsnlcDR3uy1hk+LqWq7Kzmf1/lKUgic941mwbg9vbNhLtNPB4LQEnppzIimx315Hq+BgGRe+mnf4/7ccquQP04fz81OGcOuiNbyzaR/jeibz7NwJADy3cgdFVX5uOiUiLk+8jzdrlt1BNKbDJGZrwft7o6Op+Ne/uDw1lW52xxQmlmMuEL7flMZWBcdszBrS36rgGJKWkHTV+AEzhndNHCMVHOHv8oXLmNIvnavGD6A2GKLSH2Dp7mJmDOyKy+Hg1kVrALhv1rEXbQyGNL0ffJcvrzqdlNgoznnhCz750RQuWfAVt00aypC0RM554XPeveQ0opwRMzI6G29WU1e7tEXEvJJNMBeIvv56xklS/pbxwCJQ74Ea21jj7AJfeXaBbwFmDY7P+WYXFbWpqKL0tvfXLPzjJxse31FSeazlEEUYKK3x8/H2Qq48sT8A0U4HKbHRzB7cHZfD/Nmf0ieVXWUNL8L2wdYDDE5LoH9KPA4FtcEQWmuq/EGinA7+8tlGbjxpcCQlZYBb7Q6gMRH1ah6Lx6OGADOGDKF8ypSwWMozHM0GloN6FlS/xhpnF/gOZhf4ngR+B2zErAGdBrB096F9N7z99X8fy9v67MHKmoi4yt3ZbDlUQbf4aH70+nJOfPxDrspeQUXtt2cmP5m/ne8P6dHgcV5cvYuLR/UBoEtMFOeN6MWJj3/IwJR4kmOiyNtziDnD3W12Hm3kDLxzT7Q7iIZEfGK2apavAEpuuIEzo6KIsjmkZikuhvPPh+HDYcQI+Pzzb3+/pAR+8AMYOxZOOAGeesrcX1AAEyaY++seEwjAzJlQWXnMp3NgdlYoAPWXJlZw7MRUcPwJszDSQMxyrLyzad/WK19f8cTLa3YvKKsJtMpGu6J1BEKa5b4SfjJxICuunU5ClJN7l2w4/P17Pi7A5XBwyeg+xzxGbTBEdsFe5o/sdfi+X08aSv51M3jgzNHc+eE6/jBtBP9evo0LXlnK//u4oE3PqZX9yu4AGhLxiRk4HegzaRIxgwYx3O5gmuumm+B734P162HlSpOc6/v732HkSPO9xYvhl7+E2lp4/HG491549VW439ou4LHH4LLLIL7xnRFjgVuALaBuARXTUGNrF5X1wO8xiyqBWSQpVgP//Xrnqiuzl/9t0eb979UEghG9QHlH0Scpjj5JsZzcxyykeP7IXizfa6ofn8nfwZsb9/K/eRNo6FLBOxv3Md6dTI/E706aXeEz78PD0hN5duVOXp5/Eqv3l7KxsLwNzqZNzMc7t9FPjnaJ6MRsXfC7APDNm8cku+NprtJS+PhjuNLayTA6GlKO6MMqBWVlpq6ivBzS0sDlgqgoqKoyveOoKNPzfuMN+OEPmxVCKvAXTA/6MvNsx5Zd4AtlF/iWYUoSn8PscdYPiKoOhIKPLt3yxU/eWvnIl7uKPg2EQhG3oldH0jMxlr7J8RQcLAPMWPHIrl14d9M+7vt0I9kXnUJ8VMMFNi/UG8Y40p0fruMP04fjD4UIWgUEDqWo9Adb90TajguzgUdYiuiqDI9HnQ2cl5FB6X33cWM7bKjaqvLz4ZprvukRT5gADz8MCQnftCkrA4/H9KjLyuCll+Dss2HHDpOEa2pM7/npp2HOHDi9ZSPs+Zg1OJp0xdqq4JgJnMNRKzj6Tx/etctYqeCwR/7eYq7Kzqc2GGJQajxPzRlP5r8+oiYYIj3OjPid0ieNf54zjj1lVVyVnc/bl5wKQKU/QN+H3mPLjbNJjv326ODC9XtYubeUu6aZD6i35Kzmvc37GdMjif/Nm9i+J9kye4E+eLPC7t0kYhOzx6NigQeBEq+X6ePHc7LdMTXXV1/BKafAp5/CySebYY2kJLi73vykV18133/wQdi8GWbNMkk8qd4e25s2wR13mKR+yy1mqOPuu2HYsOMObREmQec3pbEnw50O/ACYhllD+vAaHJm9Urr/cGy/Wf1T4occdzRCtJ2wLJ2L5KGMTCAuPtnNjuDD3T5dd8WOrXvHHqwNRIfdu9+x9Oljbidbbynnnw/Ll3+7zVNPwbx5ZpBhyBAYOND0nuu7/XaTiB95BC65BH7/e3NrgVmYCo7nQPVvrHF2ga8wu8D3NGZCSwGmgiMdIG9P8f6fvfP1//6Rt+XZAxVSwSHCzv/ZHcDRRGRiPuP7fVw1wdQrAqF455gZN50YSpo/aJ/jj/1WlLzT9Y2Nm9VLK5YdevWrl3a+t/KObflbzt5zsKR3md0xH03PntC3r6mwAPjgAzOsUV+/fuZ+gH37TNtB9fZg+egj6N0bhg41480OBzidDVZmNJUCLsWMP98PKrWxB2QX+HYBDwN/BA5Sr4Lj3U37t16VveKJl1bvek0qOEQYmYd3btgtCRyRQxmZM2aOdqrKRx3Kn3TlXY+dkNq9d3Rjjwn6q6pDNTtKYllXnRq3UrlTVsT17boqJTa6ytbyuvx8uOoqM/wwaJDpIb/0kvneddfBnj1wxRXg85kLgLfdBpdear6vNcyeDS+/DKmpsG6d6TEHAqZCY1LrXg49hCmZexR0dWONPRluB99eg2M/ZpiDWJfDedX4AZlT+6dPjZU1OIT95uPNetXuIOqL0MQ8+xfAkOHjM11zr77hmuM9jtYhHaguLHUENpclulYHuicud/VJz0/qlrwtyRGRnyXaxQ7M7uX/BR1qrLG1BsckzBoccZgLhH6A9LjomGsnDpg8sVfKKbIGh7DRf/BmhdWu2hGXmDNnzO4K/BnYed51N80YNnb85NZ+jmCgpjZUvbM4WhdUp8au1O6UFXF9uq5MTogtb7Det5NZiVmD472mNPZkuBMwY9d162MfruAYnGoqOEZ0kwoOYYsteLPCagWmSEzM0zGz13bc9Oe//Sy+S5e09npuf3VRmcO/pTTBuSbQNWGFs1dafqI7dVOy0xnqzMnkfUwFx4qmNPZkuNP4poKjBrNRrAaY2Cul++Vj+83snxI/tI1iFeJYBuDN2m53EHUiMTH/DkgdOubE2PN/8vPr7I4nFPQHgtV7iqNCBZUpMV/rHkkrYvp2zU9OSjjUmcZONfACcDvobU15gCfD3QczvHEiUIrZCRyAMwd3H3DBCb1ndUuI6XWsxwvRyn6EN+tpu4OoE1GJud4wxo65V98wffj4zKl2x3QsgZrSCmq3lsY71tamJ+Q7eqWsSOiVvj4lyhXoyKPXNcA/gP8Huqixxp4MtwKGARcBgzCVHGVgSkIuHt3nhLOG9jgjKSaq0YoQIVroObxZzZs324YiLTFPxSxYtOOn9zx4dVJaekT1qEKhYChYvbfYFdxQkRTcMDr7AAAgAElEQVS9Ktijy4roPl3zk9O67Eto/NERpRhTwfFIMyo4xmFqSrtihjcOV3D8+MT+E6cN6Do11uVsfBUQIY7POrxZIxtv1j4iLTHfDnSLS+xSceN9j9zmcHSM2olAbXmlrtlRGudYW5MWl696payI752+NiUmuibSKxV2YpYNfbaJFRxRmAqO+RxRwZEWFxVz7YSBkzJ7p5wqFRyiDfiBeLxZYbHGS8Qk5swZs2OBvwO7TpwyY8D3/u/ysPnY0RZ0KKQDNQeKnYFNFV1cqwLdu6yI6pOe36Vbys6kxh8ddr4GbgP9TlMaWxUcdWtwgFnTIAgwMCW+yzUTBkwf0a3LOKngEK1sJN6sdXYHAZGVmIdgVjXbOefK608fOfHkaTaHZIugv7omVLOjOIb11WmxK+lpTZSJi6lodJJNGPgAU8GxvNGWNFzBMcGd0u3ycf1mDZAKDtF6zsObtcDuIMAsfRcpBmCuCdG9T9+wXUe1rTmjYmOcUcN6hBjGQTwcLIdVZZpATVGJw7+5PNG1yt8tcUVU77T8xB4pW5LDbLDnDOArUC9iKji2NtQ4u8BXBDzjyXC/j6ngGI9VwbHMV3xgma/4+dmDu/e/4ITes7onxPRu8+hFRzei8SbtI5J6zDdjknPRLX994tdRMTGdqRztuAQDtf5Q9a7iaF1QlRK7UvdMXhHbN31lcmJ8aTisDVDLNxUchY01tio4hgIXAoOBIkySBuDiUX1OOHuYVHCIFnkKb9aP7Q4CIiQxZ86Y7cSMLx9MSk1z/fSPD4X9ZorhzF9dXKb8W8oSHGv8XRPznb1TVyS40zak2DRRpgS4F3gYdKO7n1gVHGMxFRzdqFfBEe10OK4a33/itAFdT5cKDnEcFuLNmmt3EBA5iTkdaxr28PEn9Zp79U+vtjumjsZMlPEVR4U2VCXHfB3q0WVFTN9u+UnJCYXtleB2YSo4nmnFCo5TXA5HRO0BKWz1Ed6saXYHAZEzxpyKddGnW+8+7TYFuzNxOKNcjoR+XaEfJcykpAY27IJAbVklNdtK4hxra9Pi8h29U1fE9+66LiXK5Xe2cgh9gCeBX4C6DfTbDTXOLvD5gcWeDPdSzNi1B3MNwldU5a/505INuQNS4vOumTBg2shuXU6UCg7RBGEzDBYpPeaTgOuAHZ4f/2TqCZmnTLc7ps7MTJTZV+wKbqxIiloV7J60Irpven5SWpIvsRWf5kNMBcdXTWnsyXCnYio4pnNEBcd4d3K3K8b1mzkgJeH493QRncEOvFmNbgzRHiKlx9wDayWyxKTkSKzj7VAcDqfDEd8rDXqllXE6ZbWw2QeBHZVVumZ7SSzratLiVqpeKcvj+nRdkxoTXX08v2fTgaWgXsJUcGxpqHF2ge8Q8Gy9Co4JmOndB5f7Sg4s9616Yeagbv0uGtVntlRwiGNIabxJ+4iUHvP1wEjg4OW33nVerwGDRtkdk2gas+b1wRJnYFO5WfN6RVTv9Pwu3ZK3N2fN61rgn8DdoA821tiq4BiCWYNjCGaBpMMVHBee0HvkxaP7nOdQKryKCYXdSvFmJdsdBEROjzkN8/EUV1RUJEykEBalHCoqrnsKdE+p5DS2BWHbfgjuqa4JVe8qiWF9VWrsSnomr4jt23VlanzsUSfKRGO2mr8C1H3AQw1VcGQX+DSw0ZPhvgdTwXExptRyH1D10prda+cMd89OjHaFxR+hCBthMR0bIicxx2FNyZXE3DE4XbExzsQh3UMMoZBzKKyA1eWaQM2hUod/S1m8Y1UwLW5ZbN+uX8f1St+c4HBoB5AE3ANcD+p3wNMNVXBkF/hCwApPhns1MAW4HNgKUF4bKJXELI7gtzuAOpGSmGMxH2dxuSQxd1RKKaJi05KITUuqYSI+foSvCIL7awLB6t2HkhP27XCnrCnrnrgkOT0u7/4Y56G6Co63GjpudoHP78lwf4LZYAGA0ppASc9E+rb5SYlIUmF3AHUiKTFXATicTqlL7WScrhiXM3FQehWD0reUnMqWErM9myJQE+M64I1yfHRhWe2wn87LcB9zN3QrOZcBUYC/uNpfeqy2otMqtzuAOmF/8SNzxmyFScxBgFAwGDbjQMJeGlfP6oB7YlntsMuAjCY8pBDzu0RRVW1JmwYnItF+uwOoE/aJ2eLAqkkNBAK1NsciwlNThiX2ATEA+ytqpMcsjrTN7gDqhH1izsvN0ZhBeQdAMOCXxCyOpk8T2uzHSsy+smrpMYsjNbjaYXsK+8RsqQGcAAG/P2yunIqw0pQe8wGs36PtJZXSYxZH2mZ3AHUiJTFXY/1B+WtramyORYSnpiTmEqwhsd2l1RXBkA62bUgiwmyzO4A6kZKYD/eYK0pL5COoOJqmJOZSrMSsgQp/QHrNor6NdgdQJ1ISczlWad+hAwcO2RyLCE9N7TEfXmWuvDYoiVnU2YI364DdQdSJlMTswypzKvTtLrI5FhGeei0o8DX2+1yGScwKoLTGL5++RJ0v7A6gvkhJzLupu5q+Y5v0mMXRuAB3Qw2yC3wBTK85CkAmmYh6Prc7gPoiJTEfxBobLNy7pyIgJXPi6JoynHF4kklhpUwyEYdJYj4O3+ollxUV+ewKRIS1ptQyyyQTcaQKYKXdQdQXKYm5iHqxHtiza6eNsYjw1azZf3tkkokw3sObFVZLPURKYi7HfASNA9i5ecMOe8MRYaqpQxkyyUTUt8DuAI4UEYnZmpa9BkgGKFj+1c5I2HlFtLumlsyFAPaW11QFQqGw6imJdlcLvGl3EEeKiMRsWYvZyYKSooPVFWWlYVNzKMJGsyaZAFTUBmU4o3PLxZsVdr8DkZSYvzWuvH/n9gY35xSdUrMnmZTVyuy/Ti7shjEgshLzXszU7CiADSuXr7c3HBGGei4o8DW2kULdYvoyyURUAC/bHcTRRExizsvNCQHLMRuz8vXnn+zw19Ycc0NO0Sk5gF4NNbD2ASzGGhY7VCWTTDqx/4XjMAZEUGK2fIVV6hQMBEK+bVvX2RyPCD9NqWU+SN0kE9nJpDP7m90BHEukJeYNmCvqDoB1y5eusTccEYZkJxPRFJ/gzVpldxDHElGJOS83pwLIB9IB8pcs3lpVUSE9HlFfcyeZSGLunP5udwANiajEbPkMa6JJKBjUm1fnf2VzPCK8NCUxF2Fd/Nt6qFLe2DufTcBrdgfRkEhMzGsxO5rEACx56/XlQdk5W3yjWZNMCqtqa2qDIVkUq3O5K9ymYB8p4hJzXm5ONbAI6AZw6MC+St+2zTLWLOo0dZLJYRW1Aek1dx5fAy/YHURjIi4xW5Zg1jtwAOTl5nxpbzgijDS1x3z4d18mmXQqd+LNCvv1HCIyMefl5hzA1DR3A1i/PM9XuM8XNluPC1t1W1Dgi2mkTQX1qntKa6TH3El8gTcr2+4gmiIiE7NlEdZFQIBP334918ZYRPhQQO+GGliTTIo4PMmkVnrMHZw2q57dbHccTRXJiXkDsBVrJuCapZ/v2r9r5wZ7QxJhoinDGYcnmRyUnUw6PKXUP/FmhdUuJQ2J2MRsTdF+BUiqu++j7Fc/0B1gPdDammpunX8WN8+ZyU3nTOPFR/4CwL5dO7jtgrP56ZmTeOAX1+Kv/W4xwf5dO7l47CB+ee5MfnnuTB6/61YA/LU13H3V//HzH0zn3eefPtz+sTt/xZa1YVtnf7yakpj3Y1X27JNJJh2a1noPcJvdcTRHxCZmyzpgPdZY86ZV+fv3bNuy2t6QWi4qOgbv06/w4Ovv80DWIvKXLGZD/jKeu/8ezrn8av7+3qckJqXwwWtHv7jco19/Hlj4Pg8sfJ9rf38fAPlLFjPohDE8+PoHLHr5vwBsW78GrUMMGjm63c6tnTQlMfuQSSadglLqRrxZEfUzjujEbC2g/wqQgDVhYNFLz30QDAT8tgbWQkop4hISAAgG/AQCflCK1V8s4dQzzwFg2rnzWfr+u00+ptMVRW11NcHAN+WbLzz8Zy762a9aN/jw0JTEXFz3xZZDMnu0o9JaZ+PNCuvJJEcT0YnZsgVYAfQA8G3fWrJ66Wcf2htSywWDQX557kx+PGkMY0+bSs9+/UlISsbpcgGQ3tNN0f69R33s/l07uGXuLO68dB5rvzKVhGNPm0rxwf385sKzOffK68nLfY/BJ4whrUfPdjundtSsSSalNQF/TSBY3bYhifYW0vqAUuo6u+M4Hi67A2ipvNwcnTlj9svAPZi1mv3vPv/0FwNHjBqdlJrmtjm84+Z0Onlg4ftUlJZw3w1Xsmvzpu+0Ud+s935YavfuPJ6bR5fUNDav/pr7bvgRf31zMfGJXfjFA/8AIOD3c/dV/8dt/3iap/7k5aBvN9POPZ/MGWe2+Xm1k+ZPMvEHS2Jcztg2ike0M621dih1Kd4sn92xHI+O0GMmLzfHh9mJoBeYNTQ+ePX5N3QoFPEXAhOSkhl10qlsWLmMitKSw0MRhXt9pHbv8Z32UdExdElNA2DwqDH07DuAPVu/vdnLuy88w7Rz57Mh/ytc0VHc/NA/efWxh9v+ZNpPsyeZlNbIJJOORMO9eLNy7I7jeHWIxGzJwawalgpm0smWtasickZgSVEhFaVm2LOmuoqvP/+EPoOGMurkSXz+ntk3cvHCVzjpjO/2cEuKCgkGgwDs3bkd3/at9Ojb7/D3y0uKWbZ4EdPOnU9NdRUO5UApRW1NTTucWbtJW1Dgi2+kTSUQ4PAkE9nJpKMIhvTnDqXutDuOlugwiTkvN6cWeBKzk7YDIPupf35QXlK839bAjsOhA/u46/Lz+YXnDG6dfxZjTpvKxOmzuPSW23nj6Sf46ezTKCs+xBnnXwxAXu57vPDInwFYm/cFN885g5vnzOT+m67mGu+9dElJPXzsV/7xEOdf93OUUoybPI3Nq1fyC88MZs3/P1vOtQ01uGB+doFPA4VYlRlFspNJhxAM6UNOh7oAb1bQ7lhaQnWAst9vyZwx+3JgKtbmrQNHjOo6//pfXON0uRrbC050LDPnZbg/aKiBJ8P9S6AfcOiHY/uOOX9k77ntE5poCyGtAw6lZuHNWmx3LC3VYXrM9byC6QmlAWxdt/rgVx8uetvekIQNZCeTTiak9XUdISlDB0zMebk5lZjdCRKx1kLIXfBi/u4tmzrc9DbRoKYm5miAnSVVkpgjWHUg+KDrD6//x+44WkuHS8wAebk524H/YhazUQCv/vPhNytKSw7aGphoT82aZLK1uFISc4Sq9AdfjXU5b7E7jtbUIROzZTGQh1VCV1lWWrvgiUefr62prrQ1KtFemjXJpNIfDFQHgvK7EWEq/YEl8VHO/4uENZabo8MmZmuRo2cwf3zpALs2bzz03gvPvhiqqycTHVmzJ5mUy04mEaWsJrA0Pso1G29WRC/BcDQdNjED5OXmlAEPYWYEJgKs/vLTnZ+99+bCjlaNIr6j+TuZyCSTiHGoqnZFlxjXNLxZVXbH0hY6dGIGyMvN2Q08DHTFugL/yRsLVq/96suIX09DNChpQYGvSyNtqgE/ZpsyiqtlkkkkOFRVm69hUkdNytAJEjNAXm7OOszkk95Yf4TZTz728dZ1q5faGphoaw32mq1JJgew3rAPVcskk3B3qKp2pYbT0u57q8MmZegkidnyCfA60B+rUuPFR+9/Z3vB2mW2RiXaUnN3MpHEHMYOVNR8oeHUjp6UoRMlZmvt5oWYag2TnLXm+Yf//OaOjetX2BqcaCvNmmSyt7xahjLC1LbiyrcKCssndYakDJ0oMQPk5eYEgWeBT4EB1CXnv973xq7NG1faGpxoCzLJJMJprVm9v/RfN77z9Q8mP/lxyO542kunSswAebk5AeAp4DOs5KxDIf3fB//4+q7NGyQ5dyzNqmXeWlxZGpJynbARCIWCK/aW/HbUPz64xroe0Gl0usQMh5Pzk8CXWMMaOhTSzz3wx4UbVi7/1N7oRCtqamLWALXBUKg6EKpo25BEU1TUBqrydhdfNv7xD/9kdyx26JSJGSAvN8cP/AtYiuk5O9Ca1/758PsrPvnw3Y6w27Zo8iSTw1vByCQT++0pq97z9sZ9k079z0dH3224E+i0iRkOJ+fHMYvsD8Daauvd55/+cslbC1+VGYIRr8E1mS0l1EvMMsnEXit8xZ8/+uXmsfNfWdqpL8h36sQMhy8IPg+8jFmbNwZgyVsL17734rP/9dfWyiadkSthQYEvtaEG2QW+GsxEExfIJBO71AZDgXc27nv0rsXrp/1pyYZOv9hYp0/MYErp8nJz3sQMbbiBBID8JYu3vfS3+/9VXlpywNYARUs0tZbZmmQitcztbX9FTdGLq3dd8thXW2/KLvDV2h1POJDEXE9ebs4nwINACtZC+zs3FhQ9ec+d/963c/t6W4MTx6spifkA1iSTAxWSmNtLSGv92c7CL/7fxwUTf5i17OXOVnnREEnMR8jLzfkauBuoxVoytKK0pPbJP9310uovP/2gI+y83ck0a5KJTyaZtIuiqtqyJ5Ztu//eJRtnPvLl5q12xxNuWi0xK6VuV0qtUUp9rZTKV0qd3EBbr1KqRQtbK6UWK6UmtuQYx5KXm7MD+AOwERgIONGaN55+Ysl7Lz73XG11tZRURY6mJuYokEkm7SFv96E1d3247py3N+67NbvAJ39LR+FqjYMopU4FzgHGa61rlFJdsWZTtQWllLOtjl0nLzenNHPG7IeAOYAH2A9UrPgkd+uODeseO/eqn3q69+k7rK3jEC3W1JK5EMD2ksqykNbaoZRq5DGimYqqassWrvc9v3C97/bsAl+h3fGEs9bqMbuBg1rrGgCt9UGt9R6l1DYrSaOUmqiUWlzvMWOVUrlKqY1KqautNtOUUm/WNVBK/U0pdYX19Tal1O+UUkuA+VaTS5VSnymlViulTrLanWTdt8L6N8O6/wql1AKl1LvWc/65sZPKy80J5OXmvIZZ07kL0AOgcJ+v4j/33PFC3oc5bwYDgQ63SHcH06xJJoGQ1pX+YFnbhtS5BEKh4KLN+5fd/N6qeQvX+66XpNy41krMOUBfpdQGpdQ/lFKnN+ExY4CzgVOB3ymlejXhMdVa68la6xet/0/QWp8GXI+ZyQewHpiqtT4R+B3wx3qPHwdcCIwGLlRKNeWPlrzcnHzgTmA7ZmgjCuD9l/+37MVH//LPksKDu5tyHGGLptQyyySTNrKhsHzX7z5c98CjS7ec/XT+jvezC3ydZr2LlmiVxKy1LgcmANdgrnC/VNfTbcDrWusqrfVB4EPgpCY81UtH/P8L1vN/DCQppVKAZOAVpdRqTE/3hHrtP9Bal2itq4G1mOnYTZKXm3MA+Aum5tmNtV3Vjg3rix733vrkumVfLpYJKWGpqZNMZCeTVlRS7S//9/Jtb96Ss/q81fvLfpNd4Ntnd0yRpFXGmAG01kHMkpqLlVKrgMuBAN/8wsce+ZCj/H/99kd7zJEXCo52jLuBD7XWc5VSA6yY6tTU+zpIM8/fmozyXuaM2euBazGJfVcwEAgu/Pc/PuqfMWL1mRf98Kz0nr0GNee4ok3FLijwdZuX4T5mLXp2gc/vyXCXYz4J+YtlwfzjVuUPVn+w9cDqV9bsfuRQtX+BXNw7Pq3SY1ZKZSilhta7axzmY/82TE8a4LwjHjZHKRWrlEoHpmF2tN4OjFRKxSilkoEzGnnqC63nnwyUaK1LMD3muqGFK47rhBqRl5uzHVO18R5mDLMrwPaCdYVP/P43zy15a+GrNVVVMk4ZPpo1yaSoqlaGMpqpNhiqXbR5/8rr31r5lyeWbTvvmZU7npOkfPxaq8ecCDxqDSUEgE2YYY0RwH+UUr/FrORW31LgLcw06Lu11nsAlFIvA19jStUamy9/SCn1GZAE/Ni678/AM0qpm4Hclp7YseTl5lQDL2bOmP0l5tPBAGAvUP3Jm1lrln+cu/HsH141fdCIUScrh0Ou8NurL7C8kTYHgG5A+QHZyaTJAqFQ4POdhwqeXbnjo30VNU8By2UcueWULKLWcpkzZjuBycBFmDc7H1b51dAxJ/aYOf+Ss1O6dmvShUbRJn42L8P9t4YaeDLc5wHfA3ZP6Zfe61eThl7dPqFFppDWoeW+4k3P5O9Ysr2k6ingy+wCn1QotZJWG2PuzKyx548yZ8xeiRmymQoUA4c2fr1i38ZV+U+ecd5FJ46bPH1mdExMvK3Bdk5NeVPcj7VR7/aSSukxH4O1o8iWZ1bu/HxDYflTwBJrISjRiiQxt6K83Jxi4D+ZM2YvwYxvDwD2oHXtB6++sOKLnLfXTJ97YWbGiRNOi46JlQTdfpo6yUQD7CypKg+GdNDpaPuJTJHCHwz5l/uKN2et93299kDZs8CH2QW+Srvj6qhkKKONZM6YHQXMAM7H1MjuxYy/E5eQGDV97gUTho8/aVJMXFyijWF2Fp/My3BPbaiBJ8M9ALgD2AXwv3kTb+oS40pph9jCWmmNv3jxtoMbXlu7p+BQtT8byMku8MknijYmibmNZc6YnQbMBGZhqmD2An6AmLg417Rz5584cuIpk2PjE5JsDLOj2zYvwz2woQaeDHcapk59J8Dj54y7wt0ltsl17h3NjpLKnW9v3Lfh3U37NoQ0OcDH2QW+Irvj6iwkMbeTzBmzUzA96O9hhpD2YlawIyo6xnn6nPPHjjr5tClxCYmdvpfWBvxA7LwM9zGrBTwZbhfwBLAD4C+zTpiX0bXL6HaKLyxUB4KVy33FG19fv3fLuoNl64E3gBXZBT7ZLKKdSWJuZ5kzZicBp2Omo0djVjarAXC6XI6pPzhv9JhTJ0+J75KUbmOYHVGveRluX0MNPBnuhzGTmGpvnzJs5sl90ia1T2j20Vqzq7Rq+/tbDmx5a+O+nbXB0FeYJRY2StmbfSQx2yRzxuxETPXGDzATG/ZjtjhCORxqytlzTxg7aerUxOSUbjaG2ZGcPC/DvbShBp4M952YTRLKrps4MPOsoT3Oap/Q2l9FbaBsma9448L1vq2biip8wCLgi+wC3367YxNSlWGbvNyccuDtzBmzFwOTgHMxq9ft16FQ1cdvvLb64zcXrM6cPmvIyMxTx/Xs23+4w+mUKoHj1xczqakh+4GeQNmBipoOd4GrqKp2/5r9ZZs+3Hbg4LI9xYXaTOTKBdZJDXJ4kcRss7zcnEpgkVVidyowF+gOlKB1cV5uzqa83JxNyWldY0+e9f1RQ0aPG5ec3rW3rUFHpqaUzO0FMgH2lFVF/LTskNYhX1n1jpX7SrbkbN5/YMuhygpMWWAOsFSW3wxfkpjDRF5uThWQmzlj9qfAiZgqjkGYGYQHSooOVue89NxXOS8999WgkaO7jT/9jHH9hg0fExMr5XZN1NT1MpwA24ojcyeT2mCodntx5aa8PYd25GzeX1hU5a/FnNcSYDWwPbvAJ6sghjlJzGEmLzenBvgC+CJzxuyemOVQZ2J60bXAgS1rVx3YsnbVIofT+f7E6bOGjJx4yrgeffplyFBHg5q6LnMIwFdeXRkIhQIuhyPs/0YqagNlm4oqNizZUej7cNvBwtpgKARsBj4D1gH7ZKPTyBL2v3SdWV5uzl4gO3PG7LeAYcAUTKJ2AiWhYLB46fvvblz6/rsbk9O7xZ0y+6zRQ0aNHZeUlu62M+4w1aydTAAqaoOlybGOtLYL6fhU+YMV+yqqd289VOn7ZEdh0bI9xcXaLGP7NeZNfUN2gS/ih2I6M6nKiDBWNcdYTC96AOYP8iBWRQfAkNHjuo8+ZfIJvQYOHtolJdUt29cBsGtehrvB5OzJcKcAD2BNMnns7LGX906KG9AOsR1TIBQKHKys9e0urdq9obBid96eQ8WbiirqfqBVmFUbVwCbpN6445DEHKEyZ8xWmJ1UTsKsW52IqYcuxJpZCNC9d98uo0+dMrT/sOFD0929BrlcUW22SW6YCwIx8zLcxxxf9WS4nZhJJrsAfd/ME84d0a3L2PYKUGtNSU3goK+sevfW4ord+XtLDizbU1zjD+koTE9eY9YsX4mMF3dokpg7gMwZs12YoY5TMRsTxGD+iIuB8rp20bGxztGnTBkwZNSYod379BuYmJzS3ZaA7dNvXoZ7Z0MNPBnuBzFvcDW/mTxsxql906a0RSDBkA5V+APFRVX+gztKKnevPVC294tdRaVFVf5ozM9OYd5k1wIFmDcLn5S1dQ4yxtwB5OXmBDB/wGszZ8x+GrPl1QnAKdbXGqisra4+tGzxos3LFi/aDNDV3TtxZOYpA/sOyRjYvXefQbHxCck2nUJ76Ys1TNGAg5gdaWoKW7CTidaaSn+wrLQmcKi42l9cVFV7aF9FzaHdpVXFWw5VlmwtrgiFNF0w1ws05s1gI6YnvBPYlV3gK2/gKUQHJom5g7HWht5i3d7InDE7HdObPgkYifmZK6D0oG936cfZr60CVgH0HZqRNvzEzIHd+/TtndK1e8/EpOTuHazSoykXAPdhKjhK95Ufe5KJPxjy1wZD1ZX+YHlJjf9QUZW/+EBFzSFfeXXxtuLKQxsLyyurAqEozL6VMdbD6nrCXTBDEp9hqid2AwdlCrSoI0MZnYi1FGlfYAgwERhsfUtjSsXKscrFAFxR0Y6BI07o1nfIMHe3Xn16pnbr0bNLalpPV1RUzJHHjhC/mpfhvr+hBp4M9zmYST47eybGxE3t33VAaY2/urQmUF1c7a8uqqqtLqysrfGHtALiMIk3FrNyYN1r5wTKMDMJ92ASbyHW5glASXaBL9AWJyg6BknMnVjmjNmxmMqO4cBozP6LDkyvTmMSdTn1LiaiFH0HD03tN2yEu0ff/j3TuvfomZSa7o6QdaUfmZfhvqmhBp4M96nAzZjzrrvgBt/ekd2BeU32YWYL7sIk4brEWyy7eoiWkMQsDrP2LuyGWS+iL5CBmX1Y10N2YFZfK6deeR5Aes9eCYNGjnJ3dffpmpicnBTfJSkpLiExKTY+ISkmLq6Lw+FolZ5wawgAAAImSURBVB3ZW2jBPLO33zF5MtzJmNX/KjHlaNVH3Gqs+ytl0oZoK5KYRYOssrxUTLLuhUnWgzGrsNWNmdYccfv2WKlSdO3ZK7Gru3dSarduXZLS0pMSk1OTErokJcUlWsk7Ni7J6XK19TWPvHkZ7pPa+DmEaDFJzOK4WBNdelq3wZgp412BNEzPuu4XS1m3Wr6dvL9Tf5uc3i0uMTk5Jjom1hUVE+OKjo5xRcXEuFxRUS5XVLTLFR3tioqKcjmjol0uV5TL6XI5XVHmP06Xy+V0Ol1a61AwEAgE/P5AwO/3V5aXJqZ177l0yOhxXwGF8zLcb7X1ayNES0liFq3K6mHHA0n1bimYxN0dM1SSDtSfNAEmedf9W/d1qJGbrvevw7o5633twPT2387LzXmmLc5XiLYgiVm0Oyt5x/BN4k7AlPG5MInVhUncMdYt2vo3yvr6yFtdj/zIXnkNZlx4ZV5uzub2OTshWk4SsxBChJlwuFIuhBCiHknMQggRZiQxCyFEmJHELIQQYUYSsxBChBlJzEIIEWYkMQshRJiRxCyEEGFGErMQQoQZScxCCBFmJDELIUSYkcQshBBhRhKzEEKEGUnMQggRZiQxCyFEmJHELIQQYUYSsxBChBlJzEIIEWYkMQshRJiRxCyEEGFGErMQQoQZScxCCBFmJDELIUSYkcQshBBhRhKzEEKEGUnMQggRZiQxCyFEmJHELIQQYUYSsxBChJn/D+8qx+GZ69yYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate Type Percents\n",
    "type_df = main_df.groupby([\"type\"]) \n",
    "tot_fare_per_type = type_df[\"fare\"].sum()\n",
    "print(tot_fare_per_type[0])\n",
    "print(tot_fare_per_type)\n",
    "tot_fare_all_type = tot_fare_per_type.sum()\n",
    "print(tot_fare_all_type)\n",
    "\n",
    "\n",
    "# Build Pie Chart\n",
    "# Labels for the sections of our pie chart\n",
    "labels = [\"Rural\", \"Suburban\", \"Urban\"]\n",
    "\n",
    "# The values of each section of the pie chart\n",
    "sizes = [tot_fare_per_type[0], tot_fare_per_type[1], tot_fare_per_type[2]]\n",
    "\n",
    "# The colors of each section of the pie chart\n",
    "colors = [\"yellow\", \"lightblue\", \"coral\"]\n",
    "\n",
    "# Tells matplotlib to seperate the \"Python\" section from the others\n",
    "explode = (0, 0, 0.1)\n",
    "\n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors,\n",
    "        autopct=\"%1.1f%%\", shadow=True, startangle=140)\n",
    "\n",
    "plt.title(\"% Total Fares by City Type\")\n",
    "\n",
    "# Save Figure\n",
    "plt.savefig(\"City_Type_Fares.png\")\n",
    "\n",
    "# Show Figure\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Total Rides by City Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "125\n",
      "type\n",
      "Rural        125\n",
      "Suburban     625\n",
      "Urban       1625\n",
      "Name: city, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate Ride Percents\n",
    "type_df = main_df.groupby([\"type\"]) \n",
    "tot_rides_per_type = type_df[\"city\"].count()\n",
    "print(tot_rides_per_type[0])\n",
    "print(tot_rides_per_type)\n",
    "\n",
    "# Build Pie Chart\n",
    "\n",
    "# Labels for the sections of our pie chart\n",
    "labels = [\"Rural\", \"Suburban\", \"Urban\"]\n",
    "\n",
    "# The values of each section of the pie chart\n",
    "sizes = [tot_rides_per_type[0], tot_rides_per_type[1], tot_rides_per_type[2]]\n",
    "\n",
    "# The colors of each section of the pie chart\n",
    "colors = [\"yellow\", \"lightblue\", \"coral\"]\n",
    "\n",
    "# Tells matplotlib to seperate the \"Python\" section from the others\n",
    "explode = (0, 0, 0.1)\n",
    "\n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors,\n",
    "        autopct=\"%1.1f%%\", shadow=True, startangle=140)\n",
    "\n",
    "plt.title(\"% Total Rides by City Type\")\n",
    "\n",
    "# Save Figure\n",
    "plt.savefig(\"City_Type_Rides.png\")\n",
    "\n",
    "# Show Figure\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Total Drivers by City Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "537\n",
      "type\n",
      "Rural         537\n",
      "Suburban     8570\n",
      "Urban       59602\n",
      "Name: driver_count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate Driver Percents\n",
    "type_df = main_df.groupby([\"type\"]) \n",
    "tot_driver_per_type = type_df[\"driver_count\"].sum()\n",
    "print(tot_driver_per_type[0])\n",
    "print(tot_driver_per_type)\n",
    "\n",
    "# Build Pie Charts\n",
    "\n",
    "# Labels for the sections of our pie chart\n",
    "labels = [\"Rural\", \"Suburban\", \"Urban\"]\n",
    "\n",
    "# The values of each section of the pie chart\n",
    "sizes = [tot_driver_per_type[0], tot_driver_per_type[1], tot_driver_per_type[2]]\n",
    "\n",
    "# The colors of each section of the pie chart\n",
    "colors = [\"yellow\", \"lightblue\", \"coral\"]\n",
    "\n",
    "# Tells matplotlib to seperate the \"Python\" section from the others\n",
    "explode = (0, 0, 0.1)\n",
    "\n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors,\n",
    "        autopct=\"%1.1f%%\", shadow=True, startangle=140)\n",
    "\n",
    "plt.title(\"% Total Driver Count by City Type\")\n",
    "\n",
    "# Save Figure\n",
    "plt.savefig(\"City_Type_Driver_Ct.png\")\n",
    "\n",
    "# Show Figure\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1) There were far more riders and drivers in the Urban city type, but lower fares.\n",
    "# 2) There were nearly five times as many riders and drivers in the Suburban city type versus the Rural cuty type.\n",
    "# 3) Fares were higher in the Rural city types\n"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}