PyberAnalysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Oberserved analysis\n",
    "1. Looking at the scatterplot chart, you can see that urban cities have about eighty percent more drivers than rural cities.This is indicates that competition is high in urban cities, thus concluding that fare prices in urban cities are more than half the price of those in rural cities; indicating that urban cities have a higher population than suburban and rural cities. \n",
    "\n",
    "2. According to the pie charts, the percent of total fare by city, percent of total drivers by city, and the percent of total rides by city is higher than rural and suburban cities by over half. Therefore, indicating that the demand for uber drivers in urban cities is higher. One can quickly conclude that people would not rather drive themselves in a city environment.\n",
    "\n",
    "3. According to all three charts, rural cities use very little to none uber services. Knowing rural cities and it's geography, one can conclude that majority of it's population owns a car. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Dependencies\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# path to csv files\n",
    "pycity_file = \"raw_data/city_data.csv\"\n",
    "pyride_file = \"raw_data/ride_data.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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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",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-04-21 03:44:04</td>\n",
       "      <td>9.54</td>\n",
       "      <td>3698147103219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-02-03 00:14:26</td>\n",
       "      <td>29.04</td>\n",
       "      <td>4982665519010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-02-08 15:50:12</td>\n",
       "      <td>16.55</td>\n",
       "      <td>2270463070874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-04-03 15:07:34</td>\n",
       "      <td>40.77</td>\n",
       "      <td>9496210735824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-02-19 14:09:20</td>\n",
       "      <td>27.11</td>\n",
       "      <td>8690324801449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-04-22 03:06:56</td>\n",
       "      <td>39.74</td>\n",
       "      <td>4081388893008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-01-31 14:51:01</td>\n",
       "      <td>43.92</td>\n",
       "      <td>4066949857460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-03-04 22:13:57</td>\n",
       "      <td>14.83</td>\n",
       "      <td>9474112834050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-03-28 19:33:00</td>\n",
       "      <td>7.75</td>\n",
       "      <td>5539056178883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-02-14 03:27:28</td>\n",
       "      <td>44.11</td>\n",
       "      <td>2503858662225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-04-27 11:59:25</td>\n",
       "      <td>30.31</td>\n",
       "      <td>6106446829435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-03-03 11:57:24</td>\n",
       "      <td>11.42</td>\n",
       "      <td>2916078036620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-01-13 10:08:54</td>\n",
       "      <td>25.81</td>\n",
       "      <td>9110913538598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-03-06 12:53:05</td>\n",
       "      <td>8.28</td>\n",
       "      <td>5127600643309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-02-05 16:12:04</td>\n",
       "      <td>42.22</td>\n",
       "      <td>4051093040264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-04-04 15:04:56</td>\n",
       "      <td>16.35</td>\n",
       "      <td>6077906760851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-03-05 16:00:59</td>\n",
       "      <td>4.85</td>\n",
       "      <td>3291539624738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-04-14 11:56:28</td>\n",
       "      <td>43.01</td>\n",
       "      <td>7636011510547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-01-21 23:20:53</td>\n",
       "      <td>10.91</td>\n",
       "      <td>3567611375530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-03-16 23:00:51</td>\n",
       "      <td>21.39</td>\n",
       "      <td>237473464569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-03-22 04:41:04</td>\n",
       "      <td>16.35</td>\n",
       "      <td>5934239154720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-01-03 01:06:17</td>\n",
       "      <td>5.32</td>\n",
       "      <td>3268844473610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Richardfort</td>\n",
       "      <td>38</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-03-29 15:16:01</td>\n",
       "      <td>37.76</td>\n",
       "      <td>4802688422688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Williamsstad</td>\n",
       "      <td>59</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-01-23 17:51:24</td>\n",
       "      <td>19.62</td>\n",
       "      <td>125986195523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Williamsstad</td>\n",
       "      <td>59</td>\n",
       "      <td>Urban</td>\n",
       "      <td>2018-03-29 21:43:04</td>\n",
       "      <td>35.58</td>\n",
       "      <td>4747780858464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2345</th>\n",
       "      <td>Bradshawfurt</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-03-24 18:53:18</td>\n",
       "      <td>57.51</td>\n",
       "      <td>2301998876294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2346</th>\n",
       "      <td>Bradshawfurt</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-03-24 07:34:03</td>\n",
       "      <td>19.89</td>\n",
       "      <td>7867402022145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2347</th>\n",
       "      <td>Bradshawfurt</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-02-18 22:21:26</td>\n",
       "      <td>34.32</td>\n",
       "      <td>8881996813087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2348</th>\n",
       "      <td>Bradshawfurt</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-08 13:46:03</td>\n",
       "      <td>55.19</td>\n",
       "      <td>1742954306812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2349</th>\n",
       "      <td>Bradshawfurt</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-07 21:12:49</td>\n",
       "      <td>49.70</td>\n",
       "      <td>5088814323688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2350</th>\n",
       "      <td>Bradshawfurt</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-02-23 12:00:59</td>\n",
       "      <td>37.05</td>\n",
       "      <td>2068423024643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2351</th>\n",
       "      <td>Bradshawfurt</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-10 09:47:54</td>\n",
       "      <td>19.07</td>\n",
       "      <td>739305106253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2352</th>\n",
       "      <td>Bradshawfurt</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-01-19 20:21:54</td>\n",
       "      <td>56.78</td>\n",
       "      <td>1253403506597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2353</th>\n",
       "      <td>Bradshawfurt</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-01-30 10:55:23</td>\n",
       "      <td>51.39</td>\n",
       "      <td>1328274868072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2354</th>\n",
       "      <td>New Ryantown</td>\n",
       "      <td>2</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-01-27 17:33:41</td>\n",
       "      <td>42.68</td>\n",
       "      <td>7994603753131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2355</th>\n",
       "      <td>New Ryantown</td>\n",
       "      <td>2</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-18 19:43:54</td>\n",
       "      <td>42.97</td>\n",
       "      <td>230914178346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2356</th>\n",
       "      <td>New Ryantown</td>\n",
       "      <td>2</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-02-04 23:54:51</td>\n",
       "      <td>45.70</td>\n",
       "      <td>3570428225530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2357</th>\n",
       "      <td>New Ryantown</td>\n",
       "      <td>2</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-30 01:50:44</td>\n",
       "      <td>50.81</td>\n",
       "      <td>5357550405010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2358</th>\n",
       "      <td>New Ryantown</td>\n",
       "      <td>2</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-05 21:38:18</td>\n",
       "      <td>50.98</td>\n",
       "      <td>4834855490008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2359</th>\n",
       "      <td>New Ryantown</td>\n",
       "      <td>2</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-05-05 19:29:38</td>\n",
       "      <td>26.53</td>\n",
       "      <td>2302209966018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2360</th>\n",
       "      <td>Randallchester</td>\n",
       "      <td>9</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-13 11:13:31</td>\n",
       "      <td>43.22</td>\n",
       "      <td>1076079536213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2361</th>\n",
       "      <td>Randallchester</td>\n",
       "      <td>9</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-02-19 03:52:47</td>\n",
       "      <td>58.55</td>\n",
       "      <td>8004803682564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2362</th>\n",
       "      <td>Randallchester</td>\n",
       "      <td>9</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-02-11 05:42:29</td>\n",
       "      <td>25.78</td>\n",
       "      <td>9010611749008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2363</th>\n",
       "      <td>Randallchester</td>\n",
       "      <td>9</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-03-25 13:36:46</td>\n",
       "      <td>10.37</td>\n",
       "      <td>3216382725494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2364</th>\n",
       "      <td>Randallchester</td>\n",
       "      <td>9</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-07 23:42:07</td>\n",
       "      <td>10.79</td>\n",
       "      <td>1615474447641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2365</th>\n",
       "      <td>Jessicaport</td>\n",
       "      <td>1</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-01-01 09:45:36</td>\n",
       "      <td>43.69</td>\n",
       "      <td>2424875833354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2366</th>\n",
       "      <td>Jessicaport</td>\n",
       "      <td>1</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-01-14 07:09:17</td>\n",
       "      <td>18.05</td>\n",
       "      <td>5405362355006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2367</th>\n",
       "      <td>Jessicaport</td>\n",
       "      <td>1</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-13 16:08:11</td>\n",
       "      <td>39.89</td>\n",
       "      <td>6511242590852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2368</th>\n",
       "      <td>Jessicaport</td>\n",
       "      <td>1</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-03-18 16:59:40</td>\n",
       "      <td>33.72</td>\n",
       "      <td>3046889917159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2369</th>\n",
       "      <td>Jessicaport</td>\n",
       "      <td>1</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-05-01 08:14:47</td>\n",
       "      <td>22.44</td>\n",
       "      <td>3725278487786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2370</th>\n",
       "      <td>Jessicaport</td>\n",
       "      <td>1</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-01-31 17:57:25</td>\n",
       "      <td>58.29</td>\n",
       "      <td>623154556195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2371</th>\n",
       "      <td>South Saramouth</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-02-20 16:32:36</td>\n",
       "      <td>44.29</td>\n",
       "      <td>3622365199969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2372</th>\n",
       "      <td>South Saramouth</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-01-28 15:55:33</td>\n",
       "      <td>31.25</td>\n",
       "      <td>7118046558393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2373</th>\n",
       "      <td>South Saramouth</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-03-27 21:07:16</td>\n",
       "      <td>11.87</td>\n",
       "      <td>170351888128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2374</th>\n",
       "      <td>South Saramouth</td>\n",
       "      <td>7</td>\n",
       "      <td>Rural</td>\n",
       "      <td>2018-04-12 18:11:50</td>\n",
       "      <td>57.23</td>\n",
       "      <td>5081198789583</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2375 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 city  driver_count   type                 date   fare  \\\n",
       "0         Richardfort            38  Urban  2018-02-24 08:40:38  13.93   \n",
       "1         Richardfort            38  Urban  2018-02-13 12:46:07  14.00   \n",
       "2         Richardfort            38  Urban  2018-02-16 13:52:19  17.92   \n",
       "3         Richardfort            38  Urban  2018-02-01 20:18:28  10.26   \n",
       "4         Richardfort            38  Urban  2018-04-17 02:26:37  23.00   \n",
       "5         Richardfort            38  Urban  2018-04-21 03:44:04   9.54   \n",
       "6         Richardfort            38  Urban  2018-02-03 00:14:26  29.04   \n",
       "7         Richardfort            38  Urban  2018-02-08 15:50:12  16.55   \n",
       "8         Richardfort            38  Urban  2018-04-03 15:07:34  40.77   \n",
       "9         Richardfort            38  Urban  2018-02-19 14:09:20  27.11   \n",
       "10        Richardfort            38  Urban  2018-04-22 03:06:56  39.74   \n",
       "11        Richardfort            38  Urban  2018-01-31 14:51:01  43.92   \n",
       "12        Richardfort            38  Urban  2018-03-04 22:13:57  14.83   \n",
       "13        Richardfort            38  Urban  2018-03-28 19:33:00   7.75   \n",
       "14        Richardfort            38  Urban  2018-02-14 03:27:28  44.11   \n",
       "15        Richardfort            38  Urban  2018-04-27 11:59:25  30.31   \n",
       "16        Richardfort            38  Urban  2018-03-03 11:57:24  11.42   \n",
       "17        Richardfort            38  Urban  2018-01-13 10:08:54  25.81   \n",
       "18        Richardfort            38  Urban  2018-03-06 12:53:05   8.28   \n",
       "19        Richardfort            38  Urban  2018-02-05 16:12:04  42.22   \n",
       "20        Richardfort            38  Urban  2018-04-04 15:04:56  16.35   \n",
       "21        Richardfort            38  Urban  2018-03-05 16:00:59   4.85   \n",
       "22        Richardfort            38  Urban  2018-04-14 11:56:28  43.01   \n",
       "23        Richardfort            38  Urban  2018-01-21 23:20:53  10.91   \n",
       "24        Richardfort            38  Urban  2018-03-16 23:00:51  21.39   \n",
       "25        Richardfort            38  Urban  2018-03-22 04:41:04  16.35   \n",
       "26        Richardfort            38  Urban  2018-01-03 01:06:17   5.32   \n",
       "27        Richardfort            38  Urban  2018-03-29 15:16:01  37.76   \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",
       "...               ...           ...    ...                  ...    ...   \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",
       "2349     Bradshawfurt             7  Rural  2018-04-07 21:12:49  49.70   \n",
       "2350     Bradshawfurt             7  Rural  2018-02-23 12:00:59  37.05   \n",
       "2351     Bradshawfurt             7  Rural  2018-04-10 09:47:54  19.07   \n",
       "2352     Bradshawfurt             7  Rural  2018-01-19 20:21:54  56.78   \n",
       "2353     Bradshawfurt             7  Rural  2018-01-30 10:55:23  51.39   \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",
       "2359     New Ryantown             2  Rural  2018-05-05 19:29:38  26.53   \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",
       "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",
       "2370      Jessicaport             1  Rural  2018-01-31 17:57:25  58.29   \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",
       "0     5628545007794  \n",
       "1      910050116494  \n",
       "2      820639054416  \n",
       "3     9554935945413  \n",
       "4      720020655850  \n",
       "5     3698147103219  \n",
       "6     4982665519010  \n",
       "7     2270463070874  \n",
       "8     9496210735824  \n",
       "9     8690324801449  \n",
       "10    4081388893008  \n",
       "11    4066949857460  \n",
       "12    9474112834050  \n",
       "13    5539056178883  \n",
       "14    2503858662225  \n",
       "15    6106446829435  \n",
       "16    2916078036620  \n",
       "17    9110913538598  \n",
       "18    5127600643309  \n",
       "19    4051093040264  \n",
       "20    6077906760851  \n",
       "21    3291539624738  \n",
       "22    7636011510547  \n",
       "23    3567611375530  \n",
       "24     237473464569  \n",
       "25    5934239154720  \n",
       "26    3268844473610  \n",
       "27    4802688422688  \n",
       "28     125986195523  \n",
       "29    4747780858464  \n",
       "...             ...  \n",
       "2345  2301998876294  \n",
       "2346  7867402022145  \n",
       "2347  8881996813087  \n",
       "2348  1742954306812  \n",
       "2349  5088814323688  \n",
       "2350  2068423024643  \n",
       "2351   739305106253  \n",
       "2352  1253403506597  \n",
       "2353  1328274868072  \n",
       "2354  7994603753131  \n",
       "2355   230914178346  \n",
       "2356  3570428225530  \n",
       "2357  5357550405010  \n",
       "2358  4834855490008  \n",
       "2359  2302209966018  \n",
       "2360  1076079536213  \n",
       "2361  8004803682564  \n",
       "2362  9010611749008  \n",
       "2363  3216382725494  \n",
       "2364  1615474447641  \n",
       "2365  2424875833354  \n",
       "2366  5405362355006  \n",
       "2367  6511242590852  \n",
       "2368  3046889917159  \n",
       "2369  3725278487786  \n",
       "2370   623154556195  \n",
       "2371  3622365199969  \n",
       "2372  7118046558393  \n",
       "2373   170351888128  \n",
       "2374  5081198789583  \n",
       "\n",
       "[2375 rows x 6 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reading the files and creating dataframe\n",
    "pycity_df = pd.read_csv(pycity_file)\n",
    "pyride_df = pd.read_csv(pyride_file)\n",
    "\n",
    "# delete any duplicate cities\n",
    "# pycity_df = pycity_df.drop_duplicates('city')\n",
    "# cities = pycity_df['city']\n",
    "#testing\n",
    "# cities\n",
    "\n",
    "#merging the dataframes\n",
    "\n",
    "merged_df = pycity_df.merge(pyride_df)\n",
    "merged_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bubble plot per city"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating DataFrame for each city\n",
    "#Urban (total revenue, total number of rides, average fare, total number of drivers)\n",
    "urban = merged_df.loc[merged_df['type'] == 'Urban']\n",
    "urban_total_revenue = urban.groupby('city').sum()['fare']\n",
    "urban_total_number_of_rides = urban.groupby('city').count()['ride_id']\n",
    "urban_average_fare = round(urban_total_revenue/urban_total_number_of_rides,2)\n",
    "urban_total_drivers =urban.drop_duplicates('city').set_index('city')['driver_count']\n",
    "\n",
    "#suburban (total revenue, total number of rides, average fare, total number of drivers)\n",
    "suburban = merged_df.loc[merged_df['type'] == 'Suburban']\n",
    "suburban_total_revenue = suburban.groupby('city').sum()['fare']\n",
    "suburban_total_number_of_rides = suburban.groupby('city').count()['ride_id']\n",
    "suburban_average_fare = round(suburban_total_revenue/suburban_total_number_of_rides,2)\n",
    "suburban_total_drivers = suburban.drop_duplicates('city').set_index('city')['driver_count']\n",
    "\n",
    "#rural(total revenue, total number of rides, average fare, total number of drivers)\n",
    "rural = merged_df.loc[merged_df['type'] == 'Rural']\n",
    "rural_total_revenue = rural.groupby('city').sum()['fare']\n",
    "rural_total_number_of_rides = rural.groupby('city').count()['ride_id']\n",
    "rural_average_fare = round(rural_total_revenue/rural_total_number_of_rides, 2)\n",
    "rural_total_drivers = rural.drop_duplicates('city').set_index('city')['driver_count']\n",
    "\n",
    "#creating the the plot for urban,suburban and rural cities\n",
    "#urban\n",
    "plt.scatter(urban_total_number_of_rides, urban_average_fare, marker='o', \n",
    "            facecolors='lightcoral', edgecolors='black', \n",
    "            s=urban_total_drivers*10, alpha=0.75, label='Urban')\n",
    "#suburban\n",
    "plt.scatter(suburban_total_number_of_rides, suburban_average_fare, marker='o', \n",
    "            facecolors='lightblue', edgecolors='black', \n",
    "            s=suburban_total_drivers*10, alpha=0.75, label='Suburban')\n",
    "#rural\n",
    "plt.scatter(rural_total_number_of_rides, rural_average_fare, marker='o', \n",
    "            facecolors='yellow', edgecolors='black', \n",
    "            s=rural_total_drivers*10, alpha=0.75, label='Rural')\n",
    "#labels\n",
    "plt.title(\"Pyber Ride Sharing Data (2016)\")\n",
    "plt.xlabel(\"Total Number of Rides (Per City)\")\n",
    "plt.xlim(0,36)\n",
    "plt.ylabel(\"Average Fare ($)\")\n",
    "plt.ylim(15,51)\n",
    "lgnd = plt.legend(scatterpoints=1)\n",
    "lgnd.legendHandles[0]._sizes = [50]\n",
    "lgnd.legendHandles[1]._sizes = [50]\n",
    "lgnd.legendHandles[2]._sizes = [50]\n",
    "\n",
    "plt.annotate(s='Note:\\nCircle size correlates with driver count per city', xy=(0,15), xytext=(12,40))\n",
    "plt.grid()\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Total Revenue for all cities\n",
    "fare_total = merged_df['fare'].sum()\n",
    "\n",
    "#total fares by type of city\n",
    "fare_type = merged_df.groupby('type').sum()['fare']\n",
    "\n",
    "#percent of revenye by city type\n",
    "fare_percent = (fare_type/fare_total) \n",
    "\n",
    "#labels\n",
    "labels = fare_percent.index\n",
    "\n",
    "#size of slice, colors, explode\n",
    "sizes = fare_percent\n",
    "colors = ['yellow', 'lightblue', 'lightcoral']\n",
    "explode = (0, 0, 0.1)\n",
    "\n",
    "#pie chart\n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors,\n",
    "        autopct=\"%1.1f%%\", shadow=True, startangle=140)\n",
    "plt.title(\"% of Total Fares by City Type\")\n",
    "# plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Total Rides by City Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Number of rides by the city type\n",
    "ride_type = merged_df.groupby('type').count()['ride_id']\n",
    "# total number of rides\n",
    "total_rides = merged_df['fare'].count()\n",
    "#percent of rides\n",
    "ride_percent = round((ride_type/total_rides),2)\n",
    "#labels,sizes, colors, explode\n",
    "labels = ride_percent.index\n",
    "sizes = ride_percent\n",
    "explode = (0,0,0.2)\n",
    "colors = ['yellow', 'lightblue', 'lightcoral']\n",
    "\n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors,\n",
    "        autopct=\"%1.1f%%\", shadow=True, startangle=140)\n",
    "plt.title(\"% of Total Rides by City Type\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Total Drivers by City Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#drivers by city type\n",
    "city_ride_dup = merged_df.drop_duplicates(['city', 'driver_count'], keep = 'first')\n",
    "#total number of drivers\n",
    "total_drivers = city_ride_dup.groupby('type')['driver_count'].sum()\n",
    "plt.pie(total_drivers,explode=(0,0,0.1),colors = [\"gold\", \"lightblue\", \"lightcoral\"],\n",
    "        autopct=\"%1.1f%%\", labels=[\"Rural\",\"Suburban\",\"Urban\"])\n",
    "plt.axis(\"equal\")\n",
    "plt.title(\"% Total Drivers (city type)\")\n",
    "plt.show() \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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