mra1385/BikeshareRoutePatterns.ipynb

## BikeshareRoutePatterns.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# import modules\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as tkr\n",
    "import matplotlib.dates as mdates\n",
    "from math import radians, cos, sin, asin, sqrt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from datetime import datetime, timedelta\n",
    "import pprint\n",
    "import seaborn as sns\n",
    "import xml.etree.ElementTree as ET\n",
    "import urllib\n",
    "%matplotlib inline\n",
    "\n",
    "# use sns plot style\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# lists based on csv filenames will be used to load multiple csv files into pd dataframe\n",
    "# quarters = ['4th', '3rd', '2nd', '1st']\n",
    "# years = ['2014']\n",
    "\n",
    "quarters = ['2014-4th', '2014-3rd', '2015-2nd', '2015-1st']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# column names for pd dataframe \n",
    "headers = ['Duration', 'Minutes', 'Start Date', 'Starting Station', 'Start Terminal', \n",
    "           'End Date', 'End Station', 'End Terminal', 'Bike', 'Member Type']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# loading multiple csv files into python list\n",
    "tmp_lst = []\n",
    "# for year in years:\n",
    "for quarter in quarters:\n",
    "    path = 'c:/users/mra/desktop/admin/chart-it/Bikeshare/system data/{}-quarter.csv'.format(quarter) \n",
    "    frame = pd.read_csv(path, names = headers, header = 0, low_memory = False)        \n",
    "    tmp_lst.append(frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# use concat method to convert python list into pd dataframe\n",
    "bike_share = (pd.concat(tmp_lst, ignore_index = True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# convert 'Minutes' column data into float data type\n",
    "bike_share['Minutes'] = bike_share.Minutes.convert_objects(convert_numeric=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# fill zero minute rides float '0' \n",
    "bike_share['Minutes'] = bike_share['Minutes'].fillna(value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# convert minutes column into float64 datatype\n",
    "bike_share['Minutes'] = bike_share.Minutes.astype('float64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# convert 'Start Date' column data into datetime data type\n",
    "bike_share['Start Date'] = pd.to_datetime(bike_share['Start Date'], format='%m/%d/%Y %H:%M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# convert 'End Date' column data into datetime data type\n",
    "bike_share['End Date'] = pd.to_datetime(bike_share['End Date'], format='%m/%d/%Y %H:%M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# add column with the start / end routes together as a new 'route' column \n",
    "bike_share['Route'] = bike_share['Starting Station'] + \" to \" + bike_share['End Station'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# series with number of rides by route\n",
    "routes = bike_share.groupby('Route')['Member Type'].count()\n",
    "routes_R = bike_share[bike_share['Member Type'] == 'Registered'].groupby('Route')['Member Type'].count()\n",
    "routes_C = bike_share[bike_share['Member Type'] == 'Casual'].groupby('Route')['Member Type'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# sort series with number of rides by route\n",
    "routes.sort(ascending=False)\n",
    "routes_R.sort(ascending=False)\n",
    "routes_C.sort(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# resample ride data into monthly data\n",
    "routes_by_month_count = bike_share.set_index('Start Date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "routes_by_month_count = routes_by_month_count.groupby('Route')['Minutes'].resample('M', how='count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# unstack month axis to be horizontal axis\n",
    "routes_by_month_count = routes_by_month_count.unstack('Start Date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# add 'total' column to add up total annual rides from each route\n",
    "routes_by_month_count['Total'] = routes_by_month_count.sum(1)\n",
    "\n",
    "# add 'percent of total' column \n",
    "routes_by_month_count['Pct Total'] = routes_by_month_count.sum(1) / routes_by_month_count['Total'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# create dictionary of most popular routes by month\n",
    "most_popular_route_by_month = dict()\n",
    "\n",
    "# iterate through months and adding most popular routes to dict\n",
    "for i in range(0,12):\n",
    "    most_popular_route_by_month[i] = routes_by_month_count.sort(routes_by_month_count.columns[i], ascending=False).ix[0].name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: 'Jefferson Dr & 14th St SW to Lincoln Memorial',\n",
      " 1: 'Jefferson Dr & 14th St SW to Jefferson Dr & 14th St SW',\n",
      " 2: 'Jefferson Dr & 14th St SW to Lincoln Memorial',\n",
      " 3: 'Lincoln Memorial to Jefferson Memorial',\n",
      " 4: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 5: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 6: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 7: '8th & F St NE to Columbus Circle / Union Station',\n",
      " 8: 'Jefferson Dr & 14th St SW to Jefferson Dr & 14th St SW',\n",
      " 9: 'Lincoln Memorial to Jefferson Memorial',\n",
      " 10: 'Lincoln Memorial to Jefferson Memorial',\n",
      " 11: 'Jefferson Dr & 14th St SW to Jefferson Dr & 14th St SW'}\n"
     ]
    }
   ],
   "source": [
    "# pretty print dictionary of most popular routes by month\n",
    "# month '12' is total\n",
    "pprint.pprint(most_popular_route_by_month)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# new dataframe based on percent of total rides using specific routes\n",
    "routes_by_month_count_pct_total = routes_by_month_count.drop(['Total','Pct Total'], axis=1).apply(axis=0, func=lambda x: x/x.sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x4031a9e8>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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TH2dZyrX02Hp5/ujfefv4B/TZ+wHoG7Dz6rrjoIKHl2biq7u8Cn4nRJp4eGkmAzYHz36Y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1wy4reMTdjzHK3NLuS7T9fQt2wlBRmZXHLhkX5qpeiNujII6dLQWSkVqJR6XilVqpTarpT6Swf2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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x274777b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot of most popular routes as percent of total by month\n",
    "\n",
    "def func(x, pos):  \n",
    "   s = '{:.2f}%'.format(x * 100)\n",
    "   return s\n",
    "\n",
    "ax1 = routes_by_month_count_pct_total.ix[routes.head(5).index].T.plot(kind='line', stacked=False, grid=True, figsize=(8,5))\n",
    "ax1.set_xlabel('Month', fontsize='14')\n",
    "ax1.set_ylabel('Percent of Rides', fontsize='14')\n",
    "ax1.tick_params(\n",
    "    axis='both',\n",
    "    which='both',      \n",
    "    bottom='off',      \n",
    "    top='off',         \n",
    "    right='off',\n",
    "    left='off',\n",
    "    labelbottom='on',\n",
    "    labelsize=14)\n",
    "\n",
    "date_fmt = 'Jan'\n",
    "formatter = mdates.DateFormatter(date_fmt)\n",
    "ax1.xaxis.set_major_formatter(formatter)\n",
    "\n",
    "y_format = tkr.FuncFormatter(func)  \n",
    "ax1.yaxis.set_major_formatter(y_format)\n",
    "ax1.legend(bbox_to_anchor=(0.6, -0.6), loc=8, borderaxespad=0., fontsize='14')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# dataframe of number of rides by route by month for registered and casual users only\n",
    "# resample ride data into monthly data\n",
    "routes_by_month_count_R = bike_share[bike_share['Member Type'] == 'Registered'].set_index('Start Date').groupby('Route')['Minutes'].resample('M', how='count')\n",
    "routes_by_month_count_C = bike_share[bike_share['Member Type'] == 'Casual'].set_index('Start Date').groupby('Route')['Minutes'].resample('M', how='count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# unstack month axis to be horizontal axis\n",
    "routes_by_month_count_R = routes_by_month_count_R.unstack('Start Date')\n",
    "routes_by_month_count_C = routes_by_month_count_C.unstack('Start Date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# add 'total' column to add up total annual rides from each route\n",
    "routes_by_month_count_R['Total'] = routes_by_month_count_R.sum(1)\n",
    "routes_by_month_count_C['Total'] = routes_by_month_count_C.sum(1)\n",
    "\n",
    "# add 'percent of total' column \n",
    "routes_by_month_count_R['Pct Total'] = routes_by_month_count_R.sum(1) / routes_by_month_count_R['Total'].sum()\n",
    "routes_by_month_count_C['Pct Total'] = routes_by_month_count_C.sum(1) / routes_by_month_count_C['Total'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# create dictionary of most popular routes by month by registered users\n",
    "most_popular_route_by_month_R = dict()\n",
    "\n",
    "# iterate through months and adding most popular routes to dict by registered users\n",
    "for i in range(0,12):\n",
    "    most_popular_route_by_month_R[i] = routes_by_month_count_R.sort(routes_by_month_count_R.columns[i], ascending=False).ix[0].name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# create dictionary of most popular routes by month by casual users\n",
    "most_popular_route_by_month_C = dict()\n",
    "\n",
    "# iterate through months and adding most popular routes to dict by casual users\n",
    "for i in range(0,12):\n",
    "    most_popular_route_by_month_C[i] = routes_by_month_count_C.sort(routes_by_month_count_C.columns[i], ascending=False).ix[0].name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 1: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 2: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 3: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 4: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 5: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 6: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 7: '8th & F St NE to Columbus Circle / Union Station',\n",
      " 8: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 9: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 10: 'Columbus Circle / Union Station to 8th & F St NE',\n",
      " 11: 'Columbus Circle / Union Station to 8th & F St NE'}\n"
     ]
    }
   ],
   "source": [
    "# pretty print dictionary of most popular routes by month for registered users\n",
    "# month '12' is total\n",
    "pprint.pprint(most_popular_route_by_month_R)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: 'Lincoln Memorial to Jefferson Dr & 14th St SW',\n",
      " 1: 'Jefferson Dr & 14th St SW to Jefferson Dr & 14th St SW',\n",
      " 2: 'Jefferson Dr & 14th St SW to Lincoln Memorial',\n",
      " 3: 'Lincoln Memorial to Jefferson Memorial',\n",
      " 4: 'Lincoln Memorial to Jefferson Memorial',\n",
      " 5: 'Lincoln Memorial to Jefferson Dr & 14th St SW',\n",
      " 6: 'Jefferson Dr & 14th St SW to Jefferson Dr & 14th St SW',\n",
      " 7: 'Jefferson Dr & 14th St SW to Jefferson Dr & 14th St SW',\n",
      " 8: 'Jefferson Dr & 14th St SW to Jefferson Dr & 14th St SW',\n",
      " 9: 'Lincoln Memorial to Jefferson Memorial',\n",
      " 10: 'Lincoln Memorial to Jefferson Memorial',\n",
      " 11: 'Jefferson Dr & 14th St SW to Jefferson Dr & 14th St SW'}\n"
     ]
    }
   ],
   "source": [
    "# pretty print dictionary of most popular routes by month for casual users\n",
    "# month '12' is total\n",
    "pprint.pprint(most_popular_route_by_month_C)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Start Date</th>\n",
       "      <th>2014-07-31 00:00:00</th>\n",
       "      <th>2014-08-31 00:00:00</th>\n",
       "      <th>2014-09-30 00:00:00</th>\n",
       "      <th>2014-10-31 00:00:00</th>\n",
       "      <th>2014-11-30 00:00:00</th>\n",
       "      <th>2014-12-31 00:00:00</th>\n",
       "      <th>2015-01-31 00:00:00</th>\n",
       "      <th>2015-02-28 00:00:00</th>\n",
       "      <th>2015-03-31 00:00:00</th>\n",
       "      <th>2015-04-30 00:00:00</th>\n",
       "      <th>2015-05-31 00:00:00</th>\n",
       "      <th>2015-06-30 00:00:00</th>\n",
       "      <th>Total</th>\n",
       "      <th>Pct Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Route</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Jefferson Dr &amp; 14th St SW to Jefferson Dr &amp; 14th St SW</th>\n",
       "      <td>746</td>\n",
       "      <td>921</td>\n",
       "      <td>526</td>\n",
       "      <td>447</td>\n",
       "      <td>209</td>\n",
       "      <td>121</td>\n",
       "      <td>85</td>\n",
       "      <td>74</td>\n",
       "      <td>580</td>\n",
       "      <td>860</td>\n",
       "      <td>885</td>\n",
       "      <td>865</td>\n",
       "      <td>6319</td>\n",
       "      <td>0.019259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Memorial to Jefferson Memorial</th>\n",
       "      <td>723</td>\n",
       "      <td>796</td>\n",
       "      <td>554</td>\n",
       "      <td>566</td>\n",
       "      <td>288</td>\n",
       "      <td>149</td>\n",
       "      <td>67</td>\n",
       "      <td>45</td>\n",
       "      <td>404</td>\n",
       "      <td>900</td>\n",
       "      <td>1053</td>\n",
       "      <td>703</td>\n",
       "      <td>6248</td>\n",
       "      <td>0.019042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jefferson Dr &amp; 14th St SW to Lincoln Memorial</th>\n",
       "      <td>822</td>\n",
       "      <td>833</td>\n",
       "      <td>578</td>\n",
       "      <td>541</td>\n",
       "      <td>237</td>\n",
       "      <td>164</td>\n",
       "      <td>82</td>\n",
       "      <td>50</td>\n",
       "      <td>386</td>\n",
       "      <td>667</td>\n",
       "      <td>960</td>\n",
       "      <td>778</td>\n",
       "      <td>6098</td>\n",
       "      <td>0.018585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Memorial to Jefferson Dr &amp; 14th St SW</th>\n",
       "      <td>824</td>\n",
       "      <td>855</td>\n",
       "      <td>565</td>\n",
       "      <td>452</td>\n",
       "      <td>274</td>\n",
       "      <td>219</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>358</td>\n",
       "      <td>643</td>\n",
       "      <td>860</td>\n",
       "      <td>801</td>\n",
       "      <td>5998</td>\n",
       "      <td>0.018280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Smithsonian / Jefferson Dr &amp; 12th St SW to Smithsonian / Jefferson Dr &amp; 12th St SW</th>\n",
       "      <td>760</td>\n",
       "      <td>748</td>\n",
       "      <td>493</td>\n",
       "      <td>360</td>\n",
       "      <td>155</td>\n",
       "      <td>112</td>\n",
       "      <td>74</td>\n",
       "      <td>54</td>\n",
       "      <td>412</td>\n",
       "      <td>656</td>\n",
       "      <td>552</td>\n",
       "      <td>471</td>\n",
       "      <td>4847</td>\n",
       "      <td>0.014772</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Start Date                                          2014-07-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  746   \n",
       "Lincoln Memorial to Jefferson Memorial                              723   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       822   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       824   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  760   \n",
       "\n",
       "Start Date                                          2014-08-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  921   \n",
       "Lincoln Memorial to Jefferson Memorial                              796   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       833   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       855   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  748   \n",
       "\n",
       "Start Date                                          2014-09-30 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  526   \n",
       "Lincoln Memorial to Jefferson Memorial                              554   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       578   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       565   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  493   \n",
       "\n",
       "Start Date                                          2014-10-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  447   \n",
       "Lincoln Memorial to Jefferson Memorial                              566   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       541   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       452   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  360   \n",
       "\n",
       "Start Date                                          2014-11-30 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  209   \n",
       "Lincoln Memorial to Jefferson Memorial                              288   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       237   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       274   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  155   \n",
       "\n",
       "Start Date                                          2014-12-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  121   \n",
       "Lincoln Memorial to Jefferson Memorial                              149   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       164   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       219   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  112   \n",
       "\n",
       "Start Date                                          2015-01-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                   85   \n",
       "Lincoln Memorial to Jefferson Memorial                               67   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                        82   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                        80   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                   74   \n",
       "\n",
       "Start Date                                          2015-02-28 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                   74   \n",
       "Lincoln Memorial to Jefferson Memorial                               45   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                        50   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                        67   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                   54   \n",
       "\n",
       "Start Date                                          2015-03-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  580   \n",
       "Lincoln Memorial to Jefferson Memorial                              404   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       386   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       358   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  412   \n",
       "\n",
       "Start Date                                          2015-04-30 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  860   \n",
       "Lincoln Memorial to Jefferson Memorial                              900   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       667   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       643   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  656   \n",
       "\n",
       "Start Date                                          2015-05-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  885   \n",
       "Lincoln Memorial to Jefferson Memorial                             1053   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       960   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       860   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  552   \n",
       "\n",
       "Start Date                                          2015-06-30 00:00:00  \\\n",
       "Route                                                                     \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...                  865   \n",
       "Lincoln Memorial to Jefferson Memorial                              703   \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial                       778   \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW                       801   \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...                  471   \n",
       "\n",
       "Start Date                                          Total  Pct Total  \n",
       "Route                                                                 \n",
       "Jefferson Dr & 14th St SW to Jefferson Dr & 14t...   6319   0.019259  \n",
       "Lincoln Memorial to Jefferson Memorial               6248   0.019042  \n",
       "Jefferson Dr & 14th St SW to Lincoln Memorial        6098   0.018585  \n",
       "Lincoln Memorial to Jefferson Dr & 14th St SW        5998   0.018280  \n",
       "Smithsonian / Jefferson Dr & 12th St SW to Smit...   4847   0.014772  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# top five most popular casual rider routes\n",
    "routes_by_month_count_C.sort('Total', ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Start Date</th>\n",
       "      <th>2014-07-31 00:00:00</th>\n",
       "      <th>2014-08-31 00:00:00</th>\n",
       "      <th>2014-09-30 00:00:00</th>\n",
       "      <th>2014-10-31 00:00:00</th>\n",
       "      <th>2014-11-30 00:00:00</th>\n",
       "      <th>2014-12-31 00:00:00</th>\n",
       "      <th>2015-01-31 00:00:00</th>\n",
       "      <th>2015-02-28 00:00:00</th>\n",
       "      <th>2015-03-31 00:00:00</th>\n",
       "      <th>2015-04-30 00:00:00</th>\n",
       "      <th>2015-05-31 00:00:00</th>\n",
       "      <th>2015-06-30 00:00:00</th>\n",
       "      <th>Total</th>\n",
       "      <th>Pct Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Route</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Columbus Circle / Union Station to 8th &amp; F St NE</th>\n",
       "      <td>436</td>\n",
       "      <td>409</td>\n",
       "      <td>459</td>\n",
       "      <td>517</td>\n",
       "      <td>422</td>\n",
       "      <td>365</td>\n",
       "      <td>345</td>\n",
       "      <td>281</td>\n",
       "      <td>434</td>\n",
       "      <td>451</td>\n",
       "      <td>497</td>\n",
       "      <td>557</td>\n",
       "      <td>5173</td>\n",
       "      <td>0.004290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8th &amp; F St NE to Columbus Circle / Union Station</th>\n",
       "      <td>307</td>\n",
       "      <td>354</td>\n",
       "      <td>441</td>\n",
       "      <td>450</td>\n",
       "      <td>393</td>\n",
       "      <td>360</td>\n",
       "      <td>325</td>\n",
       "      <td>313</td>\n",
       "      <td>410</td>\n",
       "      <td>391</td>\n",
       "      <td>449</td>\n",
       "      <td>450</td>\n",
       "      <td>4643</td>\n",
       "      <td>0.003851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Park / 13th &amp; East Capitol St NE  to Eastern Market Metro / Pennsylvania Ave &amp; 7th St SE</th>\n",
       "      <td>363</td>\n",
       "      <td>322</td>\n",
       "      <td>366</td>\n",
       "      <td>347</td>\n",
       "      <td>258</td>\n",
       "      <td>219</td>\n",
       "      <td>214</td>\n",
       "      <td>219</td>\n",
       "      <td>243</td>\n",
       "      <td>299</td>\n",
       "      <td>343</td>\n",
       "      <td>329</td>\n",
       "      <td>3522</td>\n",
       "      <td>0.002921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eastern Market Metro / Pennsylvania Ave &amp; 7th St SE to Lincoln Park / 13th &amp; East Capitol St NE</th>\n",
       "      <td>368</td>\n",
       "      <td>327</td>\n",
       "      <td>349</td>\n",
       "      <td>343</td>\n",
       "      <td>267</td>\n",
       "      <td>208</td>\n",
       "      <td>202</td>\n",
       "      <td>185</td>\n",
       "      <td>219</td>\n",
       "      <td>285</td>\n",
       "      <td>312</td>\n",
       "      <td>301</td>\n",
       "      <td>3366</td>\n",
       "      <td>0.002791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire Ave &amp; T St NW to Massachusetts Ave &amp; Dupont Circle NW</th>\n",
       "      <td>306</td>\n",
       "      <td>320</td>\n",
       "      <td>341</td>\n",
       "      <td>345</td>\n",
       "      <td>277</td>\n",
       "      <td>227</td>\n",
       "      <td>221</td>\n",
       "      <td>174</td>\n",
       "      <td>235</td>\n",
       "      <td>294</td>\n",
       "      <td>302</td>\n",
       "      <td>284</td>\n",
       "      <td>3326</td>\n",
       "      <td>0.002758</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Start Date                                          2014-07-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    436   \n",
       "8th & F St NE to Columbus Circle / Union Station                    307   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  363   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  368   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  306   \n",
       "\n",
       "Start Date                                          2014-08-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    409   \n",
       "8th & F St NE to Columbus Circle / Union Station                    354   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  322   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  327   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  320   \n",
       "\n",
       "Start Date                                          2014-09-30 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    459   \n",
       "8th & F St NE to Columbus Circle / Union Station                    441   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  366   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  349   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  341   \n",
       "\n",
       "Start Date                                          2014-10-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    517   \n",
       "8th & F St NE to Columbus Circle / Union Station                    450   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  347   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  343   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  345   \n",
       "\n",
       "Start Date                                          2014-11-30 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    422   \n",
       "8th & F St NE to Columbus Circle / Union Station                    393   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  258   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  267   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  277   \n",
       "\n",
       "Start Date                                          2014-12-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    365   \n",
       "8th & F St NE to Columbus Circle / Union Station                    360   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  219   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  208   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  227   \n",
       "\n",
       "Start Date                                          2015-01-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    345   \n",
       "8th & F St NE to Columbus Circle / Union Station                    325   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  214   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  202   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  221   \n",
       "\n",
       "Start Date                                          2015-02-28 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    281   \n",
       "8th & F St NE to Columbus Circle / Union Station                    313   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  219   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  185   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  174   \n",
       "\n",
       "Start Date                                          2015-03-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    434   \n",
       "8th & F St NE to Columbus Circle / Union Station                    410   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  243   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  219   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  235   \n",
       "\n",
       "Start Date                                          2015-04-30 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    451   \n",
       "8th & F St NE to Columbus Circle / Union Station                    391   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  299   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  285   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  294   \n",
       "\n",
       "Start Date                                          2015-05-31 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    497   \n",
       "8th & F St NE to Columbus Circle / Union Station                    449   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  343   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  312   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  302   \n",
       "\n",
       "Start Date                                          2015-06-30 00:00:00  \\\n",
       "Route                                                                     \n",
       "Columbus Circle / Union Station to 8th & F St NE                    557   \n",
       "8th & F St NE to Columbus Circle / Union Station                    450   \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...                  329   \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...                  301   \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...                  284   \n",
       "\n",
       "Start Date                                          Total  Pct Total  \n",
       "Route                                                                 \n",
       "Columbus Circle / Union Station to 8th & F St NE     5173   0.004290  \n",
       "8th & F St NE to Columbus Circle / Union Station     4643   0.003851  \n",
       "Lincoln Park / 13th & East Capitol St NE  to Ea...   3522   0.002921  \n",
       "Eastern Market Metro / Pennsylvania Ave & 7th S...   3366   0.002791  \n",
       "New Hampshire Ave & T St NW to Massachusetts Av...   3326   0.002758  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# top five most popular registerd rider routes\n",
    "routes_by_month_count_R.sort('Total', ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# new dataframe based on percent of total rides using specific routes\n",
    "routes_by_month_count_pct_total_R = routes_by_month_count_R.drop(['Total','Pct Total'], axis=1).apply(axis=0, func=lambda x: x/x.sum())\n",
    "routes_by_month_count_pct_total_C = routes_by_month_count_C.drop(['Total','Pct Total'], axis=1).apply(axis=0, func=lambda x: x/x.sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# new dataframe based on most popular route by month\n",
    "lst_popular_routes_R = routes_by_month_count_pct_total_R[routes_by_month_count_pct_total_R == routes_by_month_count_pct_total_R.max()].dropna(how='all').index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "lst_popular_routes_C = routes_by_month_count_pct_total_C[routes_by_month_count_pct_total_C == routes_by_month_count_pct_total_C.max()].dropna(how='all').index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1508d9b0>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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RX1pDXKT89yGE6FyHAVQp9RpgAK3rgXU4xVFrfUsX1yWEcLNte0t448u91Da0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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x274410f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot of most popular routes as percent of total by month for registered users\n",
    "\n",
    "def func(x, pos):  \n",
    "   s = '{:.2f}%'.format(x * 100)\n",
    "   return s\n",
    "\n",
    "ax1 = routes_by_month_count_pct_total_R.ix[routes_R.head(5).index].T.plot(kind='line', stacked=False, grid=True, figsize=(8,5))\n",
    "ax1.set_xlabel('Month', fontsize='14')\n",
    "ax1.set_ylabel('Percent of Rides', fontsize='14')\n",
    "ax1.tick_params(\n",
    "    axis='both',\n",
    "    which='both',      \n",
    "    bottom='off',      \n",
    "    top='off',         \n",
    "    right='off',\n",
    "    left='off',\n",
    "    labelbottom='on',\n",
    "    labelsize=14)\n",
    "\n",
    "date_fmt = 'Jan'\n",
    "formatter = mdates.DateFormatter(date_fmt)\n",
    "ax1.xaxis.set_major_formatter(formatter)\n",
    "\n",
    "y_format = tkr.FuncFormatter(func)  \n",
    "ax1.yaxis.set_major_formatter(y_format)\n",
    "ax1.legend(bbox_to_anchor=(0.6, -0.6), loc=8, borderaxespad=0., fontsize='14')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0xf6f1f28>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jfwBzEDPzv4LZ4ttVNwqy4ymr6+JwZTuLfVC7UXi8tb+Wzh4716+aRfQUXUll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\n2f4x4drtnyzGBxEK+21E3OA/unD9zVK5b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/uUdK4ZOclkMpnPhWzJm7E4lhhIi5+bicGo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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14d15cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot of most popular routes as percent of total by month for casual users\n",
    "def func(x, pos):  \n",
    "   s = '{:.2f}%'.format(x * 100)\n",
    "   return s\n",
    "\n",
    "ax1 = routes_by_month_count_pct_total_C.ix[routes_C.head(5).index].T.plot(kind='line', stacked=False, grid=True, figsize=(8,5))\n",
    "ax1.set_xlabel('Month', fontsize='14')\n",
    "ax1.set_ylabel('Percent of Rides', fontsize='14')\n",
    "ax1.tick_params(\n",
    "    axis='both',\n",
    "    which='both',      \n",
    "    bottom='off',      \n",
    "    top='off',         \n",
    "    right='off',\n",
    "    left='off',\n",
    "    labelbottom='on',\n",
    "    labelsize=14)\n",
    "\n",
    "date_fmt = 'Jan'\n",
    "formatter = mdates.DateFormatter(date_fmt)\n",
    "ax1.xaxis.set_major_formatter(formatter)\n",
    "\n",
    "y_format = tkr.FuncFormatter(func)  \n",
    "ax1.yaxis.set_major_formatter(y_format)\n",
    "ax1.legend(bbox_to_anchor=(0.6, -0.6), loc=8, borderaxespad=0., fontsize='14')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# capital bikeshare does not provide station size information with the system data file\n",
    "# station size information is provided in a separate 'station status' xml feed \n",
    "# next few steps load and parse this feed to create a data frame with station sizes to merge into\n",
    "# the broader bike_share dataframe\n",
    "\n",
    "# path of the xml feed\n",
    "xml_path = 'https://www.capitalbikeshare.com/data/stations/bikeStations.xml'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# load xml file\n",
    "tree = ET.parse(urllib.request.urlopen(xml_path))\n",
    "root = tree.getroot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# parse xml file and add station / location data to a dict\n",
    "station_location = dict()\n",
    "\n",
    "for child in root:\n",
    "    tmp_lst = [child[4].text,  child[5].text]\n",
    "    station_location[child[1].text] = tmp_lst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# create dataframe with station location\n",
    "names_station_location = ['Starting Station', 'Geolocation']\n",
    "station_location_df = pd.DataFrame(list(station_location.items()), columns = names_station_location)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "station_location_df['Latitude'] = station_location_df['Geolocation'].apply(lambda x: pd.Series(x[0]))\n",
    "station_location_df['Longitude'] = station_location_df['Geolocation'].apply(lambda x: pd.Series(x[1]))\n",
    "del station_location_df['Geolocation']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "station_location_df['End Station'] = station_location_df['Starting Station']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share = bike_share.merge(station_location_df, on='End Station')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "del bike_share['Starting Station_y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share.rename(columns={'Starting Station_x':'Starting Station', 'Latitude' : 'Lat (End)', 'Longitude' : 'Long (End)'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share = bike_share.merge(station_location_df, on='Starting Station')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "del bike_share['End Station_y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share.rename(columns={'End Station_x':'End Station', 'Latitude' : 'Lat (Start)', 'Longitude' : 'Long (Start)'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share[['Lat (End)', 'Long (End)', 'Lat (Start)', 'Long (Start)']].to_csv('c:/users/mra/desktop/admin/chart-it/Bikeshare/pt 3/cartoDB.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def distance(lon1, lat1, lon2, lat2):\n",
    "    \"\"\"\n",
    "    Calculate the great circle distance between two points \n",
    "    on the earth (specified in decimal degrees)\n",
    "    \"\"\"\n",
    "    # convert decimal degrees to radians \n",
    "    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])\n",
    "    # haversine formula \n",
    "    dlon = lon2 - lon1 \n",
    "    dlat = lat2 - lat1 \n",
    "    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2\n",
    "    c = 2 * asin(sqrt(a)) \n",
    "    km = 6367 * c\n",
    "    return km * 0.621371"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share['Lat (Start)'] = bike_share['Lat (Start)'].astype(float)\n",
    "bike_share['Lat (End)'] = bike_share['Lat (End)'].astype(float)\n",
    "bike_share['Long (Start)'] = bike_share['Long (Start)'].astype(float)\n",
    "bike_share['Long (End)'] = bike_share['Long (End)'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share['Distance by Lat/Long'] =  bike_share.apply(lambda x: distance(x['Long (Start)'], x['Lat (Start)'], x['Long (End)'],\\\n",
    "                                                                          x['Lat (End)']), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share['Distance by Ride Duration']= ( bike_share['Minutes'] / 60 ) * 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.FancyArrow at 0xb900ef0>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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rXf4wNzeXL7/8knnz5hEREcGAAQPIysoCrtS8V/fd5s2bk5eXx4kTJ0zbfv75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\nAZteihsuxddIAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e684208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"whitegrid\")\n",
    "plt.figure(figsize=(12,8))\n",
    "ax1 = sns.distplot(bike_share[bike_share['Distance by Lat/Long'] < 8]['Distance by Lat/Long'],bins=(30), \\\n",
    "             label= \"By Station Distance\", norm_hist=True, kde=False)\n",
    "\n",
    "ax1.set(xlim=(0, 8))\n",
    "\n",
    "sns.distplot(bike_share[bike_share['Distance by Ride Duration'] < 8]['Distance by Ride Duration'], bins=(30), \\\n",
    "             label= \"By Ride Duration\", norm_hist=True, kde=False).set(xlim=(0, 8))\n",
    "\n",
    "sns.axlabel('Distance (miles)', 'Percent of Rides', fontsize=14)\n",
    "plt.legend(frameon=False, fontsize=14, loc=9)\n",
    "plt.xticks(fontsize = 14)\n",
    "plt.yticks(fontsize = 14)\n",
    "plt.xticks(np.arange(0,8,0.5))\n",
    "ax1.grid(False)\n",
    "ax1.spines[\"top\"].set_visible(False)  \n",
    "ax1.spines[\"right\"].set_visible(False) \n",
    "ax1.spines[\"left\"].set_visible(False) \n",
    "\n",
    "\n",
    "def func(x, pos):  \n",
    "   s = '{:.0f}%'.format(x * 100)\n",
    "   return s\n",
    "\n",
    "y_format = tkr.FuncFormatter(func)\n",
    "ax1.yaxis.set_major_formatter(y_format)\n",
    "\n",
    "# arrows and annotation\n",
    "ax1.text(x=bike_share['Distance by Lat/Long'].quantile(0.50) - 0.1,y=0.73,\\\n",
    "         s='Median: {:,.1f} miles'.format(bike_share['Distance by Lat/Long'].quantile(0.50)), color='blue',\\\n",
    "         alpha=0.5, backgroundcolor='white', size=14, weight='bold')\n",
    "ax1.arrow(bike_share['Distance by Lat/Long'].quantile(0.50), 0.73, 0,-0.075, head_width=0.07, head_length=0.015,\\\n",
    "          color='blue', alpha=0.5)\n",
    "\n",
    "ax1.text(x=bike_share['Distance by Ride Duration'].quantile(0.50) - 0.1,y=0.38,\\\n",
    "         s='Median: {:,.1f} miles'.format(bike_share['Distance by Ride Duration'].quantile(0.50)), color='green',\\\n",
    "         alpha=0.5, backgroundcolor='white', size=14, weight='bold')\n",
    "ax1.arrow(bike_share['Distance by Ride Duration'].quantile(0.50), 0.37, 0,-0.035, head_width=0.07, head_length=0.015, \\\n",
    "          color='green', alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3003890.000000\n",
       "mean           2.895354\n",
       "std            9.810808\n",
       "min            0.000000\n",
       "25%            1.069225\n",
       "50%            1.821667\n",
       "75%            3.100285\n",
       "max        13834.926163\n",
       "Name: Distance by Ride Duration, dtype: float64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# summary statistics of distance by ride duration\n",
    "bike_share['Distance by Ride Duration'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3003890.000000\n",
       "mean           1.106070\n",
       "std            0.791678\n",
       "min            0.000000\n",
       "25%            0.566500\n",
       "50%            0.928157\n",
       "75%            1.461276\n",
       "max           16.293834\n",
       "Name: Distance by Lat/Long, dtype: float64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# summary statistics of distance by lat/long\n",
    "bike_share['Distance by Lat/Long'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# calculate implied average speed using distance traveled by latitude and longitude\n",
    "bike_share['Average Speed'] = bike_share['Distance by Lat/Long'] / (bike_share['Minutes'] / 60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3003710.000000\n",
       "mean           5.578164\n",
       "std            2.521842\n",
       "min            0.000000\n",
       "25%            4.161289\n",
       "50%            5.884933\n",
       "75%            7.275870\n",
       "max          117.326716\n",
       "Name: Average Speed, dtype: float64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# summary statistics for average speed\n",
    "bike_share['Average Speed'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# groupby object for map\n",
    "map_df = bike_share.groupby('Starting Station').agg({'Minutes':'median', 'Distance by Lat/Long': 'median', \\\n",
    "                                            'Distance by Ride Duration' : 'median', 'Average Speed' :\\\n",
    "                                            'median', 'Lat (Start)': 'median', 'Long (Start)' : 'median'\\\n",
    "                                            })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_busy = pd.read_pickle('c:/users/mra/desktop/admin/chart-it/Bikeshare/pt 3/busy.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# add 'busy-ness' ratio\n",
    "map_df = map_df.join(df_busy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "map_df.to_csv('c:/users/mra/desktop/admin/chart-it/Bikeshare/pt 3/busy.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Long (Start)</th>\n",
       "      <th>Average Speed</th>\n",
       "      <th>Distance by Lat/Long</th>\n",
       "      <th>Distance by Ride Duration</th>\n",
       "      <th>Lat (Start)</th>\n",
       "      <th>Minutes</th>\n",
       "      <th>Busiest</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Starting Station</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Prince St &amp; Union St</th>\n",
       "      <td>-77.040363</td>\n",
       "      <td>3.256164</td>\n",
       "      <td>0.698327</td>\n",
       "      <td>6.121644</td>\n",
       "      <td>38.803124</td>\n",
       "      <td>36.729867</td>\n",
       "      <td>1.098771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47th &amp; Elm St</th>\n",
       "      <td>-77.091991</td>\n",
       "      <td>5.980837</td>\n",
       "      <td>1.518164</td>\n",
       "      <td>4.595000</td>\n",
       "      <td>38.982456</td>\n",
       "      <td>27.570000</td>\n",
       "      <td>0.413278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S George Mason Dr &amp; 13th St S</th>\n",
       "      <td>-77.100555</td>\n",
       "      <td>3.352359</td>\n",
       "      <td>0.761952</td>\n",
       "      <td>4.504944</td>\n",
       "      <td>38.854691</td>\n",
       "      <td>27.029667</td>\n",
       "      <td>0.064692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>River Rd &amp; Landy Ln</th>\n",
       "      <td>-77.103381</td>\n",
       "      <td>6.784992</td>\n",
       "      <td>1.761135</td>\n",
       "      <td>4.266744</td>\n",
       "      <td>38.964992</td>\n",
       "      <td>25.600467</td>\n",
       "      <td>0.510494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Memorial</th>\n",
       "      <td>-77.049426</td>\n",
       "      <td>2.511495</td>\n",
       "      <td>1.120962</td>\n",
       "      <td>4.254851</td>\n",
       "      <td>38.888251</td>\n",
       "      <td>25.529108</td>\n",
       "      <td>16.844947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Smithsonian / Jefferson Dr &amp; 12th St SW</th>\n",
       "      <td>-77.028580</td>\n",
       "      <td>2.112316</td>\n",
       "      <td>0.824447</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>38.888767</td>\n",
       "      <td>25.500000</td>\n",
       "      <td>8.907653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Randle Circle &amp; Minnesota Ave SE</th>\n",
       "      <td>-76.960700</td>\n",
       "      <td>4.564116</td>\n",
       "      <td>1.383689</td>\n",
       "      <td>4.125597</td>\n",
       "      <td>38.878000</td>\n",
       "      <td>24.753583</td>\n",
       "      <td>0.026617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fallsgrove Dr &amp; W Montgomery Ave</th>\n",
       "      <td>-77.188014</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.123264</td>\n",
       "      <td>39.099376</td>\n",
       "      <td>24.739583</td>\n",
       "      <td>0.052032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio Dr &amp; West Basin Dr SW / MLK &amp; FDR Memorials</th>\n",
       "      <td>-77.046570</td>\n",
       "      <td>2.138904</td>\n",
       "      <td>0.819373</td>\n",
       "      <td>4.121667</td>\n",
       "      <td>38.884120</td>\n",
       "      <td>24.730000</td>\n",
       "      <td>4.213056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jefferson Dr &amp; 14th St SW</th>\n",
       "      <td>-77.032429</td>\n",
       "      <td>2.402684</td>\n",
       "      <td>0.821984</td>\n",
       "      <td>3.833333</td>\n",
       "      <td>38.888553</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>13.347899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jefferson Memorial</th>\n",
       "      <td>-77.037413</td>\n",
       "      <td>3.174741</td>\n",
       "      <td>1.119273</td>\n",
       "      <td>3.810225</td>\n",
       "      <td>38.879819</td>\n",
       "      <td>22.861350</td>\n",
       "      <td>7.807070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34th &amp; Water St NW</th>\n",
       "      <td>-77.067786</td>\n",
       "      <td>4.147182</td>\n",
       "      <td>1.289664</td>\n",
       "      <td>3.767317</td>\n",
       "      <td>38.903582</td>\n",
       "      <td>22.603900</td>\n",
       "      <td>3.208482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shady Grove Hospital</th>\n",
       "      <td>-77.196636</td>\n",
       "      <td>4.559129</td>\n",
       "      <td>0.231261</td>\n",
       "      <td>3.733333</td>\n",
       "      <td>39.097636</td>\n",
       "      <td>22.400000</td>\n",
       "      <td>0.007632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S Four Mile Run Dr &amp; S Shirlington Rd</th>\n",
       "      <td>-77.085931</td>\n",
       "      <td>5.173468</td>\n",
       "      <td>1.871691</td>\n",
       "      <td>3.728461</td>\n",
       "      <td>38.844400</td>\n",
       "      <td>22.370767</td>\n",
       "      <td>0.390897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S Arlington Mill Dr &amp; Campbell Ave</th>\n",
       "      <td>-77.089555</td>\n",
       "      <td>5.169456</td>\n",
       "      <td>1.077868</td>\n",
       "      <td>3.671667</td>\n",
       "      <td>38.842320</td>\n",
       "      <td>22.030000</td>\n",
       "      <td>0.834542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Traville Gateway Dr &amp; Gudelsky Dr</th>\n",
       "      <td>-77.202501</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.577047</td>\n",
       "      <td>39.093783</td>\n",
       "      <td>21.462283</td>\n",
       "      <td>0.036986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania &amp; Minnesota Ave SE</th>\n",
       "      <td>-76.971015</td>\n",
       "      <td>6.535476</td>\n",
       "      <td>2.459086</td>\n",
       "      <td>3.564167</td>\n",
       "      <td>38.873057</td>\n",
       "      <td>21.385000</td>\n",
       "      <td>0.371132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21st St &amp; Constitution Ave NW</th>\n",
       "      <td>-77.046567</td>\n",
       "      <td>3.159242</td>\n",
       "      <td>1.001917</td>\n",
       "      <td>3.511899</td>\n",
       "      <td>38.892459</td>\n",
       "      <td>21.071392</td>\n",
       "      <td>5.278271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19th St &amp; Constitution Ave NW</th>\n",
       "      <td>-77.043600</td>\n",
       "      <td>2.933852</td>\n",
       "      <td>0.923744</td>\n",
       "      <td>3.424931</td>\n",
       "      <td>38.892300</td>\n",
       "      <td>20.549583</td>\n",
       "      <td>2.713115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taft St &amp; E Gude Dr</th>\n",
       "      <td>-77.132954</td>\n",
       "      <td>5.019259</td>\n",
       "      <td>1.253895</td>\n",
       "      <td>3.414167</td>\n",
       "      <td>39.094103</td>\n",
       "      <td>20.485000</td>\n",
       "      <td>0.019941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fairfax Village</th>\n",
       "      <td>-76.952103</td>\n",
       "      <td>7.074807</td>\n",
       "      <td>2.095602</td>\n",
       "      <td>3.340894</td>\n",
       "      <td>38.865590</td>\n",
       "      <td>20.045367</td>\n",
       "      <td>0.023073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hains Point/Buckeye &amp; Ohio Dr SW</th>\n",
       "      <td>-77.030230</td>\n",
       "      <td>3.294770</td>\n",
       "      <td>0.719052</td>\n",
       "      <td>3.325000</td>\n",
       "      <td>38.878433</td>\n",
       "      <td>19.950000</td>\n",
       "      <td>1.747534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Columbia Pike &amp; S Orme St</th>\n",
       "      <td>-77.072315</td>\n",
       "      <td>4.483460</td>\n",
       "      <td>1.341264</td>\n",
       "      <td>3.312500</td>\n",
       "      <td>38.867262</td>\n",
       "      <td>19.875000</td>\n",
       "      <td>0.661972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Columbia Pike &amp; S Dinwiddie St / Arlington Mill Community Center</th>\n",
       "      <td>-77.111530</td>\n",
       "      <td>4.641720</td>\n",
       "      <td>1.526713</td>\n",
       "      <td>3.310000</td>\n",
       "      <td>38.856319</td>\n",
       "      <td>19.860000</td>\n",
       "      <td>0.274492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Harvard St &amp; Adams Mill Rd NW</th>\n",
       "      <td>-77.043358</td>\n",
       "      <td>4.498810</td>\n",
       "      <td>1.566620</td>\n",
       "      <td>3.286208</td>\n",
       "      <td>38.927872</td>\n",
       "      <td>19.717250</td>\n",
       "      <td>1.763799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S Kenmore &amp; 24th St S</th>\n",
       "      <td>-77.084918</td>\n",
       "      <td>5.576033</td>\n",
       "      <td>1.648926</td>\n",
       "      <td>3.279167</td>\n",
       "      <td>38.848454</td>\n",
       "      <td>19.675000</td>\n",
       "      <td>0.124107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iwo Jima Memorial/N Meade &amp; 14th St N</th>\n",
       "      <td>-77.071301</td>\n",
       "      <td>4.649790</td>\n",
       "      <td>1.181326</td>\n",
       "      <td>3.273160</td>\n",
       "      <td>38.889920</td>\n",
       "      <td>19.638958</td>\n",
       "      <td>2.385764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Broschart &amp; Blackwell Rd</th>\n",
       "      <td>-77.200322</td>\n",
       "      <td>0.489623</td>\n",
       "      <td>0.218899</td>\n",
       "      <td>3.263126</td>\n",
       "      <td>39.102099</td>\n",
       "      <td>19.578758</td>\n",
       "      <td>0.011390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12th &amp; Newton St NE</th>\n",
       "      <td>-76.991016</td>\n",
       "      <td>7.526495</td>\n",
       "      <td>2.500499</td>\n",
       "      <td>3.246667</td>\n",
       "      <td>38.933668</td>\n",
       "      <td>19.480000</td>\n",
       "      <td>0.781127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland &amp; Independence Ave SW</th>\n",
       "      <td>-77.018939</td>\n",
       "      <td>3.377864</td>\n",
       "      <td>0.941325</td>\n",
       "      <td>3.238333</td>\n",
       "      <td>38.887299</td>\n",
       "      <td>19.430000</td>\n",
       "      <td>3.878729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norfolk &amp; Rugby Ave</th>\n",
       "      <td>-77.100239</td>\n",
       "      <td>6.060958</td>\n",
       "      <td>0.512190</td>\n",
       "      <td>0.999467</td>\n",
       "      <td>38.990639</td>\n",
       "      <td>5.996800</td>\n",
       "      <td>0.392359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N Quincy St &amp; Wilson Blvd</th>\n",
       "      <td>-77.107673</td>\n",
       "      <td>6.824854</td>\n",
       "      <td>0.575253</td>\n",
       "      <td>0.996667</td>\n",
       "      <td>38.880151</td>\n",
       "      <td>5.980000</td>\n",
       "      <td>1.771467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S Walter Reed Dr &amp; 8th St S</th>\n",
       "      <td>-77.087870</td>\n",
       "      <td>5.796089</td>\n",
       "      <td>0.578754</td>\n",
       "      <td>0.993283</td>\n",
       "      <td>38.866120</td>\n",
       "      <td>5.959700</td>\n",
       "      <td>0.307692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N Veitch  &amp; 20th St N</th>\n",
       "      <td>-77.086502</td>\n",
       "      <td>7.240274</td>\n",
       "      <td>0.833890</td>\n",
       "      <td>0.981847</td>\n",
       "      <td>38.896923</td>\n",
       "      <td>5.891083</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson Blvd &amp; Franklin Rd</th>\n",
       "      <td>-77.088900</td>\n",
       "      <td>7.024962</td>\n",
       "      <td>0.627848</td>\n",
       "      <td>0.973653</td>\n",
       "      <td>38.890400</td>\n",
       "      <td>5.841917</td>\n",
       "      <td>1.911376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23rd &amp; Crystal Dr</th>\n",
       "      <td>-77.049800</td>\n",
       "      <td>5.845530</td>\n",
       "      <td>0.642352</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>38.853300</td>\n",
       "      <td>5.800000</td>\n",
       "      <td>1.749050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fairfax Dr &amp; Kenmore St</th>\n",
       "      <td>-77.101080</td>\n",
       "      <td>6.827157</td>\n",
       "      <td>0.625195</td>\n",
       "      <td>0.963333</td>\n",
       "      <td>38.884616</td>\n",
       "      <td>5.780000</td>\n",
       "      <td>1.157219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fenton St &amp; New York Ave</th>\n",
       "      <td>-77.023082</td>\n",
       "      <td>8.167777</td>\n",
       "      <td>0.778661</td>\n",
       "      <td>0.961667</td>\n",
       "      <td>38.985404</td>\n",
       "      <td>5.770000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Takoma Metro</th>\n",
       "      <td>-77.016855</td>\n",
       "      <td>7.558499</td>\n",
       "      <td>0.588017</td>\n",
       "      <td>0.930804</td>\n",
       "      <td>38.975219</td>\n",
       "      <td>5.584825</td>\n",
       "      <td>1.738657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27th &amp; Crystal Dr</th>\n",
       "      <td>-77.051516</td>\n",
       "      <td>6.919161</td>\n",
       "      <td>0.595690</td>\n",
       "      <td>0.914919</td>\n",
       "      <td>38.848441</td>\n",
       "      <td>5.489517</td>\n",
       "      <td>1.857957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ripley &amp; Bonifant St</th>\n",
       "      <td>-77.029457</td>\n",
       "      <td>4.852867</td>\n",
       "      <td>0.392140</td>\n",
       "      <td>0.913333</td>\n",
       "      <td>38.992679</td>\n",
       "      <td>5.480000</td>\n",
       "      <td>0.238411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8th &amp; F St NE</th>\n",
       "      <td>-76.994749</td>\n",
       "      <td>7.285029</td>\n",
       "      <td>0.547554</td>\n",
       "      <td>0.901442</td>\n",
       "      <td>38.897274</td>\n",
       "      <td>5.408650</td>\n",
       "      <td>5.021181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>King Farm Blvd &amp; Pleasant Dr</th>\n",
       "      <td>-77.171487</td>\n",
       "      <td>6.111884</td>\n",
       "      <td>0.454314</td>\n",
       "      <td>0.891667</td>\n",
       "      <td>39.114688</td>\n",
       "      <td>5.350000</td>\n",
       "      <td>0.239262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bethesda Metro</th>\n",
       "      <td>-77.094537</td>\n",
       "      <td>6.168125</td>\n",
       "      <td>0.512190</td>\n",
       "      <td>0.883900</td>\n",
       "      <td>38.984691</td>\n",
       "      <td>5.303400</td>\n",
       "      <td>1.455420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philadelphia &amp; Maple Ave</th>\n",
       "      <td>-77.011336</td>\n",
       "      <td>6.516146</td>\n",
       "      <td>0.512754</td>\n",
       "      <td>0.880000</td>\n",
       "      <td>38.981280</td>\n",
       "      <td>5.280000</td>\n",
       "      <td>0.516839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia Square Metro / N Monroe St &amp; 9th St N</th>\n",
       "      <td>-77.103148</td>\n",
       "      <td>6.368970</td>\n",
       "      <td>0.505749</td>\n",
       "      <td>0.873856</td>\n",
       "      <td>38.882788</td>\n",
       "      <td>5.243133</td>\n",
       "      <td>1.856458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mount Vernon Ave &amp; E Nelson Ave</th>\n",
       "      <td>-77.057619</td>\n",
       "      <td>5.973294</td>\n",
       "      <td>0.458849</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>38.820064</td>\n",
       "      <td>5.170000</td>\n",
       "      <td>0.887134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cordell &amp; Norfolk Ave</th>\n",
       "      <td>-77.098029</td>\n",
       "      <td>5.862272</td>\n",
       "      <td>0.383710</td>\n",
       "      <td>0.858061</td>\n",
       "      <td>38.989540</td>\n",
       "      <td>5.148367</td>\n",
       "      <td>0.790964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Congress Heights Metro</th>\n",
       "      <td>-76.987823</td>\n",
       "      <td>7.619383</td>\n",
       "      <td>0.630407</td>\n",
       "      <td>0.828333</td>\n",
       "      <td>38.844711</td>\n",
       "      <td>4.970000</td>\n",
       "      <td>0.079192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crystal City Metro / 18th &amp; Bell St</th>\n",
       "      <td>-77.051141</td>\n",
       "      <td>6.741843</td>\n",
       "      <td>0.595690</td>\n",
       "      <td>0.819771</td>\n",
       "      <td>38.857063</td>\n",
       "      <td>4.918625</td>\n",
       "      <td>2.771844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson Blvd &amp; N Uhle St</th>\n",
       "      <td>-77.084600</td>\n",
       "      <td>6.738273</td>\n",
       "      <td>0.463603</td>\n",
       "      <td>0.799358</td>\n",
       "      <td>38.891696</td>\n",
       "      <td>4.796150</td>\n",
       "      <td>2.059392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N Veitch &amp; Key Blvd</th>\n",
       "      <td>-77.086045</td>\n",
       "      <td>6.520936</td>\n",
       "      <td>0.453992</td>\n",
       "      <td>0.788139</td>\n",
       "      <td>38.893241</td>\n",
       "      <td>4.728833</td>\n",
       "      <td>1.214109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26th &amp; S Clark St</th>\n",
       "      <td>-77.051520</td>\n",
       "      <td>6.422424</td>\n",
       "      <td>0.440665</td>\n",
       "      <td>0.786667</td>\n",
       "      <td>38.850688</td>\n",
       "      <td>4.720000</td>\n",
       "      <td>1.013148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carroll &amp; Westmoreland Ave</th>\n",
       "      <td>-77.011210</td>\n",
       "      <td>7.150856</td>\n",
       "      <td>0.325118</td>\n",
       "      <td>0.785692</td>\n",
       "      <td>38.975000</td>\n",
       "      <td>4.714150</td>\n",
       "      <td>0.555947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carroll &amp; Ethan Allen Ave</th>\n",
       "      <td>-77.006472</td>\n",
       "      <td>7.349650</td>\n",
       "      <td>0.588017</td>\n",
       "      <td>0.778333</td>\n",
       "      <td>38.977933</td>\n",
       "      <td>4.670000</td>\n",
       "      <td>0.844495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N Adams St &amp; Lee Hwy</th>\n",
       "      <td>-77.089006</td>\n",
       "      <td>6.150740</td>\n",
       "      <td>0.381889</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>38.895930</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>1.034375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anacostia Metro</th>\n",
       "      <td>-76.994637</td>\n",
       "      <td>6.790037</td>\n",
       "      <td>0.480977</td>\n",
       "      <td>0.723511</td>\n",
       "      <td>38.862669</td>\n",
       "      <td>4.341067</td>\n",
       "      <td>0.799523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norfolk Ave &amp; Fairmont St</th>\n",
       "      <td>-77.096539</td>\n",
       "      <td>6.238947</td>\n",
       "      <td>0.325465</td>\n",
       "      <td>0.711503</td>\n",
       "      <td>38.988562</td>\n",
       "      <td>4.269017</td>\n",
       "      <td>0.603300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aurora Hills Community Ctr/18th &amp; Hayes St</th>\n",
       "      <td>-77.059490</td>\n",
       "      <td>7.107053</td>\n",
       "      <td>0.307312</td>\n",
       "      <td>0.571667</td>\n",
       "      <td>38.857866</td>\n",
       "      <td>3.430000</td>\n",
       "      <td>1.239268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pleasant St &amp; MLK Ave SE</th>\n",
       "      <td>-76.990037</td>\n",
       "      <td>6.867880</td>\n",
       "      <td>0.261453</td>\n",
       "      <td>0.386667</td>\n",
       "      <td>38.863897</td>\n",
       "      <td>2.320000</td>\n",
       "      <td>0.354636</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>350 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Long (Start)  \\\n",
       "Starting Station                                                   \n",
       "Prince St & Union St                                  -77.040363   \n",
       "47th & Elm St                                         -77.091991   \n",
       "S George Mason Dr & 13th St S                         -77.100555   \n",
       "River Rd & Landy Ln                                   -77.103381   \n",
       "Lincoln Memorial                                      -77.049426   \n",
       "Smithsonian / Jefferson Dr & 12th St SW               -77.028580   \n",
       "Randle Circle & Minnesota Ave SE                      -76.960700   \n",
       "Fallsgrove Dr & W Montgomery Ave                      -77.188014   \n",
       "Ohio Dr & West Basin Dr SW / MLK & FDR Memorials      -77.046570   \n",
       "Jefferson Dr & 14th St SW                             -77.032429   \n",
       "Jefferson Memorial                                    -77.037413   \n",
       "34th & Water St NW                                    -77.067786   \n",
       "Shady Grove Hospital                                  -77.196636   \n",
       "S Four Mile Run Dr & S Shirlington Rd                 -77.085931   \n",
       "S Arlington Mill Dr & Campbell Ave                    -77.089555   \n",
       "Traville Gateway Dr & Gudelsky Dr                     -77.202501   \n",
       "Pennsylvania & Minnesota Ave SE                       -76.971015   \n",
       "21st St & Constitution Ave NW                         -77.046567   \n",
       "19th St & Constitution Ave NW                         -77.043600   \n",
       "Taft St & E Gude Dr                                   -77.132954   \n",
       "Fairfax Village                                       -76.952103   \n",
       "Hains Point/Buckeye & Ohio Dr SW                      -77.030230   \n",
       "Columbia Pike & S Orme St                             -77.072315   \n",
       "Columbia Pike & S Dinwiddie St / Arlington Mill...    -77.111530   \n",
       "Harvard St & Adams Mill Rd NW                         -77.043358   \n",
       "S Kenmore & 24th St S                                 -77.084918   \n",
       "Iwo Jima Memorial/N Meade & 14th St N                 -77.071301   \n",
       "Broschart & Blackwell Rd                              -77.200322   \n",
       "12th & Newton St NE                                   -76.991016   \n",
       "Maryland & Independence Ave SW                        -77.018939   \n",
       "...                                                          ...   \n",
       "Norfolk & Rugby Ave                                   -77.100239   \n",
       "N Quincy St & Wilson Blvd                             -77.107673   \n",
       "S Walter Reed Dr & 8th St S                           -77.087870   \n",
       "N Veitch  & 20th St N                                 -77.086502   \n",
       "Wilson Blvd & Franklin Rd                             -77.088900   \n",
       "23rd & Crystal Dr                                     -77.049800   \n",
       "Fairfax Dr & Kenmore St                               -77.101080   \n",
       "Fenton St & New York Ave                              -77.023082   \n",
       "Takoma Metro                                          -77.016855   \n",
       "27th & Crystal Dr                                     -77.051516   \n",
       "Ripley & Bonifant St                                  -77.029457   \n",
       "8th & F St NE                                         -76.994749   \n",
       "King Farm Blvd & Pleasant Dr                          -77.171487   \n",
       "Bethesda Metro                                        -77.094537   \n",
       "Philadelphia & Maple Ave                              -77.011336   \n",
       "Virginia Square Metro / N Monroe St & 9th St N        -77.103148   \n",
       "Mount Vernon Ave & E Nelson Ave                       -77.057619   \n",
       "Cordell & Norfolk Ave                                 -77.098029   \n",
       "Congress Heights Metro                                -76.987823   \n",
       "Crystal City Metro / 18th & Bell St                   -77.051141   \n",
       "Wilson Blvd & N Uhle St                               -77.084600   \n",
       "N Veitch & Key Blvd                                   -77.086045   \n",
       "26th & S Clark St                                     -77.051520   \n",
       "Carroll & Westmoreland Ave                            -77.011210   \n",
       "Carroll & Ethan Allen Ave                             -77.006472   \n",
       "N Adams St & Lee Hwy                                  -77.089006   \n",
       "Anacostia Metro                                       -76.994637   \n",
       "Norfolk Ave & Fairmont St                             -77.096539   \n",
       "Aurora Hills Community Ctr/18th & Hayes St            -77.059490   \n",
       "Pleasant St & MLK Ave SE                              -76.990037   \n",
       "\n",
       "                                                    Average Speed  \\\n",
       "Starting Station                                                    \n",
       "Prince St & Union St                                     3.256164   \n",
       "47th & Elm St                                            5.980837   \n",
       "S George Mason Dr & 13th St S                            3.352359   \n",
       "River Rd & Landy Ln                                      6.784992   \n",
       "Lincoln Memorial                                         2.511495   \n",
       "Smithsonian / Jefferson Dr & 12th St SW                  2.112316   \n",
       "Randle Circle & Minnesota Ave SE                         4.564116   \n",
       "Fallsgrove Dr & W Montgomery Ave                         0.000000   \n",
       "Ohio Dr & West Basin Dr SW / MLK & FDR Memorials         2.138904   \n",
       "Jefferson Dr & 14th St SW                                2.402684   \n",
       "Jefferson Memorial                                       3.174741   \n",
       "34th & Water St NW                                       4.147182   \n",
       "Shady Grove Hospital                                     4.559129   \n",
       "S Four Mile Run Dr & S Shirlington Rd                    5.173468   \n",
       "S Arlington Mill Dr & Campbell Ave                       5.169456   \n",
       "Traville Gateway Dr & Gudelsky Dr                        0.000000   \n",
       "Pennsylvania & Minnesota Ave SE                          6.535476   \n",
       "21st St & Constitution Ave NW                            3.159242   \n",
       "19th St & Constitution Ave NW                            2.933852   \n",
       "Taft St & E Gude Dr                                      5.019259   \n",
       "Fairfax Village                                          7.074807   \n",
       "Hains Point/Buckeye & Ohio Dr SW                         3.294770   \n",
       "Columbia Pike & S Orme St                                4.483460   \n",
       "Columbia Pike & S Dinwiddie St / Arlington Mill...       4.641720   \n",
       "Harvard St & Adams Mill Rd NW                            4.498810   \n",
       "S Kenmore & 24th St S                                    5.576033   \n",
       "Iwo Jima Memorial/N Meade & 14th St N                    4.649790   \n",
       "Broschart & Blackwell Rd                                 0.489623   \n",
       "12th & Newton St NE                                      7.526495   \n",
       "Maryland & Independence Ave SW                           3.377864   \n",
       "...                                                           ...   \n",
       "Norfolk & Rugby Ave                                      6.060958   \n",
       "N Quincy St & Wilson Blvd                                6.824854   \n",
       "S Walter Reed Dr & 8th St S                              5.796089   \n",
       "N Veitch  & 20th St N                                    7.240274   \n",
       "Wilson Blvd & Franklin Rd                                7.024962   \n",
       "23rd & Crystal Dr                                        5.845530   \n",
       "Fairfax Dr & Kenmore St                                  6.827157   \n",
       "Fenton St & New York Ave                                 8.167777   \n",
       "Takoma Metro                                             7.558499   \n",
       "27th & Crystal Dr                                        6.919161   \n",
       "Ripley & Bonifant St                                     4.852867   \n",
       "8th & F St NE                                            7.285029   \n",
       "King Farm Blvd & Pleasant Dr                             6.111884   \n",
       "Bethesda Metro                                           6.168125   \n",
       "Philadelphia & Maple Ave                                 6.516146   \n",
       "Virginia Square Metro / N Monroe St & 9th St N           6.368970   \n",
       "Mount Vernon Ave & E Nelson Ave                          5.973294   \n",
       "Cordell & Norfolk Ave                                    5.862272   \n",
       "Congress Heights Metro                                   7.619383   \n",
       "Crystal City Metro / 18th & Bell St                      6.741843   \n",
       "Wilson Blvd & N Uhle St                                  6.738273   \n",
       "N Veitch & Key Blvd                                      6.520936   \n",
       "26th & S Clark St                                        6.422424   \n",
       "Carroll & Westmoreland Ave                               7.150856   \n",
       "Carroll & Ethan Allen Ave                                7.349650   \n",
       "N Adams St & Lee Hwy                                     6.150740   \n",
       "Anacostia Metro                                          6.790037   \n",
       "Norfolk Ave & Fairmont St                                6.238947   \n",
       "Aurora Hills Community Ctr/18th & Hayes St               7.107053   \n",
       "Pleasant St & MLK Ave SE                                 6.867880   \n",
       "\n",
       "                                                    Distance by Lat/Long  \\\n",
       "Starting Station                                                           \n",
       "Prince St & Union St                                            0.698327   \n",
       "47th & Elm St                                                   1.518164   \n",
       "S George Mason Dr & 13th St S                                   0.761952   \n",
       "River Rd & Landy Ln                                             1.761135   \n",
       "Lincoln Memorial                                                1.120962   \n",
       "Smithsonian / Jefferson Dr & 12th St SW                         0.824447   \n",
       "Randle Circle & Minnesota Ave SE                                1.383689   \n",
       "Fallsgrove Dr & W Montgomery Ave                                0.000000   \n",
       "Ohio Dr & West Basin Dr SW / MLK & FDR Memorials                0.819373   \n",
       "Jefferson Dr & 14th St SW                                       0.821984   \n",
       "Jefferson Memorial                                              1.119273   \n",
       "34th & Water St NW                                              1.289664   \n",
       "Shady Grove Hospital                                            0.231261   \n",
       "S Four Mile Run Dr & S Shirlington Rd                           1.871691   \n",
       "S Arlington Mill Dr & Campbell Ave                              1.077868   \n",
       "Traville Gateway Dr & Gudelsky Dr                               0.000000   \n",
       "Pennsylvania & Minnesota Ave SE                                 2.459086   \n",
       "21st St & Constitution Ave NW                                   1.001917   \n",
       "19th St & Constitution Ave NW                                   0.923744   \n",
       "Taft St & E Gude Dr                                             1.253895   \n",
       "Fairfax Village                                                 2.095602   \n",
       "Hains Point/Buckeye & Ohio Dr SW                                0.719052   \n",
       "Columbia Pike & S Orme St                                       1.341264   \n",
       "Columbia Pike & S Dinwiddie St / Arlington Mill...              1.526713   \n",
       "Harvard St & Adams Mill Rd NW                                   1.566620   \n",
       "S Kenmore & 24th St S                                           1.648926   \n",
       "Iwo Jima Memorial/N Meade & 14th St N                           1.181326   \n",
       "Broschart & Blackwell Rd                                        0.218899   \n",
       "12th & Newton St NE                                             2.500499   \n",
       "Maryland & Independence Ave SW                                  0.941325   \n",
       "...                                                                  ...   \n",
       "Norfolk & Rugby Ave                                             0.512190   \n",
       "N Quincy St & Wilson Blvd                                       0.575253   \n",
       "S Walter Reed Dr & 8th St S                                     0.578754   \n",
       "N Veitch  & 20th St N                                           0.833890   \n",
       "Wilson Blvd & Franklin Rd                                       0.627848   \n",
       "23rd & Crystal Dr                                               0.642352   \n",
       "Fairfax Dr & Kenmore St                                         0.625195   \n",
       "Fenton St & New York Ave                                        0.778661   \n",
       "Takoma Metro                                                    0.588017   \n",
       "27th & Crystal Dr                                               0.595690   \n",
       "Ripley & Bonifant St                                            0.392140   \n",
       "8th & F St NE                                                   0.547554   \n",
       "King Farm Blvd & Pleasant Dr                                    0.454314   \n",
       "Bethesda Metro                                                  0.512190   \n",
       "Philadelphia & Maple Ave                                        0.512754   \n",
       "Virginia Square Metro / N Monroe St & 9th St N                  0.505749   \n",
       "Mount Vernon Ave & E Nelson Ave                                 0.458849   \n",
       "Cordell & Norfolk Ave                                           0.383710   \n",
       "Congress Heights Metro                                          0.630407   \n",
       "Crystal City Metro / 18th & Bell St                             0.595690   \n",
       "Wilson Blvd & N Uhle St                                         0.463603   \n",
       "N Veitch & Key Blvd                                             0.453992   \n",
       "26th & S Clark St                                               0.440665   \n",
       "Carroll & Westmoreland Ave                                      0.325118   \n",
       "Carroll & Ethan Allen Ave                                       0.588017   \n",
       "N Adams St & Lee Hwy                                            0.381889   \n",
       "Anacostia Metro                                                 0.480977   \n",
       "Norfolk Ave & Fairmont St                                       0.325465   \n",
       "Aurora Hills Community Ctr/18th & Hayes St                      0.307312   \n",
       "Pleasant St & MLK Ave SE                                        0.261453   \n",
       "\n",
       "                                                    Distance by Ride Duration  \\\n",
       "Starting Station                                                                \n",
       "Prince St & Union St                                                 6.121644   \n",
       "47th & Elm St                                                        4.595000   \n",
       "S George Mason Dr & 13th St S                                        4.504944   \n",
       "River Rd & Landy Ln                                                  4.266744   \n",
       "Lincoln Memorial                                                     4.254851   \n",
       "Smithsonian / Jefferson Dr & 12th St SW                              4.250000   \n",
       "Randle Circle & Minnesota Ave SE                                     4.125597   \n",
       "Fallsgrove Dr & W Montgomery Ave                                     4.123264   \n",
       "Ohio Dr & West Basin Dr SW / MLK & FDR Memorials                     4.121667   \n",
       "Jefferson Dr & 14th St SW                                            3.833333   \n",
       "Jefferson Memorial                                                   3.810225   \n",
       "34th & Water St NW                                                   3.767317   \n",
       "Shady Grove Hospital                                                 3.733333   \n",
       "S Four Mile Run Dr & S Shirlington Rd                                3.728461   \n",
       "S Arlington Mill Dr & Campbell Ave                                   3.671667   \n",
       "Traville Gateway Dr & Gudelsky Dr                                    3.577047   \n",
       "Pennsylvania & Minnesota Ave SE                                      3.564167   \n",
       "21st St & Constitution Ave NW                                        3.511899   \n",
       "19th St & Constitution Ave NW                                        3.424931   \n",
       "Taft St & E Gude Dr                                                  3.414167   \n",
       "Fairfax Village                                                      3.340894   \n",
       "Hains Point/Buckeye & Ohio Dr SW                                     3.325000   \n",
       "Columbia Pike & S Orme St                                            3.312500   \n",
       "Columbia Pike & S Dinwiddie St / Arlington Mill...                   3.310000   \n",
       "Harvard St & Adams Mill Rd NW                                        3.286208   \n",
       "S Kenmore & 24th St S                                                3.279167   \n",
       "Iwo Jima Memorial/N Meade & 14th St N                                3.273160   \n",
       "Broschart & Blackwell Rd                                             3.263126   \n",
       "12th & Newton St NE                                                  3.246667   \n",
       "Maryland & Independence Ave SW                                       3.238333   \n",
       "...                                                                       ...   \n",
       "Norfolk & Rugby Ave                                                  0.999467   \n",
       "N Quincy St & Wilson Blvd                                            0.996667   \n",
       "S Walter Reed Dr & 8th St S                                          0.993283   \n",
       "N Veitch  & 20th St N                                                0.981847   \n",
       "Wilson Blvd & Franklin Rd                                            0.973653   \n",
       "23rd & Crystal Dr                                                    0.966667   \n",
       "Fairfax Dr & Kenmore St                                              0.963333   \n",
       "Fenton St & New York Ave                                             0.961667   \n",
       "Takoma Metro                                                         0.930804   \n",
       "27th & Crystal Dr                                                    0.914919   \n",
       "Ripley & Bonifant St                                                 0.913333   \n",
       "8th & F St NE                                                        0.901442   \n",
       "King Farm Blvd & Pleasant Dr                                         0.891667   \n",
       "Bethesda Metro                                                       0.883900   \n",
       "Philadelphia & Maple Ave                                             0.880000   \n",
       "Virginia Square Metro / N Monroe St & 9th St N                       0.873856   \n",
       "Mount Vernon Ave & E Nelson Ave                                      0.861667   \n",
       "Cordell & Norfolk Ave                                                0.858061   \n",
       "Congress Heights Metro                                               0.828333   \n",
       "Crystal City Metro / 18th & Bell St                                  0.819771   \n",
       "Wilson Blvd & N Uhle St                                              0.799358   \n",
       "N Veitch & Key Blvd                                                  0.788139   \n",
       "26th & S Clark St                                                    0.786667   \n",
       "Carroll & Westmoreland Ave                                           0.785692   \n",
       "Carroll & Ethan Allen Ave                                            0.778333   \n",
       "N Adams St & Lee Hwy                                                 0.750000   \n",
       "Anacostia Metro                                                      0.723511   \n",
       "Norfolk Ave & Fairmont St                                            0.711503   \n",
       "Aurora Hills Community Ctr/18th & Hayes St                           0.571667   \n",
       "Pleasant St & MLK Ave SE                                             0.386667   \n",
       "\n",
       "                                                    Lat (Start)    Minutes  \\\n",
       "Starting Station                                                             \n",
       "Prince St & Union St                                  38.803124  36.729867   \n",
       "47th & Elm St                                         38.982456  27.570000   \n",
       "S George Mason Dr & 13th St S                         38.854691  27.029667   \n",
       "River Rd & Landy Ln                                   38.964992  25.600467   \n",
       "Lincoln Memorial                                      38.888251  25.529108   \n",
       "Smithsonian / Jefferson Dr & 12th St SW               38.888767  25.500000   \n",
       "Randle Circle & Minnesota Ave SE                      38.878000  24.753583   \n",
       "Fallsgrove Dr & W Montgomery Ave                      39.099376  24.739583   \n",
       "Ohio Dr & West Basin Dr SW / MLK & FDR Memorials      38.884120  24.730000   \n",
       "Jefferson Dr & 14th St SW                             38.888553  23.000000   \n",
       "Jefferson Memorial                                    38.879819  22.861350   \n",
       "34th & Water St NW                                    38.903582  22.603900   \n",
       "Shady Grove Hospital                                  39.097636  22.400000   \n",
       "S Four Mile Run Dr & S Shirlington Rd                 38.844400  22.370767   \n",
       "S Arlington Mill Dr & Campbell Ave                    38.842320  22.030000   \n",
       "Traville Gateway Dr & Gudelsky Dr                     39.093783  21.462283   \n",
       "Pennsylvania & Minnesota Ave SE                       38.873057  21.385000   \n",
       "21st St & Constitution Ave NW                         38.892459  21.071392   \n",
       "19th St & Constitution Ave NW                         38.892300  20.549583   \n",
       "Taft St & E Gude Dr                                   39.094103  20.485000   \n",
       "Fairfax Village                                       38.865590  20.045367   \n",
       "Hains Point/Buckeye & Ohio Dr SW                      38.878433  19.950000   \n",
       "Columbia Pike & S Orme St                             38.867262  19.875000   \n",
       "Columbia Pike & S Dinwiddie St / Arlington Mill...    38.856319  19.860000   \n",
       "Harvard St & Adams Mill Rd NW                         38.927872  19.717250   \n",
       "S Kenmore & 24th St S                                 38.848454  19.675000   \n",
       "Iwo Jima Memorial/N Meade & 14th St N                 38.889920  19.638958   \n",
       "Broschart & Blackwell Rd                              39.102099  19.578758   \n",
       "12th & Newton St NE                                   38.933668  19.480000   \n",
       "Maryland & Independence Ave SW                        38.887299  19.430000   \n",
       "...                                                         ...        ...   \n",
       "Norfolk & Rugby Ave                                   38.990639   5.996800   \n",
       "N Quincy St & Wilson Blvd                             38.880151   5.980000   \n",
       "S Walter Reed Dr & 8th St S                           38.866120   5.959700   \n",
       "N Veitch  & 20th St N                                 38.896923   5.891083   \n",
       "Wilson Blvd & Franklin Rd                             38.890400   5.841917   \n",
       "23rd & Crystal Dr                                     38.853300   5.800000   \n",
       "Fairfax Dr & Kenmore St                               38.884616   5.780000   \n",
       "Fenton St & New York Ave                              38.985404   5.770000   \n",
       "Takoma Metro                                          38.975219   5.584825   \n",
       "27th & Crystal Dr                                     38.848441   5.489517   \n",
       "Ripley & Bonifant St                                  38.992679   5.480000   \n",
       "8th & F St NE                                         38.897274   5.408650   \n",
       "King Farm Blvd & Pleasant Dr                          39.114688   5.350000   \n",
       "Bethesda Metro                                        38.984691   5.303400   \n",
       "Philadelphia & Maple Ave                              38.981280   5.280000   \n",
       "Virginia Square Metro / N Monroe St & 9th St N        38.882788   5.243133   \n",
       "Mount Vernon Ave & E Nelson Ave                       38.820064   5.170000   \n",
       "Cordell & Norfolk Ave                                 38.989540   5.148367   \n",
       "Congress Heights Metro                                38.844711   4.970000   \n",
       "Crystal City Metro / 18th & Bell St                   38.857063   4.918625   \n",
       "Wilson Blvd & N Uhle St                               38.891696   4.796150   \n",
       "N Veitch & Key Blvd                                   38.893241   4.728833   \n",
       "26th & S Clark St                                     38.850688   4.720000   \n",
       "Carroll & Westmoreland Ave                            38.975000   4.714150   \n",
       "Carroll & Ethan Allen Ave                             38.977933   4.670000   \n",
       "N Adams St & Lee Hwy                                  38.895930   4.500000   \n",
       "Anacostia Metro                                       38.862669   4.341067   \n",
       "Norfolk Ave & Fairmont St                             38.988562   4.269017   \n",
       "Aurora Hills Community Ctr/18th & Hayes St            38.857866   3.430000   \n",
       "Pleasant St & MLK Ave SE                              38.863897   2.320000   \n",
       "\n",
       "                                                      Busiest  \n",
       "Starting Station                                               \n",
       "Prince St & Union St                                 1.098771  \n",
       "47th & Elm St                                        0.413278  \n",
       "S George Mason Dr & 13th St S                        0.064692  \n",
       "River Rd & Landy Ln                                  0.510494  \n",
       "Lincoln Memorial                                    16.844947  \n",
       "Smithsonian / Jefferson Dr & 12th St SW              8.907653  \n",
       "Randle Circle & Minnesota Ave SE                     0.026617  \n",
       "Fallsgrove Dr & W Montgomery Ave                     0.052032  \n",
       "Ohio Dr & West Basin Dr SW / MLK & FDR Memorials     4.213056  \n",
       "Jefferson Dr & 14th St SW                           13.347899  \n",
       "Jefferson Memorial                                   7.807070  \n",
       "34th & Water St NW                                   3.208482  \n",
       "Shady Grove Hospital                                 0.007632  \n",
       "S Four Mile Run Dr & S Shirlington Rd                0.390897  \n",
       "S Arlington Mill Dr & Campbell Ave                   0.834542  \n",
       "Traville Gateway Dr & Gudelsky Dr                    0.036986  \n",
       "Pennsylvania & Minnesota Ave SE                      0.371132  \n",
       "21st St & Constitution Ave NW                        5.278271  \n",
       "19th St & Constitution Ave NW                        2.713115  \n",
       "Taft St & E Gude Dr                                  0.019941  \n",
       "Fairfax Village                                      0.023073  \n",
       "Hains Point/Buckeye & Ohio Dr SW                     1.747534  \n",
       "Columbia Pike & S Orme St                            0.661972  \n",
       "Columbia Pike & S Dinwiddie St / Arlington Mill...   0.274492  \n",
       "Harvard St & Adams Mill Rd NW                        1.763799  \n",
       "S Kenmore & 24th St S                                0.124107  \n",
       "Iwo Jima Memorial/N Meade & 14th St N                2.385764  \n",
       "Broschart & Blackwell Rd                             0.011390  \n",
       "12th & Newton St NE                                  0.781127  \n",
       "Maryland & Independence Ave SW                       3.878729  \n",
       "...                                                       ...  \n",
       "Norfolk & Rugby Ave                                  0.392359  \n",
       "N Quincy St & Wilson Blvd                            1.771467  \n",
       "S Walter Reed Dr & 8th St S                          0.307692  \n",
       "N Veitch  & 20th St N                                     NaN  \n",
       "Wilson Blvd & Franklin Rd                            1.911376  \n",
       "23rd & Crystal Dr                                    1.749050  \n",
       "Fairfax Dr & Kenmore St                              1.157219  \n",
       "Fenton St & New York Ave                                  NaN  \n",
       "Takoma Metro                                         1.738657  \n",
       "27th & Crystal Dr                                    1.857957  \n",
       "Ripley & Bonifant St                                 0.238411  \n",
       "8th & F St NE                                        5.021181  \n",
       "King Farm Blvd & Pleasant Dr                         0.239262  \n",
       "Bethesda Metro                                       1.455420  \n",
       "Philadelphia & Maple Ave                             0.516839  \n",
       "Virginia Square Metro / N Monroe St & 9th St N       1.856458  \n",
       "Mount Vernon Ave & E Nelson Ave                      0.887134  \n",
       "Cordell & Norfolk Ave                                0.790964  \n",
       "Congress Heights Metro                               0.079192  \n",
       "Crystal City Metro / 18th & Bell St                  2.771844  \n",
       "Wilson Blvd & N Uhle St                              2.059392  \n",
       "N Veitch & Key Blvd                                  1.214109  \n",
       "26th & S Clark St                                    1.013148  \n",
       "Carroll & Westmoreland Ave                           0.555947  \n",
       "Carroll & Ethan Allen Ave                            0.844495  \n",
       "N Adams St & Lee Hwy                                 1.034375  \n",
       "Anacostia Metro                                      0.799523  \n",
       "Norfolk Ave & Fairmont St                            0.603300  \n",
       "Aurora Hills Community Ctr/18th & Hayes St           1.239268  \n",
       "Pleasant St & MLK Ave SE                             0.354636  \n",
       "\n",
       "[350 rows x 7 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "map_df.sort('Minutes',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2873"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(bike_share[bike_share['Starting Station'] == 'Prince St & Union St'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.FancyArrow at 0x14fb8da0>"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Bg+DyZeVR1WB9VdRqpWV0rzGL559XLryxsUoX3+DBythJVZ/v2FFpBURFKQGnWzfw9TWs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\nM5JUhBBClBlJKkIIIcrM/wFjUxpBvnfKCAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x155a2518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"whitegrid\")\n",
    "plt.figure(figsize=(6,4))\n",
    "ax1 = sns.distplot(bike_share[(bike_share['Distance by Lat/Long'] < 8) & (bike_share['Member Type'] == 'Registered')]['Distance by Lat/Long'],bins=(30), \\\n",
    "             label= \"Registered Users\", norm_hist=True, kde=False)\n",
    "\n",
    "ax1.set(xlim=(0, 8))\n",
    "\n",
    "sns.distplot(bike_share[(bike_share['Distance by Ride Duration'] < 8) & (bike_share['Member Type'] == 'Casual')]['Distance by Ride Duration'], bins=(30), \\\n",
    "             label= \"Casual Users\", norm_hist=True, kde=False).set(xlim=(0, 8))\n",
    "\n",
    "sns.axlabel('Distance (miles)', 'Percent of Rides', fontsize=14)\n",
    "plt.legend(frameon=False, fontsize=14, loc='best')\n",
    "plt.xticks(fontsize = 14)\n",
    "plt.yticks(fontsize = 14)\n",
    "plt.xticks(np.arange(0,9,1))\n",
    "ax1.grid(False)\n",
    "ax1.spines[\"top\"].set_visible(False)  \n",
    "ax1.spines[\"right\"].set_visible(False) \n",
    "ax1.spines[\"left\"].set_visible(False) \n",
    "\n",
    "\n",
    "def func(x, pos):  \n",
    "   s = '{:.0f}%'.format(x * 100)\n",
    "   return s\n",
    "\n",
    "y_format = tkr.FuncFormatter(func)\n",
    "ax1.yaxis.set_major_formatter(y_format)\n",
    "\n",
    "# arrows and annotation\n",
    "ax1.text(x=bike_share[bike_share['Member Type'] == 'Registered']['Distance by Lat/Long'].quantile(0.50) - 0.1,y=0.73,\\\n",
    "         s='Median: {:,.1f} miles'.format(bike_share[bike_share['Member Type'] == 'Registered']['Distance by Lat/Long'].quantile(0.50)), color='blue',\\\n",
    "         alpha=0.5, backgroundcolor='white', size=14, weight='bold')\n",
    "ax1.arrow(bike_share[bike_share['Member Type'] == 'Registered']['Distance by Lat/Long'].quantile(0.50), 0.73, 0,-0.075, head_width=0.07, head_length=0.015,\\\n",
    "          color='blue', alpha=0.5)\n",
    "\n",
    "ax1.text(x=bike_share[bike_share['Member Type'] == 'Casual']['Distance by Ride Duration'].quantile(0.50) - 0.1,y=0.28,\\\n",
    "         s='Median: {:,.1f} miles'.format(bike_share[bike_share['Member Type'] == 'Casual']['Distance by Ride Duration'].quantile(0.50)), color='green',\\\n",
    "         alpha=0.5, backgroundcolor='white', size=14, weight='bold')\n",
    "ax1.arrow(bike_share[bike_share['Member Type'] == 'Casual']['Distance by Ride Duration'].quantile(0.50), 0.27, 0,-0.035, head_width=0.07, head_length=0.015, \\\n",
    "          color='green', alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x2742e0f0>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kKyuLbdu26W33K4QQQhiUVI4cOcLYsWPRarWcOnUKjUZDXl4eU6ZMYceOHXc6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\nBEEQhGYjkoogCILQbERSEQRBEJrNfwGcqLJdKDIjqQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcee1c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"whitegrid\")\n",
    "plt.figure(figsize=(6,4))\n",
    "ax1 = sns.distplot(bike_share[(bike_share['Distance by Lat/Long'] < 8) & (bike_share['Member Type'] == 'Registered')]['Distance by Lat/Long'],bins=(30), \\\n",
    "             label= \"Registered Users\", norm_hist=True, kde=False)\n",
    "\n",
    "ax1.set(xlim=(0, 8))\n",
    "\n",
    "sns.distplot(bike_share[(bike_share['Distance by Lat/Long'] < 8) & (bike_share['Member Type'] == 'Casual')]['Distance by Lat/Long'], bins=(30), \\\n",
    "             label= \"Casual Users\", norm_hist=True, kde=False).set(xlim=(0, 8))\n",
    "\n",
    "sns.axlabel('Distance (miles)', 'Percent of Rides', fontsize=14)\n",
    "plt.legend(frameon=False, fontsize=14, loc='best')\n",
    "plt.xticks(fontsize = 14)\n",
    "plt.yticks(fontsize = 14)\n",
    "plt.xticks(np.arange(0,9,1))\n",
    "ax1.grid(False)\n",
    "ax1.spines[\"top\"].set_visible(False)  \n",
    "ax1.spines[\"right\"].set_visible(False) \n",
    "ax1.spines[\"left\"].set_visible(False) \n",
    "\n",
    "\n",
    "def func(x, pos):  \n",
    "   s = '{:.0f}%'.format(x * 100)\n",
    "   return s\n",
    "\n",
    "y_format = tkr.FuncFormatter(func)\n",
    "ax1.yaxis.set_major_formatter(y_format)\n",
    "\n",
    "# arrows and annotation\n",
    "ax1.text(x=2.5,y=0.4,\\\n",
    "         s='Median: {:,.1f} miles'.format(bike_share[bike_share['Member Type'] == 'Registered']['Distance by Lat/Long'].quantile(0.50)), color='black',\\\n",
    "         alpha=0.5, backgroundcolor='white', size=14, weight='bold')\n",
    "# ax1.arrow(bike_share[bike_share['Member Type'] == 'Registered']['Distance by Lat/Long'].quantile(0.50), 0.73, 0,-0.075, head_width=0.07, head_length=0.015,\\\n",
    "#           color='black', alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.FancyArrow at 0x403ce8d0>"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4McePH2flypUl9jVq1CgmTpyIp6cnXbp0ITo6Gp1Oh6+vL1FRUdSvX/VPHFd0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\nBEEQhHrzf2UsnahAzRSVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14b23dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"whitegrid\")\n",
    "plt.figure(figsize=(6,4))\n",
    "ax1 = sns.distplot(bike_share[(bike_share['Distance by Ride Duration'] < 8) & (bike_share['Member Type'] == 'Registered')]['Distance by Ride Duration'],bins=(30), \\\n",
    "             label= \"Registered Users\", norm_hist=True, kde=False)\n",
    "\n",
    "ax1.set(xlim=(0, 8))\n",
    "\n",
    "sns.distplot(bike_share[(bike_share['Distance by Ride Duration'] < 8) & (bike_share['Member Type'] == 'Casual')]['Distance by Ride Duration'], bins=(30), \\\n",
    "             label= \"Casual Users\", norm_hist=True, kde=False).set(xlim=(0, 8))\n",
    "\n",
    "sns.axlabel('Distance (miles)', 'Percent of Rides', fontsize=14)\n",
    "plt.legend(frameon=False, fontsize=14, loc='best')\n",
    "plt.xticks(fontsize = 14)\n",
    "plt.yticks(fontsize = 14)\n",
    "plt.xticks(np.arange(0,9,1))\n",
    "ax1.grid(False)\n",
    "ax1.spines[\"top\"].set_visible(False)  \n",
    "ax1.spines[\"right\"].set_visible(False) \n",
    "ax1.spines[\"left\"].set_visible(False) \n",
    "\n",
    "\n",
    "def func(x, pos):  \n",
    "   s = '{:.0f}%'.format(x * 100)\n",
    "   return s\n",
    "\n",
    "y_format = tkr.FuncFormatter(func)\n",
    "ax1.yaxis.set_major_formatter(y_format)\n",
    "\n",
    "# arrows and annotation\n",
    "ax1.text(x=bike_share[bike_share['Member Type'] == 'Registered']['Distance by Ride Duration'].quantile(0.50) - 0.1,y=0.5,\\\n",
    "         s='Median: {:,.1f} miles'.format(bike_share[bike_share['Member Type'] == 'Registered']['Distance by Ride Duration'].quantile(0.50)), color='blue',\\\n",
    "         alpha=0.5, backgroundcolor='white', size=14, weight='bold')\n",
    "ax1.arrow(bike_share[bike_share['Member Type'] == 'Registered']['Distance by Ride Duration'].quantile(0.50), 0.49, 0,-0.055, head_width=0.07, head_length=0.015,\\\n",
    "          color='blue', alpha=0.5)\n",
    "\n",
    "ax1.text(x=bike_share[bike_share['Member Type'] == 'Casual']['Distance by Ride Duration'].quantile(0.50) - 0.1,y=0.28,\\\n",
    "         s='Median: {:,.1f} miles'.format(bike_share[bike_share['Member Type'] == 'Casual']['Distance by Ride Duration'].quantile(0.50)), color='green',\\\n",
    "         alpha=0.5, backgroundcolor='white', size=14, weight='bold')\n",
    "ax1.arrow(bike_share[bike_share['Member Type'] == 'Casual']['Distance by Ride Duration'].quantile(0.50), 0.27, 0,-0.035, head_width=0.07, head_length=0.015, \\\n",
    "          color='green', alpha=0.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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