Bikeshare Station Patterns

BikeshareStationPatterns.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 fivethirtyeight plot style\n",
    "plt.style.use('fivethirtyeight')"
   ]
  },
  {
   "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": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: convert_objects is deprecated.  Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.\n",
      "  from IPython.kernel.zmq import kernelapp as app\n"
     ]
    }
   ],
   "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": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: sort is deprecated, use sort_values(inplace=True) for for INPLACE sorting\n",
      "  from IPython.kernel.zmq import kernelapp as app\n",
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:3: FutureWarning: sort is deprecated, use sort_values(inplace=True) for for INPLACE sorting\n",
      "  app.launch_new_instance()\n",
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:4: FutureWarning: sort is deprecated, use sort_values(inplace=True) for for INPLACE sorting\n"
     ]
    }
   ],
   "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": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:6: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n"
     ]
    }
   ],
   "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": 19,
   "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": 20,
   "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": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
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ZZKKrxigwWNmaaeC7zGryDeeeHh/qr2ZaqJ6xwVpUisY/sGHeamZ1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\nuOOOO5AkiRkzZvDJJ5+4NFOVkblsRBHT7d/F57dORdvPbGPOmTbmnGm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ZGRn4+fmBeTW9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2A//gv2v42FahojUzwYuyn6oKYYG92G6nZ4BmNnnNlNgDUZg/JHg7H3487Zj+PYf0BvQR/W3rPG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\nBEEQBKFB+z9GP7vobirpMAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1b927748>"
      ]
     },
     "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": 22,
   "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": 23,
   "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": 24,
   "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": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:6: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n"
     ]
    }
   ],
   "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": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:6: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n"
     ]
    }
   ],
   "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": 27,
   "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": 28,
   "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": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  from IPython.kernel.zmq import kernelapp as app\n"
     ]
    },
    {
     "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": 29,
     "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": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  from IPython.kernel.zmq import kernelapp as app\n"
     ]
    },
    {
     "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": 30,
     "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": 31,
   "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": 32,
   "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": 33,
   "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": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1529c400>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4w7ozqecL4crVfE7rG2VjR16Ad3fAPJfK2/tyGdcitMxSF0L4h2IVwYcOHaJd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\nGyQFsBCXyd20Ne76TdEn7fHGTKv+jW3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bsNwQhY1JPfQ2HaF3jH2nkpFplgYGEKQT/Pjj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YPa4+7sBYCzszPh4eG0b9+ev/76iyNHjlg8Z+NiuRu/ZXTgz+yWhLqeJtQtAXubMgz58ZQenoLa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\nBALBW8f/A1fCH3/A65kZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d710470>"
      ]
     },
     "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": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0xc86e208>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SaTZWY8xdz111kglFv6fu6/EYWo1nT+28gvOs3LnouuMVpduZbefwBU+RfA3w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\ngUAgEDQK/wdlg4xHGQbiRQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x133c4da0>"
      ]
     },
     "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": 36,
   "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": 37,
   "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": 38,
   "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": 39,
   "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": 40,
   "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": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "station_location_df['End Station'] = station_location_df['Starting Station']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share = bike_share.merge(station_location_df, on='End Station')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "del bike_share['Starting Station_y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share = bike_share.merge(station_location_df, on='Starting Station')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "del bike_share['End Station_y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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": 48,
   "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": 49,
   "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": 50,
   "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": 51,
   "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": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share['Distance by Ride Duration']= ( bike_share['Minutes'] / 60 ) * 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x9df60b8>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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yMgBIS0ujtLSUiIiI5jwVEbmGJSQkEBoaClTdJv/4448ZP348b731FoGBgQwd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\nhBBCCCGa3jdlChhWavf1nwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c7a6d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"darkgrid\", {\"axes.facecolor\": \"0.94\"})\n",
    "\n",
    "plt.figure(figsize=(10,6))\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, 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, 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)\n",
    "\n",
    "ax1.text(0.95, -0.15, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", fontsize=12)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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": 54,
     "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": 55,
   "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": 55,
     "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": 56,
   "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": 57,
   "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": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# summary statistics for average speed\n",
    "bike_share['Average Speed'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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": 59,
   "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": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# add 'busy-ness' ratio\n",
    "map_df = map_df.join(df_busy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:1: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Distance by Lat/Long</th>\n",
       "      <th>Average Speed</th>\n",
       "      <th>Distance by Ride Duration</th>\n",
       "      <th>Lat (Start)</th>\n",
       "      <th>Long (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>0.698327</td>\n",
       "      <td>3.256164</td>\n",
       "      <td>6.121644</td>\n",
       "      <td>38.803124</td>\n",
       "      <td>-77.040363</td>\n",
       "      <td>36.729867</td>\n",
       "      <td>1.040941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47th &amp; Elm St</th>\n",
       "      <td>1.518164</td>\n",
       "      <td>5.980837</td>\n",
       "      <td>4.595000</td>\n",
       "      <td>38.982456</td>\n",
       "      <td>-77.091991</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>0.761952</td>\n",
       "      <td>3.352359</td>\n",
       "      <td>4.504944</td>\n",
       "      <td>38.854691</td>\n",
       "      <td>-77.100555</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>1.761135</td>\n",
       "      <td>6.784992</td>\n",
       "      <td>4.266744</td>\n",
       "      <td>38.964992</td>\n",
       "      <td>-77.103381</td>\n",
       "      <td>25.600467</td>\n",
       "      <td>0.510494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Memorial</th>\n",
       "      <td>1.120962</td>\n",
       "      <td>2.511495</td>\n",
       "      <td>4.254851</td>\n",
       "      <td>38.888251</td>\n",
       "      <td>-77.049426</td>\n",
       "      <td>25.529108</td>\n",
       "      <td>17.731523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Smithsonian / Jefferson Dr &amp; 12th St SW</th>\n",
       "      <td>0.824447</td>\n",
       "      <td>2.112316</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>38.888767</td>\n",
       "      <td>-77.028580</td>\n",
       "      <td>25.500000</td>\n",
       "      <td>8.483479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Randle Circle &amp; Minnesota Ave SE</th>\n",
       "      <td>1.383689</td>\n",
       "      <td>4.564116</td>\n",
       "      <td>4.125597</td>\n",
       "      <td>38.878000</td>\n",
       "      <td>-76.960700</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.123264</td>\n",
       "      <td>39.099376</td>\n",
       "      <td>-77.188014</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>0.819373</td>\n",
       "      <td>2.138904</td>\n",
       "      <td>4.121667</td>\n",
       "      <td>38.884120</td>\n",
       "      <td>-77.046570</td>\n",
       "      <td>24.730000</td>\n",
       "      <td>4.029880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jefferson Dr &amp; 14th St SW</th>\n",
       "      <td>0.821984</td>\n",
       "      <td>2.402684</td>\n",
       "      <td>3.833333</td>\n",
       "      <td>38.888553</td>\n",
       "      <td>-77.032429</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>14.682688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jefferson Memorial</th>\n",
       "      <td>1.119273</td>\n",
       "      <td>3.174741</td>\n",
       "      <td>3.810225</td>\n",
       "      <td>38.879819</td>\n",
       "      <td>-77.037413</td>\n",
       "      <td>22.861350</td>\n",
       "      <td>8.978131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34th &amp; Water St NW</th>\n",
       "      <td>1.289664</td>\n",
       "      <td>4.147182</td>\n",
       "      <td>3.767317</td>\n",
       "      <td>38.903582</td>\n",
       "      <td>-77.067786</td>\n",
       "      <td>22.603900</td>\n",
       "      <td>3.585950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shady Grove Hospital</th>\n",
       "      <td>0.231261</td>\n",
       "      <td>4.559129</td>\n",
       "      <td>3.733333</td>\n",
       "      <td>39.097636</td>\n",
       "      <td>-77.196636</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>1.871691</td>\n",
       "      <td>5.173468</td>\n",
       "      <td>3.728461</td>\n",
       "      <td>38.844400</td>\n",
       "      <td>-77.085931</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>1.077868</td>\n",
       "      <td>5.169456</td>\n",
       "      <td>3.671667</td>\n",
       "      <td>38.842320</td>\n",
       "      <td>-77.089555</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.577047</td>\n",
       "      <td>39.093783</td>\n",
       "      <td>-77.202501</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>2.459086</td>\n",
       "      <td>6.535476</td>\n",
       "      <td>3.564167</td>\n",
       "      <td>38.873057</td>\n",
       "      <td>-76.971015</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>1.001917</td>\n",
       "      <td>3.159242</td>\n",
       "      <td>3.511899</td>\n",
       "      <td>38.892459</td>\n",
       "      <td>-77.046567</td>\n",
       "      <td>21.071392</td>\n",
       "      <td>4.574502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19th St &amp; Constitution Ave NW</th>\n",
       "      <td>0.923744</td>\n",
       "      <td>2.933852</td>\n",
       "      <td>3.424931</td>\n",
       "      <td>38.892300</td>\n",
       "      <td>-77.043600</td>\n",
       "      <td>20.549583</td>\n",
       "      <td>2.792912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taft St &amp; E Gude Dr</th>\n",
       "      <td>1.253895</td>\n",
       "      <td>5.019259</td>\n",
       "      <td>3.414167</td>\n",
       "      <td>39.094103</td>\n",
       "      <td>-77.132954</td>\n",
       "      <td>20.485000</td>\n",
       "      <td>0.019941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fairfax Village</th>\n",
       "      <td>2.095602</td>\n",
       "      <td>7.074807</td>\n",
       "      <td>3.340894</td>\n",
       "      <td>38.865590</td>\n",
       "      <td>-76.952103</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>0.719052</td>\n",
       "      <td>3.294770</td>\n",
       "      <td>3.325000</td>\n",
       "      <td>38.878433</td>\n",
       "      <td>-77.030230</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>1.341264</td>\n",
       "      <td>4.483460</td>\n",
       "      <td>3.312500</td>\n",
       "      <td>38.867262</td>\n",
       "      <td>-77.072315</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>1.526713</td>\n",
       "      <td>4.641720</td>\n",
       "      <td>3.310000</td>\n",
       "      <td>38.856319</td>\n",
       "      <td>-77.111530</td>\n",
       "      <td>19.860000</td>\n",
       "      <td>0.256192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Harvard St &amp; Adams Mill Rd NW</th>\n",
       "      <td>1.566620</td>\n",
       "      <td>4.498810</td>\n",
       "      <td>3.286208</td>\n",
       "      <td>38.927872</td>\n",
       "      <td>-77.043358</td>\n",
       "      <td>19.717250</td>\n",
       "      <td>1.646213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S Kenmore &amp; 24th St S</th>\n",
       "      <td>1.648926</td>\n",
       "      <td>5.576033</td>\n",
       "      <td>3.279167</td>\n",
       "      <td>38.848454</td>\n",
       "      <td>-77.084918</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>1.181326</td>\n",
       "      <td>4.649790</td>\n",
       "      <td>3.273160</td>\n",
       "      <td>38.889920</td>\n",
       "      <td>-77.071301</td>\n",
       "      <td>19.638958</td>\n",
       "      <td>2.518307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Broschart &amp; Blackwell Rd</th>\n",
       "      <td>0.218899</td>\n",
       "      <td>0.489623</td>\n",
       "      <td>3.263126</td>\n",
       "      <td>39.102099</td>\n",
       "      <td>-77.200322</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>2.500499</td>\n",
       "      <td>7.526495</td>\n",
       "      <td>3.246667</td>\n",
       "      <td>38.933668</td>\n",
       "      <td>-76.991016</td>\n",
       "      <td>19.480000</td>\n",
       "      <td>0.710115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland &amp; Independence Ave SW</th>\n",
       "      <td>0.941325</td>\n",
       "      <td>3.377864</td>\n",
       "      <td>3.238333</td>\n",
       "      <td>38.887299</td>\n",
       "      <td>-77.018939</td>\n",
       "      <td>19.430000</td>\n",
       "      <td>4.211191</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>0.512190</td>\n",
       "      <td>6.060958</td>\n",
       "      <td>0.999467</td>\n",
       "      <td>38.990639</td>\n",
       "      <td>-77.100239</td>\n",
       "      <td>5.996800</td>\n",
       "      <td>0.431594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N Quincy St &amp; Wilson Blvd</th>\n",
       "      <td>0.575253</td>\n",
       "      <td>6.824854</td>\n",
       "      <td>0.996667</td>\n",
       "      <td>38.880151</td>\n",
       "      <td>-77.107673</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>0.578754</td>\n",
       "      <td>5.796089</td>\n",
       "      <td>0.993283</td>\n",
       "      <td>38.866120</td>\n",
       "      <td>-77.087870</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>0.833890</td>\n",
       "      <td>7.240274</td>\n",
       "      <td>0.981847</td>\n",
       "      <td>38.896923</td>\n",
       "      <td>-77.086502</td>\n",
       "      <td>5.891083</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson Blvd &amp; Franklin Rd</th>\n",
       "      <td>0.627848</td>\n",
       "      <td>7.024962</td>\n",
       "      <td>0.973653</td>\n",
       "      <td>38.890400</td>\n",
       "      <td>-77.088900</td>\n",
       "      <td>5.841917</td>\n",
       "      <td>1.911376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23rd &amp; Crystal Dr</th>\n",
       "      <td>0.642352</td>\n",
       "      <td>5.845530</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>38.853300</td>\n",
       "      <td>-77.049800</td>\n",
       "      <td>5.800000</td>\n",
       "      <td>1.646165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fairfax Dr &amp; Kenmore St</th>\n",
       "      <td>0.625195</td>\n",
       "      <td>6.827157</td>\n",
       "      <td>0.963333</td>\n",
       "      <td>38.884616</td>\n",
       "      <td>-77.101080</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>0.778661</td>\n",
       "      <td>8.167777</td>\n",
       "      <td>0.961667</td>\n",
       "      <td>38.985404</td>\n",
       "      <td>-77.023082</td>\n",
       "      <td>5.770000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Takoma Metro</th>\n",
       "      <td>0.588017</td>\n",
       "      <td>7.558499</td>\n",
       "      <td>0.930804</td>\n",
       "      <td>38.975219</td>\n",
       "      <td>-77.016855</td>\n",
       "      <td>5.584825</td>\n",
       "      <td>1.555640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27th &amp; Crystal Dr</th>\n",
       "      <td>0.595690</td>\n",
       "      <td>6.919161</td>\n",
       "      <td>0.914919</td>\n",
       "      <td>38.848441</td>\n",
       "      <td>-77.051516</td>\n",
       "      <td>5.489517</td>\n",
       "      <td>1.857957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ripley &amp; Bonifant St</th>\n",
       "      <td>0.392140</td>\n",
       "      <td>4.852867</td>\n",
       "      <td>0.913333</td>\n",
       "      <td>38.992679</td>\n",
       "      <td>-77.029457</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>0.547554</td>\n",
       "      <td>7.285029</td>\n",
       "      <td>0.901442</td>\n",
       "      <td>38.897274</td>\n",
       "      <td>-76.994749</td>\n",
       "      <td>5.408650</td>\n",
       "      <td>4.686435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>King Farm Blvd &amp; Pleasant Dr</th>\n",
       "      <td>0.454314</td>\n",
       "      <td>6.111884</td>\n",
       "      <td>0.891667</td>\n",
       "      <td>39.114688</td>\n",
       "      <td>-77.171487</td>\n",
       "      <td>5.350000</td>\n",
       "      <td>0.269170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bethesda Metro</th>\n",
       "      <td>0.512190</td>\n",
       "      <td>6.168125</td>\n",
       "      <td>0.883900</td>\n",
       "      <td>38.984691</td>\n",
       "      <td>-77.094537</td>\n",
       "      <td>5.303400</td>\n",
       "      <td>1.455420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philadelphia &amp; Maple Ave</th>\n",
       "      <td>0.512754</td>\n",
       "      <td>6.516146</td>\n",
       "      <td>0.880000</td>\n",
       "      <td>38.981280</td>\n",
       "      <td>-77.011336</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>0.505749</td>\n",
       "      <td>6.368970</td>\n",
       "      <td>0.873856</td>\n",
       "      <td>38.882788</td>\n",
       "      <td>-77.103148</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>0.458849</td>\n",
       "      <td>5.973294</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>38.820064</td>\n",
       "      <td>-77.057619</td>\n",
       "      <td>5.170000</td>\n",
       "      <td>0.887134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cordell &amp; Norfolk Ave</th>\n",
       "      <td>0.383710</td>\n",
       "      <td>5.862272</td>\n",
       "      <td>0.858061</td>\n",
       "      <td>38.989540</td>\n",
       "      <td>-77.098029</td>\n",
       "      <td>5.148367</td>\n",
       "      <td>0.790964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Congress Heights Metro</th>\n",
       "      <td>0.630407</td>\n",
       "      <td>7.619383</td>\n",
       "      <td>0.828333</td>\n",
       "      <td>38.844711</td>\n",
       "      <td>-76.987823</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>0.595690</td>\n",
       "      <td>6.741843</td>\n",
       "      <td>0.819771</td>\n",
       "      <td>38.857063</td>\n",
       "      <td>-77.051141</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>0.463603</td>\n",
       "      <td>6.738273</td>\n",
       "      <td>0.799358</td>\n",
       "      <td>38.891696</td>\n",
       "      <td>-77.084600</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>0.453992</td>\n",
       "      <td>6.520936</td>\n",
       "      <td>0.788139</td>\n",
       "      <td>38.893241</td>\n",
       "      <td>-77.086045</td>\n",
       "      <td>4.728833</td>\n",
       "      <td>1.335520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26th &amp; S Clark St</th>\n",
       "      <td>0.440665</td>\n",
       "      <td>6.422424</td>\n",
       "      <td>0.786667</td>\n",
       "      <td>38.850688</td>\n",
       "      <td>-77.051520</td>\n",
       "      <td>4.720000</td>\n",
       "      <td>1.013148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carroll &amp; Westmoreland Ave</th>\n",
       "      <td>0.325118</td>\n",
       "      <td>7.150856</td>\n",
       "      <td>0.785692</td>\n",
       "      <td>38.975000</td>\n",
       "      <td>-77.011210</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>0.588017</td>\n",
       "      <td>7.349650</td>\n",
       "      <td>0.778333</td>\n",
       "      <td>38.977933</td>\n",
       "      <td>-77.006472</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>0.381889</td>\n",
       "      <td>6.150740</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>38.895930</td>\n",
       "      <td>-77.089006</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>1.034375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anacostia Metro</th>\n",
       "      <td>0.480977</td>\n",
       "      <td>6.790037</td>\n",
       "      <td>0.723511</td>\n",
       "      <td>38.862669</td>\n",
       "      <td>-76.994637</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>0.325465</td>\n",
       "      <td>6.238947</td>\n",
       "      <td>0.711503</td>\n",
       "      <td>38.988562</td>\n",
       "      <td>-77.096539</td>\n",
       "      <td>4.269017</td>\n",
       "      <td>0.548455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aurora Hills Community Ctr/18th &amp; Hayes St</th>\n",
       "      <td>0.307312</td>\n",
       "      <td>7.107053</td>\n",
       "      <td>0.571667</td>\n",
       "      <td>38.857866</td>\n",
       "      <td>-77.059490</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>0.261453</td>\n",
       "      <td>6.867880</td>\n",
       "      <td>0.386667</td>\n",
       "      <td>38.863897</td>\n",
       "      <td>-76.990037</td>\n",
       "      <td>2.320000</td>\n",
       "      <td>0.322397</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>350 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    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",
       "                                                    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 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)  Long (Start)  \\\n",
       "Starting Station                                                                \n",
       "Prince St & Union St                                  38.803124    -77.040363   \n",
       "47th & Elm St                                         38.982456    -77.091991   \n",
       "S George Mason Dr & 13th St S                         38.854691    -77.100555   \n",
       "River Rd & Landy Ln                                   38.964992    -77.103381   \n",
       "Lincoln Memorial                                      38.888251    -77.049426   \n",
       "Smithsonian / Jefferson Dr & 12th St SW               38.888767    -77.028580   \n",
       "Randle Circle & Minnesota Ave SE                      38.878000    -76.960700   \n",
       "Fallsgrove Dr & W Montgomery Ave                      39.099376    -77.188014   \n",
       "Ohio Dr & West Basin Dr SW / MLK & FDR Memorials      38.884120    -77.046570   \n",
       "Jefferson Dr & 14th St SW                             38.888553    -77.032429   \n",
       "Jefferson Memorial                                    38.879819    -77.037413   \n",
       "34th & Water St NW                                    38.903582    -77.067786   \n",
       "Shady Grove Hospital                                  39.097636    -77.196636   \n",
       "S Four Mile Run Dr & S Shirlington Rd                 38.844400    -77.085931   \n",
       "S Arlington Mill Dr & Campbell Ave                    38.842320    -77.089555   \n",
       "Traville Gateway Dr & Gudelsky Dr                     39.093783    -77.202501   \n",
       "Pennsylvania & Minnesota Ave SE                       38.873057    -76.971015   \n",
       "21st St & Constitution Ave NW                         38.892459    -77.046567   \n",
       "19th St & Constitution Ave NW                         38.892300    -77.043600   \n",
       "Taft St & E Gude Dr                                   39.094103    -77.132954   \n",
       "Fairfax Village                                       38.865590    -76.952103   \n",
       "Hains Point/Buckeye & Ohio Dr SW                      38.878433    -77.030230   \n",
       "Columbia Pike & S Orme St                             38.867262    -77.072315   \n",
       "Columbia Pike & S Dinwiddie St / Arlington Mill...    38.856319    -77.111530   \n",
       "Harvard St & Adams Mill Rd NW                         38.927872    -77.043358   \n",
       "S Kenmore & 24th St S                                 38.848454    -77.084918   \n",
       "Iwo Jima Memorial/N Meade & 14th St N                 38.889920    -77.071301   \n",
       "Broschart & Blackwell Rd                              39.102099    -77.200322   \n",
       "12th & Newton St NE                                   38.933668    -76.991016   \n",
       "Maryland & Independence Ave SW                        38.887299    -77.018939   \n",
       "...                                                         ...           ...   \n",
       "Norfolk & Rugby Ave                                   38.990639    -77.100239   \n",
       "N Quincy St & Wilson Blvd                             38.880151    -77.107673   \n",
       "S Walter Reed Dr & 8th St S                           38.866120    -77.087870   \n",
       "N Veitch  & 20th St N                                 38.896923    -77.086502   \n",
       "Wilson Blvd & Franklin Rd                             38.890400    -77.088900   \n",
       "23rd & Crystal Dr                                     38.853300    -77.049800   \n",
       "Fairfax Dr & Kenmore St                               38.884616    -77.101080   \n",
       "Fenton St & New York Ave                              38.985404    -77.023082   \n",
       "Takoma Metro                                          38.975219    -77.016855   \n",
       "27th & Crystal Dr                                     38.848441    -77.051516   \n",
       "Ripley & Bonifant St                                  38.992679    -77.029457   \n",
       "8th & F St NE                                         38.897274    -76.994749   \n",
       "King Farm Blvd & Pleasant Dr                          39.114688    -77.171487   \n",
       "Bethesda Metro                                        38.984691    -77.094537   \n",
       "Philadelphia & Maple Ave                              38.981280    -77.011336   \n",
       "Virginia Square Metro / N Monroe St & 9th St N        38.882788    -77.103148   \n",
       "Mount Vernon Ave & E Nelson Ave                       38.820064    -77.057619   \n",
       "Cordell & Norfolk Ave                                 38.989540    -77.098029   \n",
       "Congress Heights Metro                                38.844711    -76.987823   \n",
       "Crystal City Metro / 18th & Bell St                   38.857063    -77.051141   \n",
       "Wilson Blvd & N Uhle St                               38.891696    -77.084600   \n",
       "N Veitch & Key Blvd                                   38.893241    -77.086045   \n",
       "26th & S Clark St                                     38.850688    -77.051520   \n",
       "Carroll & Westmoreland Ave                            38.975000    -77.011210   \n",
       "Carroll & Ethan Allen Ave                             38.977933    -77.006472   \n",
       "N Adams St & Lee Hwy                                  38.895930    -77.089006   \n",
       "Anacostia Metro                                       38.862669    -76.994637   \n",
       "Norfolk Ave & Fairmont St                             38.988562    -77.096539   \n",
       "Aurora Hills Community Ctr/18th & Hayes St            38.857866    -77.059490   \n",
       "Pleasant St & MLK Ave SE                              38.863897    -76.990037   \n",
       "\n",
       "                                                      Minutes    Busiest  \n",
       "Starting Station                                                          \n",
       "Prince St & Union St                                36.729867   1.040941  \n",
       "47th & Elm St                                       27.570000   0.413278  \n",
       "S George Mason Dr & 13th St S                       27.029667   0.064692  \n",
       "River Rd & Landy Ln                                 25.600467   0.510494  \n",
       "Lincoln Memorial                                    25.529108  17.731523  \n",
       "Smithsonian / Jefferson Dr & 12th St SW             25.500000   8.483479  \n",
       "Randle Circle & Minnesota Ave SE                    24.753583   0.026617  \n",
       "Fallsgrove Dr & W Montgomery Ave                    24.739583   0.052032  \n",
       "Ohio Dr & West Basin Dr SW / MLK & FDR Memorials    24.730000   4.029880  \n",
       "Jefferson Dr & 14th St SW                           23.000000  14.682688  \n",
       "Jefferson Memorial                                  22.861350   8.978131  \n",
       "34th & Water St NW                                  22.603900   3.585950  \n",
       "Shady Grove Hospital                                22.400000   0.007632  \n",
       "S Four Mile Run Dr & S Shirlington Rd               22.370767   0.390897  \n",
       "S Arlington Mill Dr & Campbell Ave                  22.030000   0.834542  \n",
       "Traville Gateway Dr & Gudelsky Dr                   21.462283   0.036986  \n",
       "Pennsylvania & Minnesota Ave SE                     21.385000   0.371132  \n",
       "21st St & Constitution Ave NW                       21.071392   4.574502  \n",
       "19th St & Constitution Ave NW                       20.549583   2.792912  \n",
       "Taft St & E Gude Dr                                 20.485000   0.019941  \n",
       "Fairfax Village                                     20.045367   0.023073  \n",
       "Hains Point/Buckeye & Ohio Dr SW                    19.950000   1.747534  \n",
       "Columbia Pike & S Orme St                           19.875000   0.661972  \n",
       "Columbia Pike & S Dinwiddie St / Arlington Mill...  19.860000   0.256192  \n",
       "Harvard St & Adams Mill Rd NW                       19.717250   1.646213  \n",
       "S Kenmore & 24th St S                               19.675000   0.124107  \n",
       "Iwo Jima Memorial/N Meade & 14th St N               19.638958   2.518307  \n",
       "Broschart & Blackwell Rd                            19.578758   0.011390  \n",
       "12th & Newton St NE                                 19.480000   0.710115  \n",
       "Maryland & Independence Ave SW                      19.430000   4.211191  \n",
       "...                                                       ...        ...  \n",
       "Norfolk & Rugby Ave                                  5.996800   0.431594  \n",
       "N Quincy St & Wilson Blvd                            5.980000   1.771467  \n",
       "S Walter Reed Dr & 8th St S                          5.959700   0.307692  \n",
       "N Veitch  & 20th St N                                5.891083        NaN  \n",
       "Wilson Blvd & Franklin Rd                            5.841917   1.911376  \n",
       "23rd & Crystal Dr                                    5.800000   1.646165  \n",
       "Fairfax Dr & Kenmore St                              5.780000   1.157219  \n",
       "Fenton St & New York Ave                             5.770000        NaN  \n",
       "Takoma Metro                                         5.584825   1.555640  \n",
       "27th & Crystal Dr                                    5.489517   1.857957  \n",
       "Ripley & Bonifant St                                 5.480000   0.238411  \n",
       "8th & F St NE                                        5.408650   4.686435  \n",
       "King Farm Blvd & Pleasant Dr                         5.350000   0.269170  \n",
       "Bethesda Metro                                       5.303400   1.455420  \n",
       "Philadelphia & Maple Ave                             5.280000   0.516839  \n",
       "Virginia Square Metro / N Monroe St & 9th St N       5.243133   1.856458  \n",
       "Mount Vernon Ave & E Nelson Ave                      5.170000   0.887134  \n",
       "Cordell & Norfolk Ave                                5.148367   0.790964  \n",
       "Congress Heights Metro                               4.970000   0.079192  \n",
       "Crystal City Metro / 18th & Bell St                  4.918625   2.771844  \n",
       "Wilson Blvd & N Uhle St                              4.796150   2.059392  \n",
       "N Veitch & Key Blvd                                  4.728833   1.335520  \n",
       "26th & S Clark St                                    4.720000   1.013148  \n",
       "Carroll & Westmoreland Ave                           4.714150   0.555947  \n",
       "Carroll & Ethan Allen Ave                            4.670000   0.844495  \n",
       "N Adams St & Lee Hwy                                 4.500000   1.034375  \n",
       "Anacostia Metro                                      4.341067   0.799523  \n",
       "Norfolk Ave & Fairmont St                            4.269017   0.548455  \n",
       "Aurora Hills Community Ctr/18th & Hayes St           3.430000   1.239268  \n",
       "Pleasant St & MLK Ave SE                             2.320000   0.322397  \n",
       "\n",
       "[350 rows x 7 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "map_df.sort('Minutes',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2873"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(bike_share[bike_share['Starting Station'] == 'Prince St & Union St'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.FancyArrow at 0xc0f5da0>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2cXFxHDlyBA8PD/0xjUZj0B/p4OCg//1e+Tx37hxt2rQxeK1Dhw76IHUntVpNcRmTZIuL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\nAHIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xabc2cc0>"
      ]
     },
     "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": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1bbd6048>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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580yfPr2qYxRCCCEqzT1vWXbr1i3q1atX2fE8dGTLMiGEeLSY/JMzMTGRadOm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\nEEI0K5L4hBBCNCuS+IQQQjQr/wcn+7hgw0AnsAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xa1e84e0>"
      ]
     },
     "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": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.FancyArrow at 0x12c36b70>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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gdA4bjUZ8fX0ZN24cZ86csSiflpaGi4tLsecKDg5m0qRJXL9+nfj4eLp27Woe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\nEwRBELSKKHyCIAiCVvkfcTQoGPPBnWQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1356c390>"
      ]
     },
     "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)"
   ]
  }
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