Bikeshare System Data Part 1 (The Rider)

Bikeshare1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# import modules\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as tkr\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from datetime import datetime, timedelta\n",
    "import seaborn as sns\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "# use fivethirtyeight plot style\n",
    "plt.style.use('fivethirtyeight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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": 46,
   "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(year,quarter) \n",
    "        frame = pd.read_csv(path, names = headers, header = 0, low_memory = False)        \n",
    "        tmp_lst.append(frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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": 48,
   "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": 49,
   "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": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share['Minutes'] = bike_share.Minutes.astype('float64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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": 52,
   "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": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# new dataframe groups data in a more useable format (by bike number) and aggregates the desired data (e.g., total minutes by bike number)\n",
    "bikes_by_number = bike_share.groupby(\"Bike\").agg({'Start Date': min, 'End Date': max, 'Minutes':[sum, np.mean, np.size]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# groups all bike data by 'Member Type'\n",
    "all_bikes_mt = bike_share.groupby(\"Member Type\").agg({'Minutes':[sum, np.mean, np.size]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bike_share_hist = pd.DataFrame({'Minutes': bike_share.Minutes, 'Member Type': bike_share['Member Type']}).dropna(how='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# adds separate 'Casual' and 'Registered' columns to data frame \n",
    "bike_share_hist['Casual'] =  bike_share_hist.groupby('Member Type').get_group('Casual')['Minutes']; \n",
    "bike_share_hist['Registered'] =  bike_share_hist.groupby('Member Type').get_group('Registered')['Minutes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# calculates median ride length for inclusion in histogram annotation\n",
    "bike_share_casual_median_ride_length = bike_share_hist['Casual'].median() \n",
    "bike_share_registered_median_ride_length = bike_share_hist['Registered'].median() \n",
    "\n",
    "bike_share_casual_median_ride_length = bike_share_hist['Casual'].median() \n",
    "bike_share_registered_median_ride_length = bike_share_hist['Registered'].median() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30min quantile: Casual(30.0), Registered(30.0), Combined(30.0).\n"
     ]
    }
   ],
   "source": [
    "thirty_min_quantile_bike_share_casual_median_ride_length = bike_share_hist['Casual'].quantile(q=.6448) \n",
    "thirty_min_quantile_bike_share_registered_median_ride_length = bike_share_hist['Registered'].quantile(q=.9757)  \n",
    "thirty_min_quantile_bike_share_median_ride_length = bike_share['Minutes'].quantile(q=.906)  \n",
    "\n",
    "print(\"30min quantile: Casual({}), Registered({}), Combined({}).\".format(thirty_min_quantile_bike_share_casual_median_ride_length,\n",
    "                                                                     thirty_min_quantile_bike_share_registered_median_ride_length, \n",
    "                                                                     thirty_min_quantile_bike_share_median_ride_length))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# delete unnecessary columns in dataframes \n",
    "del bike_share_hist['Member Type'],bike_share_hist['Minutes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0xaaa2e48>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
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FahERERERGyhQi4iIiIjYoFEC9f79+/nrX/9Kly5d6NevHx988IHRlpOTw7hx4+jcuTMD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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcf17a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot histogram of casual/registered member type trip length \n",
    "\n",
    "# formatter function to format y-axis labels to have a comma at the thousands place \n",
    "def func(x, pos):  \n",
    "   s = '{:0,d}'.format(int(x))\n",
    "   return s\n",
    "\n",
    "plt.subplot(1,1,1)\n",
    "\n",
    "ax2 = bike_share_hist['Registered'].hist(alpha=1, grid=False, bins=25, range=[0,50], figsize=(10,6), stacked=True)\n",
    "ax2.text(x=15,y=270000,s='Registered Member / Median Ride Length: {:.1f} mins'.format(bike_share_registered_median_ride_length))\n",
    "ax2.arrow(15, 265000, -4, -20000, head_width=0.05, head_length=0.1, fc='k', ec='k')\n",
    "\n",
    "ax1 = bike_share_hist['Casual'].hist(alpha=0.6, grid = False, bins=25, range=[0,50], figsize=(10,6), stacked=True)\n",
    "ax1.set_xlabel('Ride Length (Minutes)', fontsize=14)\n",
    "ax1.set_ylabel('Rides')\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",
    "y_format = tkr.FuncFormatter(func)  # make formatter\n",
    "ax1.yaxis.set_major_formatter(y_format)\n",
    "ax1.text(x=20,y=100000,s='Casual Member / Median Ride Length: {:.1f} mins'.format(bike_share_casual_median_ride_length))\n",
    "ax1.arrow(35, 90000, -5, -65000, head_width=0.05, head_length=0.1, fc='k', ec='k')\n",
    "\n",
    "plt.xticks(fontsize=14)\n",
    "plt.yticks(fontsize=14)\n",
    "\n",
    "ax1.text(0.13, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
    "          fontsize=12, transform=ax1.transAxes) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# add 'Start Date' column to bike_share_hist dataframe to calculate data by month\n",
    "bike_share_hist['Start Date'] = bike_share['Start Date']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# create dataframe of only casual riders\n",
    "bike_share_casual_minutes = bike_share_hist.set_index('Start Date'); del bike_share_casual_minutes['Registered']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# create dataframe of only registered riders\n",
    "bike_share_registered_minutes = bike_share_hist.set_index('Start Date'); del bike_share_registered_minutes['Casual']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# resample all data by average ride length in minutes\n",
    "bike_share_casual_minutes_monthly_avg = bike_share_casual_minutes.resample('M')\n",
    "bike_share_registered_minutes_monthly_avg = bike_share_registered_minutes.resample('M')\n",
    "bike_share_monthly_minutes_avg =  bike_share_hist.set_index('Start Date').resample('M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# resample all data by number of rides\n",
    "bike_share_casual_minutes_monthly_count = bike_share_casual_minutes.resample('M', how='count')\n",
    "bike_share_registered_minutes_monthly_count = bike_share_registered_minutes.resample('M', how='count')\n",
    "bike_share_monthly_minutes_count =  bike_share_hist.set_index('Start Date').resample('M', how='count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# resample all data by median ride length\n",
    "bike_share_casual_minutes_monthly_median = bike_share_casual_minutes.resample('M', how='median')\n",
    "bike_share_registered_minutes_monthly_median = bike_share_registered_minutes.resample('M', how='median')\n",
    "bike_share_monthly_minutes_median =  bike_share_hist.set_index('Start Date').resample('M', how='median')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# resample all data by total ride length in minutes\n",
    "bike_share_casual_minutes_monthly = bike_share_casual_minutes.resample('M',how='sum')\n",
    "bike_share_registered_minutes_monthly = bike_share_registered_minutes.resample('M',how='sum')\n",
    "bike_share_monthly_minutes =  bike_share_hist.set_index('Start Date').resample('M',how='sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of rides: 2946921 (Casual: 620706, Registered 2326215).\n"
     ]
    }
   ],
   "source": [
    "# general annual system stats (number of rides)\n",
    "total_rides_count = bike_share['Minutes'].count()\n",
    "casual_rides_count = bike_share[bike_share['Member Type'] == 'Casual']['Minutes'].count() \n",
    "registered_rides_count = bike_share[bike_share['Member Type'] == 'Registered']['Minutes'].count() \n",
    "\n",
    "print(\"Total number of rides: {} (Casual: {}, Registered {}).\".format(total_rides_count, \n",
    "                                                                      casual_rides_count,\n",
    "                                                                      registered_rides_count))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of minutes: 50401729.60999889 (Casual: 23722090.959999133, Registered 26679638.650001545).\n"
     ]
    }
   ],
   "source": [
    "# general annual system stats (total minutes)\n",
    "total_rides_minutes = bike_share['Minutes'].sum()\n",
    "casual_rides_minutes = bike_share[bike_share['Member Type'] == 'Casual']['Minutes'].sum() \n",
    "registered_rides_minutes = bike_share[bike_share['Member Type'] == 'Registered']['Minutes'].sum() \n",
    "\n",
    "print(\"Total number of minutes: {} (Casual: {}, Registered {}).\".format(total_rides_minutes, \n",
    "                                                                        casual_rides_minutes, \n",
    "                                                                        registered_rides_minutes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Avg minutes per ride: 17.103183156249823 (Casual: 38.21791791927117, Registered 11.469119857795407).\n"
     ]
    }
   ],
   "source": [
    "# general annual system stats (avg minutes)\n",
    "total_rides_avg_minutes = bike_share['Minutes'].mean()\n",
    "casual_rides_avg_minutes = bike_share[bike_share['Member Type'] == 'Casual']['Minutes'].mean() \n",
    "registered_rides_avg_minutes = bike_share[bike_share['Member Type'] == 'Registered']['Minutes'].mean() \n",
    "\n",
    "print(\"Avg minutes per ride: {} (Casual: {}, Registered {}).\".format(total_rides_avg_minutes,\n",
    "                                                                     casual_rides_avg_minutes, \n",
    "                                                                     registered_rides_avg_minutes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median minutes per ride: 10.77 (Casual: 23.42, Registered 9.1).\n"
     ]
    }
   ],
   "source": [
    "# general annual system stats (median minutes)\n",
    "total_rides_median_minutes = bike_share['Minutes'].median()\n",
    "casual_rides_median_minutes = bike_share[bike_share['Member Type'] == 'Casual']['Minutes'].median() \n",
    "registered_rides_median_minutes = bike_share[bike_share['Member Type'] == 'Registered']['Minutes'].median() \n",
    "\n",
    "print(\"Median minutes per ride: {} (Casual: {}, Registered {}).\".format(total_rides_median_minutes,\n",
    "                                                                     casual_rides_median_minutes, \n",
    "                                                                     registered_rides_median_minutes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rides with zero minutes: 8211 (Casual: 3, Registered 8208).\n"
     ]
    }
   ],
   "source": [
    "# number of rides with zero minutes\n",
    "total_rides_zero_minutes = bike_share[bike_share['Minutes'] < 0.1]['Minutes'].count()\n",
    "casual_rides_zero_minutes = bike_share[(bike_share['Member Type'] == 'Casual') & \n",
    "                                       (bike_share['Minutes'] < 0.1) ]['Minutes'].count() \n",
    "registered_rides_zero_minutes = bike_share[(bike_share['Member Type'] == 'Registered') & \n",
    "                                       (bike_share['Minutes'] < 0.1) ]['Minutes'].count()  \n",
    "\n",
    "print(\"Rides with zero minutes: {} (Casual: {}, Registered {}).\".format(total_rides_zero_minutes,\n",
    "                                                                     casual_rides_zero_minutes, \n",
    "                                                                     registered_rides_zero_minutes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8329, 95800)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# min/max ride numbers by month\n",
    "bike_share_monthly_minutes_count['Registered'].min(),bike_share_monthly_minutes_count['Registered'].max()\n",
    "bike_share_monthly_minutes_count['Casual'].min(),bike_share_monthly_minutes_count['Casual'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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"
     ]
    }
   ],
   "source": [
    "# new dataframe of 100 longest rides\n",
    "sorted_by_longest_ride = bike_share.sort('Minutes', ascending=False)[0:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Longest rides stats: \n",
      " Sum Member Type\n",
      "Casual        108089.03\n",
      "Registered     30152.00\n",
      "Name: Minutes, dtype: float64, \n",
      " Count: Member Type\n",
      "Casual        78\n",
      "Registered    22\n",
      "Name: Minutes, dtype: int64, \n",
      " Mean Member Type\n",
      "Casual        1385.756795\n",
      "Registered    1370.545455\n",
      "Name: Minutes, dtype: float64, \n",
      " Median: Member Type\n",
      "Casual        1388.260\n",
      "Registered    1367.925\n",
      "Name: Minutes, dtype: float64).\n"
     ]
    }
   ],
   "source": [
    "# longest ride stats by Member Type\n",
    "member_type_longest_ride_sum = sorted_by_longest_ride.groupby('Member Type')['Minutes'].sum()\n",
    "member_type_longest_ride_count = sorted_by_longest_ride.groupby('Member Type')['Minutes'].count()\n",
    "member_type_longest_ride_mean = sorted_by_longest_ride.groupby('Member Type')['Minutes'].mean()\n",
    "member_type_longest_ride_median = sorted_by_longest_ride.groupby('Member Type')['Minutes'].median()\n",
    "\n",
    "\n",
    "print(\"Longest rides stats: \\n Sum {}, \\n Count: {}, \\n Mean {}, \\n Median: {}).\".format(member_type_longest_ride_sum, \n",
    "                                                                             member_type_longest_ride_count, \n",
    "                                                                             member_type_longest_ride_mean, \n",
    "                                                                             member_type_longest_ride_median))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Longest rides stats: sum 138241.02999999997, count: 100, mean: 1382.4102999999998, median: 1386.34).\n"
     ]
    }
   ],
   "source": [
    "# key statistics for longest rides\n",
    "total_longest_ride_sum = sorted_by_longest_ride['Minutes'].sum()\n",
    "total_longest_ride_count = sorted_by_longest_ride['Minutes'].count()\n",
    "total_longest_ride_mean = sorted_by_longest_ride['Minutes'].mean()\n",
    "total_longest_ride_median = sorted_by_longest_ride['Minutes'].median()\n",
    "\n",
    "print(\"Longest rides stats: sum {}, count: {}, mean: {}, median: {}).\".format(total_longest_ride_sum, \n",
    "                                                                             total_longest_ride_count, \n",
    "                                                                             total_longest_ride_mean, \n",
    "                                                                             total_longest_ride_median))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Standard deviation of ride length: 29.9747147221765 (Casual: 50.66318440236662, Registered 17.39634245187136).\n"
     ]
    }
   ],
   "source": [
    "# general annual system stats (std dev minutes)\n",
    "total_rides_avg_minutes_std = bike_share['Minutes'].std()\n",
    "casual_rides_avg_minutes_std = bike_share[bike_share['Member Type'] == 'Casual']['Minutes'].std() \n",
    "registered_rides_avg_minutes_std = bike_share[bike_share['Member Type'] == 'Registered']['Minutes'].std() \n",
    "\n",
    "print(\"Standard deviation of ride length: {} (Casual: {}, Registered {}).\".format(total_rides_avg_minutes_std,\n",
    "                                                                     casual_rides_avg_minutes_std, \n",
    "                                                                     registered_rides_avg_minutes_std))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rides with zero minutes: 32328 (Casual: 48, Registered 32280).\n"
     ]
    }
   ],
   "source": [
    "# number of rides with zero minutes\n",
    "total_rides_zero_minutes = bike_share[bike_share['Minutes'] <= 1]['Minutes'].count()\n",
    "casual_rides_zero_minutes = bike_share[(bike_share['Member Type'] == 'Casual') & \n",
    "                                       (bike_share['Minutes'] <= 1) ]['Minutes'].count() \n",
    "registered_rides_zero_minutes = bike_share[(bike_share['Member Type'] == 'Registered') & \n",
    "                                       (bike_share['Minutes'] <= 1) ]['Minutes'].count()  \n",
    "\n",
    "print(\"Rides with zero minutes: {} (Casual: {}, Registered {}).\".format(total_rides_zero_minutes,\n",
    "                                                                     casual_rides_zero_minutes, \n",
    "                                                                     registered_rides_zero_minutes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x9de2898>"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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uri5cuKCGDRtWeO7+/fut7kK7u7srKChI+/btK9c3OztbWVlZVv1DQkKUlZWl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      "text/plain": [
       "<matplotlib.figure.Figure at 0xa8cbda0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot histogram of casual/registered member type trip length \n",
    "\n",
    "# formatter function to format y-axis labels to have a comma at the thousands place \n",
    "def func(x, pos):  \n",
    "    s = '{:0,.1f}'.format(int(x)/1000)\n",
    "    return s\n",
    "\n",
    "plt.subplot(1,1,1)\n",
    "ax2 = bike_share_hist['Registered'].hist(grid=False, bins=25, range=[0,50], figsize=(10,6), stacked=True)\n",
    "ax2.text(x=bike_share_registered_median_ride_length+5,y=340000,s='Registered: {:.1f} mins'.\n",
    "         format(bike_share_registered_median_ride_length),fontsize=14)\n",
    "ax2.arrow(13, 350000, -4, 0, head_width=14000, head_length=1, fc='k', ec='k')\n",
    "\n",
    "\n",
    "ax1 = bike_share_hist['Casual'].hist(grid = False, bins=25, range=[0,50], figsize=(10,6), stacked=True, alpha=0.7)\n",
    "ax1.set_xlabel('Ride Duration (Minutes)', fontsize=14)\n",
    "ax1.set_ylabel('Rides (thousands)', 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",
    "y_format = tkr.FuncFormatter(func)  # make formatter\n",
    "ax1.yaxis.set_major_formatter(y_format)\n",
    "ax1.text(x=bike_share_casual_median_ride_length,y=60000,s='Casual: {:.1f} mins'.format(bike_share_casual_median_ride_length),\n",
    "         fontsize=14)\n",
    "ax1.arrow(30, 45000, -10, 0, head_width=14000, head_length=1, fc='k', ec='k')\n",
    "\n",
    "plt.xticks(fontsize=14)\n",
    "plt.yticks(fontsize=14)\n",
    "\n",
    "ax1.text(0.13, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
    "          fontsize=12, transform=ax1.transAxes) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0xa8cbe80>"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\matplotlib\\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  if self._edgecolors == str('face'):\n"
     ]
    },
    {
     "data": {
      "image/png": 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XB6q3C5Uexert9q8EVNX433tRHgH/sJ/V140aSaLSo9DXjWqePeV65ybzmjWJ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BVxXHqfh9w9X6AEg1gr9qBTg6GA24Yb2IUQQoiWQNPrcR+ZdSE0utvYu6th9DhIP7iLgMmMKzkD\nRdNIP/gNaWVFOFOzqc/siCcpLdqb0CQk5IpjKMEgucVfYPB5SK7aj9HrCk0VlpaLPz4x2uUJIYQQ\n4jR9O7obwOysC4/u6o6M7ibVVOBNSDoyuntkpgZzIvbMDjSkt2vRc+BLyBWRNI3skm3EuepJqDtM\nvKMGVW/AlZzRar7ZCSGEEG2NpjccNbrrIL6hljiXHdAwuR1kOHYRMMXjSgmN7mYc2EX6wUIcaTnY\nMzq0yAwgIVdESC/bjaWukjhnPUm2clSDAV98Ek5rdrRLE0IIIUQT8JsT8ZsTUYKB8FXUUBR0aoCk\n6oMk2crxHundTbKVkWQrwxefhD2jAw3pZ7WY0V0JuSIsqeoA1kN70fs8WCtLUA0GAkYz9oz2MXPm\npRBCCCGahqY34E7JDPfuxjtqiHM1EBrdbSDDUXtkdDfzyOhuAellu3Gk5mLP7IAnMTXam3BSEnIF\nAPF2G5n7v0YJBkkvK0TV6VH1htBMCjp9tMsTQgghxJmiKPjjE/HHh0Z34x21mI8a3U2uPkCSrQxP\nQgrOtFySbAdJsh3EF59EfWZHHGlnoRqM0d6KY0jIFRg9TnL2bkWnBkkrLwIldFWV+sy8mHzSCiGE\nEOLM0PQGXCmZuI4zumt21xO/v4aAKR5nSiZoGpn7vybj4Dc0pOViz+iIN9Ea7U0Ik5DbxukCPnKL\nP0cX8JNyqAS934um12PPaEcgrmknZRZCCCFEC3HU6K4u4D9yVbVa9IoPnRogpeoAybYyPJYUHKm5\nJFcfJLn6IN6EZOwZHWJidFdCblumquTs+RKjx0mirRyT246mN+C0ZuNLSIl2dUIIIYSIAarBGB7d\nNXkcmBtqiXMfGd111RPfUEMgLh5nSlZodNdlPzK6exb2zA54LdEZ3ZWQ24Zl7t9JfIMNc0MNlrpK\nVIMRj8WKKyUz2qUJIYQQItYoCr74JHzxSaHR3SMzM+gUP7pggJTD+0m2HcSTYMWRlkNy9QGSqw/g\nTUgJzbubdlazXjFVQm4bZa3YQ3L1QYweFymH96EajPjjLDSkt4t2aUIIIYSIcarBiMuahSslE5Pb\nQbyjBpO7AQCzq474BhuBuISjRnfrST/4DY60s7BntG+W0V0JuW2QpfYQ6WW70fl9pJYXoRqMBA0m\n6jM7yFRhQgghhDh9ioIvIQlfwvFGd/2kHN5Hsu3At6O7VftJrtrfLKO7EnLbmDhnHdklX6GoKunl\nhWg6XWgmhay8Zj2EIIQQQojWJXJ0t4F4R+0xo7v+uASc1izQCI/uhnp3OwJNe8K7pJo2RO/zkFu8\nFSUYJLWiGEVVj0wV1oGgMS7a5QkhhBCiNVAUfAnJ+BKS0QV8R+bdrUOn+NEH/VgrS1H1B/EemZkh\npWo/KVX7ofs1TVpGs4dcn8/HnDlzWLduHUajkZEjRzJq1Kjjrjt27Fg2b94csWz27Nn07du3OUpt\nVZRggNziz9H7PSRX7cPgdaPp9TSk5eI3J0a7PCGEEEK0QqrBhNOajTMl69jRXUcd8XYb/jhLaHS3\niTV7yH366afZuXMn8+bNo7KykqlTp5KTk8OgQYOOWbekpIRHH32UCy+8MLwsKSmpOcttHTSN7JKv\niHPZsdQdJt5Rg6o34krOwJOUFu3qhBBCCNHaHXd0txZdMIA+6MNaWdLkD9msIdftdvP2228zd+5c\nzjvvPM477zxGjRrFq6++ekzIdTgcVFVV0aNHD9LSJIj9GOkHv8FSV0mcs57EmjJUvRFvfDJOa3a0\nSxNCCCFEGxM5umsnvqEWk8fR5I+ja/J7PImioiL8fj+9evUKL+vZsye7du1C07SIdUtKSjCZTGRn\nSxD7MZKr9mOtLEHvdWOtLEHVGwmYzNgz2stMCkIIIYSIHkXBl5BCfXYnbO3ObfK7b9aQW11dTXJy\nMkbjt5d5S0tLw+/3U1NTE7FuSUkJSUlJ/PWvf+XXv/41t9xyC5999llzltvixdurydhfgBIMkl5R\nhKrTo+qN1Gfmga5Zd70QQgghxAmpBlOT32ezJh2Px4PJFLkRjb/7/f6I5aWlpXg8Hvr168fTTz/N\nJZdcwj333MPXX3/dbPW2ZEa3g5w9X6JTg6SV7QY4MpNCx6hfS1oIIYQQ4kxr1p5ck8mEz+eLWNb4\nu9lsjlg+duxYbrvtNhISEgA455xz+Oabb1i5ciU/+clPmqfgFkrn95Fb/HloEuZDe9EHAmh6HfaM\n9gTimnYOOiGEEEKIWNSsI7lZWVk0NDQQCATCy2w2GyaTieTk5Ih1FUUJB9xGeXl5VFVVNUutLZWi\nBsndsxWj10VS9UHi3A1oeh0Oaza+hORT34EQQgghRCvQrCH33HPPxWAwsH379vCyr776im7duqH7\nTo/o/fffz6xZsyKWFRYW0qlTp+YotcXK3LcTs6MGs91GQn01qt6AJzEVd0pmtEsTQgghhGg2zRpy\nzWYzw4YNY9asWRQUFLBx40ZWrFjBddddB4ROTPN6vQAMGDCAVatW8cEHH7B//34WLlzI9u3bufba\na5uz5BYltaKYJFsZRreDlKoDqAYDfrOFhrSzol2aEEIIIUSzUurq6rRTr9Z0PB4Ps2bNYv369SQm\nJjJy5EhGjhwJQH5+PlOmTGHYsGEAvP7667z88sscPnyYc845h/Hjx0dMP3Yy75a6z9g2xCJLTQU5\ne79E5/eRcWAXml5P0BhHbXZnNL0+2uUJIYQQQpxU99827WV9mz3kNpe2FHLjHHW0K/wfuoCPjP27\nAA1Nb6A2pzNBY1y0yxNCCCGEOKWmDrkyWWoLZ/C6yd2zFSUYJK28GEVTQdFRn9lRAq4QQggh2iwJ\nuS2YEgyQW/w5er+HlMOl6H0eNJ2OhvSz8Jst0S5PCCGEECJqJOS2VJpGzt5tmNwNWGoPYXbWoen1\nuJIz8CSmRrs6IYQQQoiokpDbQmUc2EVC/WHiHHUk1lSg6g14E5JxWrOjXZoQQgghRNRJyG2Bkg/v\nC7UneN1YD5eiGowETPHY09uDokS7PCGEEEKIqJOQ28LE11eRcWAXumCA9PIiVJ0eVW+kPrMj6GR3\nCiGEEEIAGKJdgDg1RQ1i8LowuR1k7duJTg2SVlaIpihoOj31WR1RDcZolymEEEIIETMk5MYIXcCH\n0esK/xiO/n+f59sVNbBW7EEXCKDpddgz2hMwxUevcCGEEEKIGCQht7loGgaf55gA2/ijC/qP8zeg\nC/rQ+7xHwq4bo9+LwedG1RtwpObgS0hu/m0RQgghhIhxEnKbUGNbwbfh1X1UqHWjaMHj/I2GLugL\nBWCPE4Pfiy7oRxfwow/6QQtdkE5TdGg6HSgKqt6AOzEVd3JGc2+iEEIIIUSLICH3ezrttoKjKMEg\n+sa/8zjRB/3hIKtTg98GWb0eTfn25DFV/+3uCRpMBA1GggYT/jgLXkvKmd1QIYQQQogWTELudzVR\nW0FjkNUHAihqEEVT0XR6VJ3+22m+jozKQmikNmgwohpMoUBrPPLfIz8yNZgQQgghxOlrkyH3B7UV\naBq6wPdrKwDQdEd+B1SdPhxgVUNkiFX1BgmyQgghhBBNpNWG3KZoK9AFQwH2mLYCnT4cXCGyrUDV\nG48ZhW0MtppOf2Y3WgghhBBCAK045J697aNjFza2Ffh94eDbtG0FRlDkggxCCCGEENHWakNunLNe\n2gqEEEIIIdqoVhtyrYf2SluBEEIIIUQb1WpDbmOAlbYCIYQQQoi2p9WG3OoO3aWtQAghhBCijWq9\nw5kScIUQQggh2qzWG3KFEEIIIUSbJSFXCCGEEEK0OhJyhRBCCCFEqyMhVwghhBBCtDoScoUQQggh\nRKsjIVcIIYQQQrQ6EnKFEEIIIUSrIyFXCCGEEEK0OhJyhRBCCCFEqyMhVwghhBBCtDoScoUQQggh\nRKsjIVcIIYQQQrQ6EnKFEEIIIUSr0+wh1+fzMXPmTH71q18xdOhQli1bdsJ1CwsLGT16NH379uXG\nG2+koKCgGSsVQgghhBAtVbOH3KeffpqdO3cyb948HnzwQV588UXWrl17zHput5sJEyZwwQUXsGzZ\nMnr16sXdd9+Ny+Vq7pKFEEIIIUQL06wh1+128/bbbzNx4kTOO+88+vbty6hRo3j11VePWXft2rUY\njUYmTJhAXl4ed999NxaL5biBWAghhBBCiKM1a8gtKirC7/fTq1ev8LKePXuya9cuNE2LWHfnzp30\n7NkzYlnPnj3ZsWNHs9QqhBBCCCFarmYNudXV1SQnJ2M0GsPL0tLS8Pv91NTURKxrs9nIyMiIWJaa\nmsrhw4ebpVYhhBBCCNFyGZrzwTweDyaTKWJZ4+9+v/+01v3ueifS/bfX/IhKhRBCCCFES9asI7km\nkwmfzxexrPF3s9l8Wut+dz0hhBBCCCG+q1lDblZWFg0NDQQCgfAym82GyWQiOTn5mHVtNlvEsuO1\nMAghhBBCCPFdzRpyzz33XAwGA9u3bw8v++qrr+jWrRs6XWQpPXr0iFhP0zS2b99Ojx49mq1eIYQQ\nQgjRMjVryDWbzQwbNoxZs2ZRUFDAxo0bWbFiBddddx0QOjHN6/UCMHDgQNxuN7Nnz2bv3r088cQT\nuN1uBg8e3JwlCyGEEEKIFkipq6vTTr1a0/F4PMyaNYv169eTmJjIyJEjGTlyJAD5+flMmTKFYcOG\nAVBQUMDf/vY3SkpK6Nq1K/fffz/nnXdec5YrhBBCCCFaoGYPueL4hg8fzqFDh45Z3qVLF1566aVT\n/u1dd93FFVdccabK+9Hy8/MBWLlyJe3atYu47Y033uDvf/87t9xyC3feeWc0yjtjPvjgA6ZMmcK4\nceP4wx/+EO1yfpS2ug8B3nrrLZYsWcLbb78d7VLOuNPd1lWrVvH888+zatWqZqrsh2tNr8PvCgQC\nLF26lPfee4/KykqsViuXXnopd955J6mpqdEur0nV1NSwaNEiNm3aRH19PdnZ2VxxxRWMGjWKuLi4\nU/79559/TmpqKl26dGmGak/P8OHDSU9P58UXX4xY/sUXXzBmzBj+85//HNPO2dIcnW8URcFsNtO1\na1duvfVWfvnLX57Rx27Z/3KtzIQJE1izZk3Ez/PPPx/tspqM0Wjkk08+OWb5hg0bUBQFRVGiUNWZ\n9eGHH9K+fXtWr14d7VKaRFvch6Lla22vw6M999xzrF27lvvvv5833niDRx55hOLiYsaPHx/t0prU\n4cOHueWWW9i3bx8zZszgtddeY/z48axbt44777wTj8dzyvv405/+dMyc/LHg66+/5q233op2GWdU\nY75ZtWoVL774IhdccAETJ05k8+bNZ/RxJeTGEIvFQlpaWsTPd2edaMl69erFxo0bI5Y5HA527NjB\nueeee8xV71q6+vp6/ve//3H77bezZ88eCgsLo13Sj9bW9qFo+Vrj6/Bo7777LnfccQe/+MUvyM7O\nplevXjz88MPs3r2br7/+OtrlNZnZs2eTk5PDs88+y4UXXkhOTg59+vRh4cKFVFVVHTMSeiKx+B6V\nk5PDvHnzqKuri3YpZ0xjvsnIyKBz586MHTuWwYMH8+STT57Rx22RIfett95i+PDh0S6jWb355pv8\n3//9H/379+f222+noKAg4vaioiJGjhxJnz59GDduHJWVlVGq9MT69u3Ltm3bcDgc4WWfffYZvXr1\nwmKxRKy7dOlSRowYwaWXXsqvf/1rFi5cGL7tzjvvZPbs2Vx99dX85je/ob6+vtm24ftYv349JpOJ\nQYMG0bFjx4jDunfeeSeLFi3i9ttvp2/fvtx+++2UlJSEb8/Pz2fBggUMGTKEsWPHRqP842qKfbhz\n50569+4dMUXgvn376N27d8y/yVdUVJCfn09ZWVl42cKFC7n99tuB0CH822+/nRdeeIEhQ4YwcOBA\n5s6dG5MfrKdyqm1tKU71Ojz6aFl5eXnENtfV1XHffffRv39/RowYwRtvvBFu24kViqKwZcsWVFUN\nLzvrrLN49dVXOeeccwBYvHgxv/nNbxg4cCDjx4/nwIED4XXz8/N55513GDFiBKiYznoAACAASURB\nVAMGDGDy5Mk4nc5m346Tqamp4ZNPPuGmm2465tB9YmIi1113He+88w6qqrJ7927uuOMO+vbty4gR\nI3j33XcBwplh7NixvPDCC82+DSczcuRIEhISeOaZZ457u91uZ+bMmVxxxRUMGDCAKVOmYLfbARg9\nejTz58+PWH/8+PE8/fTTZ7zuH2vEiBHs2bOHsrIyHA4H06ZNY+DAgQwdOpTHHnsMl8sVXvdE+/VU\nWmTIba1O9EG4adMmFixYwD333MPy5cu55JJL+NOf/hQRElauXMmtt97KP/7xD4LBIFOmTGmusk9b\np06dyM3N5T//+U942caNG+nXrx9A+FD3mjVreOmll/jrX//KG2+8wW233cbixYsjgv2qVauYNm0a\nc+bMISUlpXk35DR98MEHXHLJJej1evr06cMHH3xAMBgM3/7Pf/6TQYMGsWzZMrKzs5kwYULEFf02\nbtzIokWLuPvuu6NR/nE1xT7s0aMHubm5rFu3Lnwfa9eu5Re/+AVWq7V5N6iJHN2mUVBQQGlpKYsW\nLeK+++7jtdde47///W8Uq2taLa0l5WSvw1O12EyePJna2loWLVrEpEmTeOGFF2Ju+6+99lreeOMN\nrrrqKmbOnMnatWtxOBzk5eURFxfHK6+8wpo1a5g+fTpLliyhffv2jBkzJjyTEYS+vNx3330899xz\n7N27l5kzZ0Zxi471zTffoKoq3bt3P+7tPXv2pLa2lm+++YY//elPdO7cmeXLl3PXXXcxa9Ystm/f\nztKlSwF47LHHYq4vOz4+nnvuuYfVq1dHTJ0KoVxw3333UVxczNy5c5k3bx779u1j6tSpAAwZMoR/\n//vf4fXtdjuff/55i5iJqlOnTgDs3buXhx9+GLvdzqJFi3jiiSfCbSkQ+rJ5vP361VdfnfIxJOTG\nkDlz5tC/f//wz4ABA6itreWf//wnN910E3369KF9+/bccsstdOvWLaKH5/rrr+fyyy+nS5cuTJ48\nmW3btrF3794obs3x9e3bl02bNgGhEyb++9//hgNSo6ysLKZMmcJFF11ETk4OV199Nenp6RHbc8kl\nl3DBBRfQrVu3Zq3/dFVVVbFt27bwtg0cOJC6ujo+/fTT8Dp9+vTh97//PXl5efzlL3/BbrdHhMcR\nI0bQsWNHzj777Gav/2SaYh8OHjyYjz/+OLz+2rVrW8Sb8okc/QU1GAzy4IMP0rFjR6644gq6du16\nzJGXlqwljUqfzuvwRPbt28eWLVuYMmUKXbt25ZJLLuGPf/xjzG3/rbfeyiOPPEL79u159913mTx5\nMkOHDmX58uUALFu2jLFjx/Lzn/+cvLw87r33XgwGQ8SXzJtvvpnevXtz/vnnc88997Bu3ToaGhqi\ntUnHaBy1PFH7XuPy//3vf1gsFu677z46duzI4MGDGT9+PMFgMPwFOikpifj4+OYp/Hvo27cvl156\nKbNmzYoYDCkpKeHLL79k6tSpdO/ene7duzNjxgw+++wzSkpKuPzyy9m/fz+lpaVA6PyI3NzcmP1s\nPFpiYiIAxcXFbNiwgWnTptGlSxe6devG1KlTWb9+PZWVlaxdu/aE+/VUDGd6I8607du388wzz7B7\n924URaFXr15MnjyZzMxMVq1axdtvv01+fj6vvfYafr+f3/zmN0ycODHmvo0D3HbbbfzqV7+KWJaS\nkkJpaSnPPfccCxYsCC/3+/1kZ2eHfz/6G25ubi7JycmUlpbSuXPnM1/4aVIUhX79+nHPPfcQDAbZ\nsmULXbp0OeYM4J///Ofs3LmTefPmUVpaSmFhITabLXw4TlEUcnNzo7EJp+3DDz9Ep9PRu3dvAH7y\nk5+QkZHB6tWr6du3L4qi0LNnz/D6CQkJdOjQgZKSEvr27QsQk9vYVPtw8ODBLF26FJvNRl1dHeXl\n5fTv3z8KW9T0rFZrROuGxWI5rTdj0fRO9To8meLiYiwWCx06dAgvi9WLEQ0aNIhBgwbhcDjYvHkz\nb775Js888wx5eXlUVVXx0EMPRRzm9/l8ES0LR78XdevWDVVV2bdvX8xsb2OItdlsZGZmHnN7VVUV\nELq41Lnnnhvx+f673/2ueYpsAvfeey/XXnstr7zySni61JKSEhISEsjLywuvl5eXR1JSEqWlpQwY\nMICf/exnrFu3jtGjR/Pxxx8zaNCgaG3C99LYFnPOOeegaRpXXXVVxO2KorB//35KSkp+8H5t0SHX\n5XJx9913c/311zNjxgyqqqqYMWMGS5Ys4b777gNChw6zs7NZtGgRBQUFTJ8+nd69e4ff9GJJamrq\nMVMzAaiqyoQJEyKm2tA0LeLbqF6vP+ZvjEbjmSv2B/rpT3+KwWDgq6++YuPGjccNNm+99RZPPvkk\nw4cPD/eQ3XXXXRHrnM50MdH04YcfEggEIt5sNE3js88+C/cQf7e3TFXViP1oMpmap9jvqSn2YefO\nnenSpQvr16+npqaGSy+99Jie3miy2WzhQ76NDAbDcb8cfzfAGgzHvq3G2ujf0X7Mtsa603kdHu3o\n7dPr9cfst1jbj0VFRaxevZoJEyYAoZGxgQMHMnDgQG6++eZwm8yjjz4aMeChaVp4FA0iPz8av4jG\n0rRV3bt3R6fTUVBQcMxRIwh9zlutVvLy8iJ6yFua3NxcbrnlFhYtWsQDDzwAhC6idTyqqoafr4MH\nD+aNN97g97//PVu2bGHcuHHNVvOPUVxcDMDBgwdJSEgIH31opGkaGRkZfPLJJz/4tRc7z+IfwO12\nc8stt3DrrbeSm5vLBRdcwIABAyIOa7eGQ4d5eXlUVlbSrl278M9LL73E1q1bw+scfcbwvn37cDgc\n4X6XWKLT6bj00kvZsGEDn3zyyXED0sqVK7nllluYOHEiQ4cOJSUlhZqampj7gDmR/fv3880333D3\n3XezYsWK8M/cuXPx+Xx88MEHQKiRvpHD4eDgwYN07do1WmWftqbah4MHD2bjxo18+umnMdeqsHz5\ncubOnRv+3eFwYLVawwH26BNzysrKYvLI0Olqrdt6Oq9Do9F4zPY1Ovvss3G5XBEjnt98802zbsOp\nBINBXn755ePWlZCQQGpqKqmpqVRXV4c/O3Jzc5k/f344YEDke9GuXbswGo0x1SZltVq5/PLLeeGF\nF475ouVwOHjppZe46qqr6NChA0VFRRHvMw8//HDEicuxbtSoUWRmZvLcc8+hKAodO3bE5XKF2xEg\n1MPqdDrDX0wbc8/KlSvJy8uLqSO4J/POO+9w/vnn07t3b1wuF4FAIPw8BXjiiSdwOBw/ar+26JCb\nnp7OsGHDWLFiBdOmTeOmm25ixYoVEWeZtoZDh9dffz2vvPIKq1ev5uDBgyxatIh33nknIsQuW7aM\njRs3UlhYyPTp0+nTp0/EYbZY0q9fP9555x2sVmv4kPzRT16r1cqWLVvYt28fu3bt4i9/+QuKooRP\nytI0LaYD74cffkhSUhJXX301nTt3Dv809hE3ztX5/vvv895771FSUsIjjzxCbm4uF198cZSrPz0/\ndB/6fL7wOkOGDOHLL7/k4MGDXHbZZc2+DSdz4YUXsnXrVjZv3kxRUVH4rPr09HSys7NZsWIFZWVl\nvPfee3z22Wcnva9Yf7425bbGktN5HXbv3p1169ZRUFBAQUEBCxcuDIf4vLw8fvnLX/Loo49SVFTE\n5s2bI26PBd26deOyyy7j3nvvZc2aNZSVlVFQUMCzzz5LcXExw4cPZ+TIkSxYsIANGzZw4MABZs2a\nxf/+97+Iz4/nn3+erVu3snPnTh5//HGGDRsWc32rEydOxOVyMXbsWLZu3cqhQ4f47LPPuOOOO8jN\nzeW2227jiiuuwO12h09cev/99/nwww/DR24TEhLYu3dvxOwwscZgMDBp0qTwxRPat2/PZZddxvTp\n08PP0+nTp9OrV6/woEhKSgq/+MUvWLJkScy2KjgcDqqrq6murqa4uJh58+bx0UcfMX78eDp16kTv\n3r2ZNm0aX3/9NYWFhUydOpXa2loyMjJOuV9PpkW0K5zocFpVVRU33ngj3bp145e//CUjRozgk08+\nYdu2bRHrfVcsf+Acz6BBg6itreWFF16gurqaTp06MXv27IhRv1GjRvHss89SUVHBpZdeyoMPPhjF\nik/uF7/4BcFgMOKw09EfHPfccw8zZszghhtuIDs7m5tvvpmsrKzwaEOsX3Rg7dq1DBky5LjtItdc\ncw1Tp04lJSWFIUOG8Prrr1NcXMyFF17Ik08+GVOHCE/mh+7Do484ZGdn061bN9q1axdzrRl9+vTh\nhhtuYNq0abjdbgYOHMhNN92EoihMnjyZOXPmcN1113HRRRdx6623smHDhvDffve5GevP16bc1lhy\nqtfhtGnTmDhxIsXFxdxxxx1kZWUxYcIE7r///vB6Dz30EDNnzmT06NFkZWVx5ZVXsmzZsubcjFOa\nOXMmS5cuZcmSJVRUVGAymbjwwgtZuHAhmZmZ3HDDDXg8HmbPno3dbue8887j6aefJiMjI3wfw4YN\nY/r06TgcDoYMGRJTM7o0Sk9PZ/HixfzjH/9g+vTp1NTUkJOTE77imclkIi4ujieeeILHH3+cN998\nk5ycHB566CF++tOfAqEBo8bPycYWj1h08cUXM3jwYNauXYuiKEydOpU5c+bwpz/9Cb1eT79+/Zg4\ncWLE3wwZMoT//Oc/MXdUrNFTTz3FU089haIoWK1Wzj//fObPn88FF1wAwLRp05g7dy5jx45FURTy\n8/O59957gVAbzsn268m0iMv6PvXUU+zdu5ennnoKCB1eW7duHUOHDuXVV1/ltddeC6/74IMPUl1d\nzaJFi4572cm77rqLXr16cccddzT7dgjR6K677uLnP/85t912W7RLiRpN07jmmmuYNGlSTPbIi7bN\n4/GwefNmLrnkkvBgyUcffcQzzzzTqi7vnJ+fz/z587nwwgujXYoQTa5FjOReeOGFvP7662zevJnU\n1FRWrlzJFVdcQUpKClVVVWzevJl27drx0Ucf8cknn5y0HyXWDx2KtqGtPw8//fTT8AT2Z/ra5UL8\nECaTiUceeYSrr76aK6+8EpvNxgsvvHDMDDhCiNjVIkLuiQ6nGY1GvvzyS/7yl78AcPnllzNz5kym\nTJkS7v1raYcORdvQ1p+H//rXv9izZw8zZsxo0/8OInbpdDpmz57NU089xUsvvYTFYmHo0KHHzPQi\nhIhdLaJdQQghhBBCiO+jZZzlIoQQQgghxPcgIVcIIYQQQrQ6EnKFEEIIIUSrIyFXCCGEEEK0OhJy\nhRBCCCFEqyMhVwghhBBCtDoScoUQQgghRKsjIVcIIYQQQrQ6EnKFEEIIIUSrIyFXCCGEEEK0OhJy\nhRBCCCFEqyMhVwghhBBCtDoScoUQQgghRKsjIVcIIYQQQrQ6EnKFEEIIIUSrIyFXCCGEEEK0OhJy\nhRBCCCFEqyMhVwghhBBCtDoScoUQQgghRKsjIVcIIYQQQrQ6EnKFEEIIIUSrIyFXCCGEEEK0OhJy\nhRBCCCFEqyMhVwghhBBCtDoScoUQQgghRKsjIVcIIYQQQrQ6EnKFEEIIIUSrIyFXHFd+fj4jR47k\nhhtuCP/MnDkz2mWFTZ8+nRUrVvyo+3A4HNx1110nvP2GG27A4XCccj2n08m4cePwer0sXLiQ/Px8\n3n333Yh13G43/fv35+677wZg4cKFrFmzBgj9W9fX13+v2o/eP6NGjeJ3v/sdN998M7t27YpYr7i4\nmPz8fJYuXfq97j+WqKrKyJEjT3h7eXk5/fv3/9GP89Zbb/H6668f97aVK1eG/w2PXm/Xrl089thj\nJ7zPO++8k4qKiuPe9s9//pMbbriBP/zhD1x//fU8/fTTBAKBH7kV4kQmTpxIaWkpAGPHjj3la+6L\nL77g+uuvB0LvNyd6DTW+T6xatSr8+v6xmuL9LVY0NDRw6623Nul9ns7+ayoFBQUMHz78lOud7P1D\nRI8h2gWI2DV//nxSUlKiXcZxKYryo+/DbrcfEwqPtnz5ciAUok623rPPPsuIESOIi4sDICcnhzVr\n1nDllVeG11m3bh3x8fHhuv/4xz/+6Pq/u39WrFjBnDlzWLx4cXjZG2+8wRVXXMHrr7/ODTfcgF6v\n/9GP29x27NhBjx49zvjjfPXVV5xzzjnHve3qq68+7nrnn38+r7/+Op988gmXXXbZMX+nKMpxn6sf\nffQRGzZs4MUXX8RkMuHz+XjggQdYuHAhY8aMaaItEkd74oknwv+/efNmNE077b892ftN4/tEU2qK\n97dY8emnnx73tfFjfN/91xxO9v4hokdCrjihE72JXHrppfTr14+ioiJmzJiBx+PhmWeewePxYDQa\nufPOO+nduzerVq1i3bp1+Hw+KioqyM7O5ne/+x2vvvoqBw4c4Prrr+cPf/gDEBoNmTx5Mt26dYt4\nLJfLxZw5c9i+fTt6vZ5+/fqFQ8D27dtZv349NTU1dO7cmUceeQSz2cw777zDW2+9hd/vx263c+ON\nN3LNNdewatUq3n77bbxeLxaLBQCv18uoUaNYunQpOl3kgY38/Hw++OADHn744ROuV1lZyaeffsqk\nSZOA0IfTL3/5SzZs2MDhw4fJysoCYPXq1QwdOjQ8kjR9+nTOOeec8PYDVFdX8+c//5nf/va3/Pa3\nv6WkpIS5c+dSX1+Pqqpce+21EcH56P0TCASoqKiICL1Op5P333+fJUuWUFhYyMcff8zgwYMBePjh\nh9m9ezcAfr+f0tJS5s2bx9lnn81jjz1GbW0tNpuN3NxcZs6cSWpqKsOHD6dHjx4UFxczZswY+vXr\nF36sTZs2sWDBAlRVJT4+ngceeICuXbvy73//m8WLFxMMBrFYLEycOJHu3buzcOFCysrKKCsro6qq\nih49epCfn8/q1aspLy9n7Nix4Vo3bNhA3759T/g4FouFYDDI3/72NwoKCmhoaGDcuHEMGDAAm812\nWttz1113sWnTJrZs2UJcXBy//e1vI54LCxcupL6+nosvvviY9UaMGMGsWbO+1we5zWZDVVU8Hg8m\nkwmTycSkSZOora0FQkcZ/v73v1NUVISiKPTu3ZsxY8ag1+vJz8/nww8/DO/rxt+Li4t5/PHHSUhI\nwOPxsGTJEtasWcNLL72ETqfDarUydepUsrOz2bRpE0uWLMHv92M2mxk3bhw//elPqaqqYuLEiTz5\n5JNkZGSE692wYQPLly9n0aJFAPzud79j0KBB/PGPf6SyspJbbrmFHj16cOmllzJ8+HB27NjBbbfd\nxptvvslZZ53Fiy++SEVFBR9++CEffPABZrOZxx57jNLSUhYsWADANddcw+OPP06nTp1O+bxasmQJ\nGzduxOv14vF4GDduHP3792fhwoXs3bs3vL+7du3K5MmTsVgsDB8+nL/97W+89tprAIwZM4YnnniC\nwsJCli5dit/vp7a2lmHDhnHHHXdE7C9N09ixYwejR4/G6XSSn5/P+PHjI/bH0T7++GPmzZvHk08+\nSceOHXn77bd544030DSNlJQUJk2aRF5eHtu2beOpp54iGAyiKAo333wzAwYMAH7c+1tiYiLPPffc\nCR/3u955553jPk/efPNNXn31VXQ6HWlpaUyaNImOHTsyffp04uLi2LVrFzabjV/96lekpqayadMm\nbDYbf/3rX7nooovCz53bbrsNl8vFjBkzOHjwIDqdjm7duvHggw+GX4+N7+vvv/8+69atY/r06Uyf\nPv2Y9R9++OHw/nvyyScBmDNnDocOHSIQCDB48GBuvvlmysvLGTNmDBdffDE7duwgEAgwfvx4Vq5c\nyb59+zj//PN55JFHjvuF4vXXX+df//oXiYmJdO7cOeJ1e7z3k23btkW8LwwYMOCE7zuieUnIFSc0\nZsyYiED37LPPYrVaCQQC9O3bl5kzZ1JXV8d1113H3Llz6d69O3v37uXOO+/kH//4BxD6dvvyyy+T\nmZnJ9ddfz9q1a5k/fz5FRUWMHj06HPJONBqyYMEC/H4/r732GsFgkD//+c9s3boVTdOoqqpi/vz5\nGI1Gbr75ZtavX0///v15++23efLJJ0lOTmbHjh2MGzeOa665BoCSkhLeeecdEhISqKio4Prrr2fZ\nsmUn/DdQFIUpU6accL0NGzZw8cUXR/w7GQwGfvWrX/H+++9z4403cujQIdxuN507dw6H3O++sVZW\nVvLQQw8xevRohgwZQiAQ4IEHHmDGjBmcd955OBwObr31Vs4+++zwqOaYMWNQFIW6ujpMJhN9+vRh\nypQp4ftcs2YNeXl5dOrUiWHDhvGvf/0rHBwfeuih8HqTJ0/moosu4qKLLuKVV16hZ8+ejBo1Cggd\n4n3vvffC+6lLly48+uijEbXbbDamTZvG888/T9euXVm/fj3z5s1j4sSJzJo1i8WLF3PWWWfx+eef\nc++994ZDxldffcWKFSswGAwMGzaM7OxsFixYwMaNG3n66afDtW7ZsoW77rrruI/z3HPPcd999+Hz\n+cjPz+eBBx7g3//+N08//TQDBgzgo48+Ou3t2bhxI126dDkm4DbuL0VR6N+//zHr9ejRg6qqKioq\nKsjNzT3BMynSsGHD+OSTTxg6dCjdunXjggsuoG/fvvzsZz8DQh/aVquVl19+Gb/fzz333MPy5cu5\n6aabTnq/JSUlvPXWW2RnZ1NYWMi8efNYtmwZWVlZ/Otf/2LJkiWMHDmS+fPn8/zzz5OcnMyePXsY\nO3YsK1euJDMz87ivxfz8fKZPn47D4cBut+N0OtmyZQt//OMf2bRpEwMGDOAnP/kJGzduZPjw4fzn\nP/8hPT2dzZs383//939s2rSJSZMmUVZWxueff85ll13GF198gcvlwu12U1FRgcFgiAi4J3pePfDA\nA2zZsoUFCxZgMpn48MMPWbhwYbhlZceOHSxbtozU1FSmTJnC4sWLGTduXHg/TpkyhdWrVzN//nyS\nk5OZNm0a06ZNo3379lRVVXHVVVdx3XXXHfNvUF1dzfPPP4/BYGDs2LG89dZb4feVo73//vssXbqU\n559/nqysLLZu3cp7773HwoULMZvN/Pe//+W+++7jlVdeYeHChYwcOZJBgwZRXFzMm2++yYABA5rk\n/e1kj3u0Ez1PLr/8cpYvX87ixYuxWq2sWrWKSZMmhf++qKiIF198kbq6On79619z77338sILL/DK\nK6+wdOlSLrroInw+HwcOHKBLly689957uN1uli9fjqqq/H875x5UVdUF8N+9XFQIEFAxQSR1zLyC\nosK9NxJ5GCqkTpCpKFpCiBY+UKd0rCEtHymg5Tg+K1N0rCHUTMfMiZcOECn4CA3HB4mYDqMmFArd\ne78/mLvnPrhgj6/6/PbvL+45i7P32WuvtddZZ+2zevVqamtrefHFF0lLS2PWrFkolUr27dtHYmIi\neXl5rcqb669z587Mnj2bKVOmEBoayoMHD5g/fz49e/ZErVZz48YNRowYwdKlS3nvvffIzMxkz549\nqFQqYmNjOXv2LIMGDbIZj+3bt7Nnzx48PT1Zu3at8Ndt+ZOioiLhF9rzo5K/DxnkSuzSVrlCYGAg\nAN9//z2+vr6o1WoA+vTpw6BBgzh16hQAarVaZDO9vb3RarUA+Pj40NTUxP379+nUqZPdPpSVlZGW\nloZCoUClUrF582YAvvzyS8LCwkSJQN++fbl9+zZOTk5kZWVRVFRETU0NVVVVNDY2iuv169cPZ2dn\nwH6m2pq25Kqrq/Hx8bE5HhMTw7vvvsv06dM5fPgwzz33XJttpKWl0b17d0aPHg3Ajz/+SG1trcha\nADQ1NVFVVSWCXJN+qqqqmDdvHgEBAbi7uwv53Nxcnn/+eQDGjBnDxo0bOXPmjIVTX7duHY2NjaKd\nSZMmUV5ezu7du7l27RqXLl2yKBUw6d2cM2fO0KdPH/r16wdAREQEERER5OTkoNFo8Pb2BiAoKAgP\nDw8uXLiAQqFAq9WKjHq3bt3Q6XRAy9y4d+8eAJcvX8bb2xtHR0e77dTW1uLo6CgyYP369RMZ0T9y\nP/Zoax54e3tz9erVhw5yXVxc2LBhA9evX+fkyZOcPHmSBQsW8MILL5CamkpJSQnbt28HwNHRkbi4\nOPbu3dtukOvl5UX37t2BFtvR6XTC/kyBW05ODnV1dRZlEUqlkpqaGruvWzt16oRGo6G0tJSff/6Z\n2NhY9u/fT0NDAwUFBbz00kv079+f9evXo9frKS0tJTExkdLSUoYPH87t27dRq9WEh4dTXFyMr68v\nXl5euLm5cerUKS5evMjIkSMt2rSnb4D09HQOHz7M9evXOXfunIWNjxw5Ek9PTwDGjx/PunXrRJBr\njUKhEP7iyJEj4iH0/v37NnLR0dHCV0VHR3PixAmbILeyspLi4mIWLlwoxv348ePU1NTwyiuvCLn6\n+nru3btHVFQUa9asoaioCI1GI2r/FQrFn/Zv9tqtr6/H1dVVHLM3Tz744AOioqKETxk7dixZWVnU\n1taiUCgIDQ3FwcGBLl264OTkxNNPPw202ILJfsvKyggODgZabG3Tpk3Mnj0bjUbD5MmThe/09vbm\n+PHj+Pr6UldXh1arpba21q68icbGRsrLy6mvrxdvBBobG7l48SJqtRqVSkVoaCgAPXv2ZPDgwWJ8\nunbtSn19vc2cMI2HaQ7FxsZy/PhxoH1/YuJh5ST/fWSQK/lDODk5Aa0v/AaDgd9++w2VSoWjo6PF\nud9bE6pSWU7RW7du0aFDB5tzpiftmzdvkpSURFxcHIGBgURGRgoHZd5vawoLC9m6dSvQEnCZ1++1\nhVKpxGAwWBxTKBSo1Wr0ej1VVVUcO3aMLVu2UFBQYPc6S5Ys4aOPPmL37t1MnToVg8GAi4uLRVat\nrq7OYnEy8eSTT5KWlsaKFSvw9/enR48eVFRUcPnyZXbt2iU2sDg6OrJ3714R5O7evZuKigq2bNki\nxm/Dhg1io0VwcDB6vd5Cx6YFwhyVSmWTmb506RJGo9FmfhiNRrG5ylq3END5OQAACIZJREFU1r+h\nRS+mDJ29dpycnGzmgqndP3I/APPnz6eurg7A5tV1axgMht81tz/55BOGDBnCoEGD8PHxYfz48Zw+\nfZp58+aRmpqKwWCw6KfBYECv14vfpnPNzc0W1zW/H+vxNJUNGQwGgoODLTLyP/30kwhy7BEeHs6J\nEydoaGhg2rRpVFdXk5+fz5UrVxg6dChKpZL+/ftTWFhIQ0MDMTExbN++nfz8fKHD8PBwUlJS6NWr\nF1qtFldXV0pKSqisrGTx4sUW7dnTd3NzM4sWLWLq1KnodDqGDh3K6tWrhYz5W5X29NLY2EhCQgIR\nEREEBgYybtw4CgoKWvVr1te19m0Arq6urFixgiVLlvDMM8/Qo0cPjEYj0dHRpKamAi26u3nzJm5u\nbsTGxhIaGkpJSQklJSVs27ZN2Ouf9W/22rX2Ifbmiel/zDG3X+v7t2e/0dHRQEsgm5uby8mTJ/nu\nu+9ITU1l0aJFREZGMmHCBL744gt69epFbGxsu/ImTDbx4YcfigeCu3fv0rFjR+7cudPu+mM0GsnN\nzSU3NxdoqbHv3bu3xX2b6709f9KWnPU6Ifl7kF9XkPwp/P39qa6uprKyEmhZhCoqKhg2bNhfcv3g\n4GAOHTqE0WgUm3PKy8vtyl+4cAFPT08SExPRarUUFRUBtOpgHBwchJMcMWIE2dnZZGdn2wS45nLW\n9OrVi+vXr4vf5oFdTEwM69atw8/Pz2ZhsXaMAQEBpKen8/HHH3Pp0iX8/Pzo0KEDR44cAVoWt4SE\nBFFHa82oUaMICAggKysLaMnWxcTEcPDgQQ4cOMCBAwfIysoiLy+Pmzdv8tVXX5GTk0NmZqZFJr20\ntJT4+HjGjBmDu7s73377bbvOWa1Wc/XqVS5fvgxAfn4+b731FkFBQZSWlorxKSsr49atW/j7+z90\nFt1804q9dtrapPN77sfBwUEs4OvXrxfzITQ01KK/5nLQossbN260Wutoj6amJjZu3Mjdu3fFsStX\nroiadJ1OJ8o6mpqa2LdvHxqNBgAPDw+xETIvL89uG0FBQZSVlYlg/fPPP2fDhg1CL9XV1QAUFxeT\nkJBAU1NTm30ePnw4ZWVlXLx4kYEDB6LVatmyZQshISEiEAgLC2PTpk1oNBqcnZ3x8/Nj586dIkvr\n5eWFu7s7ubm56HQ6tFoteXl53Lt3T2RsTdjTd0VFBWq1mvj4eAIDA8nPz7fQaVFREQ0NDRgMBvbv\n3y8yeeYolUqam5u5du0av/zyC7NmzWL48OGcOnWKpqYmG3s3Go0cPXqU5uZmHjx4wKFDh0Tm0hxf\nX1+GDRvGxIkTefvttzEajaJm16SH/fv3M2fOHACSkpL44YcfGDt2LIsXLxaZVnv8Hv/WVrvm2Jsn\nOp2OY8eOiTl68OBB3N3d8fX1fWj7PXv2LIMHDwZafNLy5cvR6XSkpqai0+mEbkeOHElVVRX5+fli\n30Fb8ib9ubi44O/vLx4MGhoamDlzJoWFhTZ9aa3PCoWCuLg4YetLly5Fq9VSWlrKrVu3gJa3hiba\n8ifmfuGP+FHJfweZyZW0SluBg/k5d3d3Vq1aRUZGBvfv3xc1b76+vpw+fdrmOua/zf+2t/EsOTmZ\nzMxMpk6dil6vZ9SoUURERAjnbo3p810TJkzAw8ODsLAwunbtyrVr12za7NatG0899RSTJk1i69at\nNqUZJllzuW3btuHm5iZkwsLC2LVrF0ajUdRtmv5vzJgxbN68mYyMDJtrtjYOfn5+JCYmkp6ezo4d\nO8jIyCArK4udO3ei1+tJSUkRWdjW9LNo0SISEhL4+uuvKSgosPnkUVBQEAEBAXz66ad89tlneHl5\nsWDBAuF84+LiSEpK4v3332fHjh14eHgQGRkpxs4c6w1Ky5cvZ9myZej1elxcXFi5ciVPPPEEr7/+\nOm+88QZ6vR4nJycyMzN57LHH7H51wHxM6urq6NChg3hA6NKlS6vtmMa+Nd097P0AhISEsHbtWgCb\nsgDz/lrLnT9/np49e4oygYchKSkJpVJJcnIyCoUCg8HAwIEDxWf6Fi5cSEZGBvHx8TQ3NxMSEsKM\nGTPEuTVr1uDq6opGo6Fbt2429w0tr7jnzp3LvHnzgJZ5/Oabb9K1a1eWLFnC0qVLMRqNqFQq8bBj\nb+MZtJRY9O7dG2dnZ5RKJRqNhhUrVogSAmixh4yMDBFM6XQ6cnJyLEpkwsPD2bNnD/379wegY8eO\nItP7MPPKzc2Nb775hsmTJ9O5c2eioqI4evQov/76KwCenp6kpaVx584dhgwZwssvv2wz/hEREaSk\npIgNgxMnTqRLly4MHjyYAQMGUFNTg6Ojo4W9+vj4kJycLD4HaCpBas2WZ8yYQWFhIdnZ2UybNo3p\n06czZ84cFAoFLi4urFmzBoC5c+eSmZnJ5s2bUSgUJCcnt1ny8nv8m06ns9tuZWUlK1euJDs7u815\nEh8fz6uvvorBYMDDw4OsrKxWbdd6DBQKBefOnWPAgAHi3NixYykvL2fSpEl06tSJHj16iNIIlUpF\nZGQkd+7cEX64LfmIiAhmzpxJRkYG77zzDmvXrmXKlCk0NzczevRoRo8eLcoqrPvVHn379iU1NZXX\nXnsNZ2dnBg4c+FD+xNwvtCZXU1PTbtuSvx7F3bt3/13f4ZBI/sdYtWoVwcHBPPvss/90VyT/AMuW\nLSMqKoqQkBCbc7NnzyY9PZ3HH3/8H+jZ/x9bt27l9u3bNqUPkn83jY2NpKSksHjxYrG/QyL5K5Dl\nChLJn8S007q9172SR4/z58/j4ODQaoAr+ft52Gyd5N9DcXEx48aNIygoSAa4kr8cmcmVSCQSiUQi\nkTxyyEyuRCKRSCQSieSRQwa5EolEIpFIJJJHDhnkSiQSiUQikUgeOWSQK5FIJBKJRCJ55JBBrkQi\nkUgkEonkkeM/HDZOIShn9GgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xa8cb9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot ride data\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "def func(x, pos):  \n",
    "   s = '{:.1f}'.format(x/1000000)\n",
    "   return s\n",
    "\n",
    "ax10 = bike_share_monthly_minutes['Registered'].plot(kind='area', stacked=False, grid=False, figsize=(10,6), fontsize=14, \\\n",
    "                                                     alpha=0.4)\n",
    "ax10 = bike_share_monthly_minutes['Casual'].plot(kind='area', stacked=False, grid=False, figsize=(10,6), fontsize=14, \\\n",
    "                                                 alpha=0.4)\n",
    "ax10.set_xlabel('', size=14)\n",
    "ax10.set_ylabel('Total Minutes (millions)', size=14)\n",
    "ax10.tick_params(\n",
    "    axis='both',\n",
    "    which='both',      \n",
    "    bottom='off',      \n",
    "    top='off',         \n",
    "    right='off',\n",
    "    left='off',\n",
    "    labelbottom='on')\n",
    "\n",
    "date_fmt = 'Jan'\n",
    "formatter = mdates.DateFormatter(date_fmt)\n",
    "ax10.xaxis.set_major_formatter(formatter)\n",
    "y_format = tkr.FuncFormatter(func)  # make formatter\n",
    "ax10.yaxis.set_major_formatter(y_format)\n",
    "ax10.set_ylim(0,4000000)\n",
    "\n",
    "legend = plt.legend(fontsize=14)\n",
    "\n",
    "ax10.text(0.13, -0.15, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
    "          fontsize=12, transform=ax10.transAxes) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FC7mmKJR18qCYELfDakG7Zxuu497H4/0XMaye7zDQWiv7YmrVCYuLW55zmksXcZkbhfuQ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\nnoYudjfE7rYfUw0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RERF8/vnnvP3222zbto2+ffsW2I+goCB7Tffccw/BwcF0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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xa536588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot ride data\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "def func(x, pos):  \n",
    "   s = '{:.0f}'.format(int(x))\n",
    "   return s\n",
    "\n",
    "ax10 = bike_share_monthly_minutes_median.Registered.plot(kind='line', stacked=False, grid=True, figsize=(10,6), fontsize=14, \\\n",
    "                                                         alpha=1)\n",
    "ax10 = bike_share_monthly_minutes_median['Casual'].plot(kind='line', stacked=False, grid=True, figsize=(10,6), fontsize=14, \\\n",
    "                                                        alpha=1)\n",
    "ax10.set_xlabel('', size=14)\n",
    "ax10.set_ylabel('Median Ride Duration (minutes)', size=14)\n",
    "ax10.tick_params(\n",
    "    axis='both',\n",
    "    which='both',      \n",
    "    bottom='off',      \n",
    "    top='off',         \n",
    "    right='off',\n",
    "    left='off',\n",
    "    labelbottom='on')\n",
    "\n",
    "date_fmt = 'Jan'\n",
    "formatter = mdates.DateFormatter(date_fmt)\n",
    "ax10.xaxis.set_major_formatter(formatter)\n",
    "y_format = tkr.FuncFormatter(func)  # make formatter\n",
    "ax10.yaxis.set_major_formatter(y_format)\n",
    "ax10.set_ylim(0,30)\n",
    "\n",
    "\n",
    "ax10.text(0.13, -0.15, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
    "          fontsize=12, transform=ax10.transAxes) \n",
    "\n",
    "ax10.text(0.16, 0.67, 'Cherry Blossoms?', transform=ax10.transAxes, fontsize=14,\n",
    "        verticalalignment='center', backgroundcolor='#f0f0f0')\n",
    "ax10.arrow(0.265, 0.7, 0, 0.11, head_width=0.025, head_length=0.05, fc='k', ec='k', transform=ax10.transAxes)\n",
    "ax10.grid(b=True, which='minor')\n",
    "ax10.spines['bottom'].set_visible(True)\n",
    "ax10.spines['bottom'].set_color('grey')\n",
    "\n",
    "legend = plt.legend(fontsize=14, frameon = 1)\n",
    "frame = legend.get_frame()\n",
    "frame.set_color('#f0f0f0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x91b2278>"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\matplotlib\\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  if self._edgecolors == str('face'):\n"
     ]
    },
    {
     "data": {
      "image/png": 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f//N/8rGPfYzbbruNSy+9lLVr1zJmzBgA2tvbKSgoAGDfvn1MmDABgKeffprPfe5zXH/9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\nEjuPPcSmkYPo7nMPuRFivZLAK8QySGdG2HL2GXTXYXD0kH++q6aT7xm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RO+FvahsYO8qu\nIz8mUs13utQNQQKvWFOilTzDJx7FcC16J04QalTxDINyVx+l1GCnyxNCCCFmaTrl5ADTg7uwQjFc\nwyRo1dg8cpB4cYpwvczOow+zaeQgumN3utp1TQKvWDOilRzbT+xHd236xk8QalZRhkE50Uc5NdDp\n8oQQQoiLcgJhMn3DFNJb8AwTzzBJ5ccYPHcY06rTnRnhJYd+SDI31ulS1y0JvGJNiJUzbD/xKIbr\n0D92nJBV84+DSfRTTkrYFUIIscppGrV4mqnBl1Cb2dTmuWwaPUI6c5aA3WDozFNsP75fNrUtA9m0\nJla9WCnDtlOPY7gOfePHCdp1PN2glBygkujrdHlCCCHEonmGSaG1qS2VHwcNotU8kVqRXI+/qe0l\nhx9gamAX2f5hlG50uOL1QVZ4xaoWL06xvR12jxFoh91BCbtCCCHWLCscZ2pwF+VEP54R8De1TZ2k\nf/wYht1kYPwYu478mGgl1+lS1wVZ4RWrjua5dBWnSGfPES9n0ZRH//gxTLuB0g2KqUGqXb2dLlMI\nIYS4NJpOOdlPLZoklR8jRBXTbrB55CDF1CCkBthx7BHyPVuY3HwZrhnsdMVrlgResWqE6hVSuXOk\nc6MYrd2qoUaZdGYEw3VaYXcT1a6eDlcqhBBCLB03ECLbv4NItUCyMAGaRrIwQaySI9u3nXR2lERx\nionNeyn0bOl0uWuSBF7RUZrnksxPkM6dI1rxzyLUXZuu4hTRah7TsXGNAErXKaQ3U4t3d7hiIYQQ\nYnnUYykakS6ShQmi1Ty65zE4dpRqPE2+Zytbzj5NKjfK2NbLscLxTpe7pkjgFR0RrhVJZ8+RzI9j\nuA6gCNdLJApTBJtVlKahdAPXDGAFo5QTfTQjXZ0uWwghhFhWSjcodG9pTWobBxsitSLheplCt7+6\nu/vwj8gM7GR6YKdsalskCbxixeiuTTI/Tnf2HOFaqX0tUZggWi1geA6uHvDPKNQNatEUtVgaJxju\ncOVCCCHEyrJCMaYHdhEvZ+gqTaMpj+7ps8TLGbL9w/RNnCCVG6UWS9MIx2m2XqxQFDSt0+WvOhJ4\nxbKLVvKksyMkChPongd4RKpFEsUpAlYNpRkoXcc1AjRDMWqxNPVoQuaLCyGE2Ng0jUqij3o0STI/\nTrhRxrSbbBp5llJygHKyn4DVIDnnQ5Su0wzFaIbjEoTnkMArloXhWKRyo6Sz5wg1qu1ryfwY4XoZ\nw3NxDRPPCOAagdZqbgo3EOpw5UIIIcTq4ppBcn3bidSKJAoT4NokilMkipO4holrBHEDwXbQ1R2b\ncL18kSAcpRnuohGOY4VjNMJdGyYIS+AVS0cpYpUs3ZlzdBUn0ZRCUx6RSo6uUoagVcNtnTXoGgEa\n4bj/q5hI14b4YhNCCCEuRT2apBGOkyhOEq3k0VBogOlamI5FpFpEUy5K09uLSk4g1A66fhCuLBCE\nZ1eDG+E4Vii2rr43S+AVl8y0Gu3V3KBV96/ZDf/XL/USmlJ4holrBv3V3FiaaiyNZwY6XLkQQgix\ntijdoJjeTCk5QMBqYDpNTLtJwG5gOhaG6x/rqQGGa2M4disIn0NpOp5u4JpBHLO1IhyJt4PwvOfR\nNJrh2EWCcHRNthxK4BUvjlJ0laZJZ0foKk2D8o8Yi5WzxCtZAlYD1zBRuoGHRiOSoBZL0QzH19VP\njEIIIUQnKN3ACsewiM27rnmuH37tmSDcxHSa7SAMc4JwrYSWc1Fo7YWpeUHYddZNEJbAK16QQLNG\nOusPhzDtpn/NqpLMTxKul4GZ1dwAjhmiFktTi6XwDPmrJoQQQiw3pRtYoZjfkjDHSgVhKzR/s1wz\nvDqCsKQQ8bxmRv12Z88RK2fnXYtVcpiOhWsE8AwDpenUIwlqsTRWOPY8jyyEEEKIlbCkQfiirRGx\ndhBOzH1eTcO6yKkRKx2EJfCKBS006rerMEm4UQE0PMMfDmEHwu3VXDkEWwghhFgbljIIo+m4c4Kw\nFYrSaK0IhxqdDcISeMU8/qjfcdK50QVG/Vq4RhDPMFGa7h8nFk9jByMdrlwIIYQQS+W5gnB7k5zd\nJNDaNLdQEE4tFITDzx+E2fv6Jft8JPAKYIFRv7USieIkwWZtzqjfIFYw2h4OIau5QgghxMahdAM7\nFMUOReddnw3CTUy7sXAQdltBWD1/EF5KEng3sIuN+jVci67CJNFqAd1z8GTUrxBCCCGex3IEYXj3\nktUngXcDuuio30qRRMkf9evpJmganoz6FUIIIcQluJQgvJQk8G4QFxv1a9pNEgV/OITheTLqVwgh\nhBArYjFBeGgJn08C73q2wKjfaCVHvDRN0Kq3Rv3quIYho36FEEII0VELBeFLJYF3HbroqF+rTrIw\ncdFRv9VYmpqM+hVCCCHEOiWBd71YYNRvvJwhVskRaK3mzhv1G0/TDMVkNVcIIYQQ65oE3jXuoqN+\nm9XWam6F2VG/QRn1K4QQQogNaWOlnlYPq6aU/zbnva88NAWa8mDObZry/BXT9vvqvNvPuy9c/GOZ\neV/N+TgFc+6rwfz328914fOhaO9mnD/qt9kaDiGjfoUQQgghNkTgvfzAfa3guFao2XpbwXz2NfNC\nsO7aJIpTrQOaZ0b9BmXUrxBCCCFEy4YIvMFmpbVyq9CUe95q7fkrvGp2NdabXa31X8+E5lbwbAfR\n2bf9m1VrpbYVTOddaz1W+3ZmV3xnHnuGUmiahmpd09R5t7ceyTUCMupXCCGEEGIBGyLwDo4ewQ+p\nWitpan5sbG/WakXNmdvmbeKa+ZhlMPM8ml/Pi1uD1rCCERn1K4QQQgixgA0ReF0z2HprNswqND9o\nzryvafNvb70/E0b919p5r8+/Pvf92efwH3fu8z//8ypt/mMudB//fjIBTQghhBBiIRsi8I4NXQ7t\n8CmEEEIIITaSDRF4ZQVUCCGEEGLjWlNJ0LIsbr31Vn72Z3+Wt7zlLXz961/vdElCCCGEEGKVW1Mr\nvLfddhvPPPMMt99+O5OTk/zJn/wJg4ODXHvttZ0uTQghhBBCrFJrZoW3Xq9zzz338IlPfILLLruM\nq6++mg9+8IP8y7/8S6dLE0IIIYQQq9iaCbzHjh3Dtm2uuOKK9rVXvepVHDp0CLWmhkoIIYQQQoiV\ntGYCbyaTIZFIEAgE2te6u7uxbZtcLtfByoQQQgghxGq2Znp4G40GwWBw3rWZ923bfs6Pvep97162\nuoQQQgghxOq2ZlZ4g8EglmXNuzbzfjgc7kRJQgghhBBiDVgzgbe/v59yuYzjOO1r2WyWYDBIIpHo\nYGVCCCGEEGI1WzOBd8+ePZimyVNPPdW+9uSTT7J37150fc18GkIIIYQQYoWtmaQYDod529vexmc+\n8xmeffZZfvCDH/CNb3yD9773vZ0uTQghhBBCrGJaoVBYM2d6NRoNPvOZz3D//fcTj8d5//vfz/vf\n//5OlyWEEEIIIVaxNbPCC/4q75/8yZ/wf//3f9x7773rNuxef/317Nu374KXxXy+119/Pf/1X/+1\nAlVempnPaXR09ILb7rrrLvbt28df//Vfd6Cy5XPfffexb98+vvGNb3S6lCWxEf8fzrj77ru5/vrr\nO13Giljs53rvvfdy3XXXrUBFl269fS3OcByHv/u7v+Nd73oXr3/967nuuuv4sz/7M/L5fKdLW3K5\nXI7PfOYzXHfddbzhDW/g3e9+N1/96ldpNpuL+vhHH32UEydOLHOVL9z111/Pr/7qr15w/bHHHmPf\nvn14nteBqpbW3IzzUz/1U7zxjW/kox/9KA899NCyPu+aCrwbycc//nG+853vzHtZb+EhEAjwwAMP\nXHD9+9//PpqmoWlaB6paPt/97ncZGhriP//zPztdypLZaP8PxfqwHr8WAb785S/z3//939x8883c\nddddfPrTn+b48eP8zu/8TqdLW1JTU1N86EMf4syZM/zpn/4p//qv/8rv/M7v8L//+7/ceOONNBqN\n532M3/zN31y1Z/gfPHiQu+++u9NlLKuZjHPvvffyta99jVe+8pV84hOf4JFHHlm255TAu0rFYjG6\nu7vnvay30yiuuOIKfvCDH8y7VqlUePrpp9mzZ8+6mqBXLBZ5+OGH+ehHP8qJEyc4evRop0taEhvp\n/6FYH9br1yLAt7/9bX7913+dq666ioGBAa644go+9alPceTIEQ4ePNjp8pbM5z73OQYHB/nSl77E\nT/7kTzI4OMgb3vAG/uZv/obp6Wm+9rWvLepxVuu/T4ODg9x+++0UCoVOl7JsZjJOb28vO3fu5Ld+\n67f4uZ/7Ob74xS8u23Oui8C7kX69CPCtb32LG264of1rgGeffXbe7ceOHeP9738/b3jDG/jt3/5t\nJicnO1Tpc7v66qs5cOAAlUqlfe3HP/4xV1xxBbFYbN5977zzTn7hF36B173udbz1rW/lb/7mb9q3\n3XjjjXzuc5/jne98J9dddx3FYnHFPofFuv/++wkGg1x77bVs27aNe++9t33bjTfeyN/+7d/y0Y9+\nlKuvvvr/b+/O43LM/sePv+42ZKksJVuWMZIsQ7qzpMVUsn6yDJGt7CNk+zCDypIxkm1IxdhiLMm+\nG7QYS2P3iam0jIip1CRK6e73R7+uR7cWDEP6nufj0eOh+zpd1znXOde53tc557oxduxY4uLipO1y\nuRw/Pz/s7OxwdXX9FNkv1Yeowzt37tCpUydSU1OltAkJCXTq1Kncd/hJSUnFlnX4+/szduxYoGCa\nf+zYsWzcuBE7Ozusra3x8fEptzfasryprJ+LN12LRWfSHj16pFTm9PR0Zs+ejaWlJQ4ODtLSnfJC\nJpMRERGhNO1dr1499uzZwxdffAHApk2b6N27N9bW1kydOpUHDx5IaeVyOYcOHcLBwQF2DMpOAAAg\nAElEQVQrKyvmzZvH8+fPP3o5yvL06VPCw8MZOXJksW9oqlatGkOGDOHQoUMoFAr++OMPxo8fT7du\n3XBwcODw4cMAUrzg6urKxo0bP3oZ3mTo0KFoamqydu3aErdnZGTg5eVFjx49sLKyYsGCBWRkZADg\n7OyMr6+vUvqpU6eyZs2afz3f78vBwYH79+/z8OFDMjMz8fDwwNraGnt7e5YuXcqLFy+ktKXVbVkq\nRMBbEZV2QwwLC8PPz48ZM2YQGBhI586d+fbbb5WCheDgYFxcXNiyZQt5eXksWLDgY2X7nTRu3Bh9\nfX0uXrwofRYaGoqFhQWANB1+/Phxdu7cyffff8++ffsYM2YMmzZtUgr0jxw5goeHB97e3mhpaX3c\ngryFkydP0rlzZ1RVVTE3N+fkyZPk5eVJ27dt24aNjQ3bt29HT0+PadOmKf0PgqGhoQQEBDB9+vRP\nkf1SfYg6NDY2Rl9fn7Nnz0r7OH36NKampmhra3/cAn0gRZdyREZGEh8fT0BAALNnz2bv3r3/+lq1\nj+lzW7ZS1rX4pmU48+bNIy0tjYCAAGbNmsXGjRvLVfkHDx7Mvn376Nu3L15eXpw+fZrMzEwMDAyo\nVKkSu3fv5vjx43h6erJ582YaNGjApEmTlNa9+vv7M3v2bNavX09sbCxeXl6fsETF3bt3D4VCgZGR\nUYnb27ZtS1paGvfu3ePbb7+ladOmBAYGMnHiRJYtW8atW7fYunUrAEuXLmXYsGEfM/tvpUqVKsyY\nMYOjR48qfRUrFMQGs2fPJiYmBh8fH9atW0dCQgLu7u4A2NnZcf78eSl9RkYGv//+O7a2th+zCP9I\n48aNAYiNjWXRokVkZGQQEBDAypUrpeUrUPDgWVLd3rx5s8z9i4C3nPL29sbS0lL6sbKyIi0tjW3b\ntjFy5EjMzc1p0KABo0ePxtDQUGm9j6OjI927d6dZs2bMmzePGzduEBsb+wlLU7pu3boRFhYGFLxw\ncenSJSlYKqSrq8uCBQswMTGhbt269O/fn1q1aimVqXPnzrRp0wZDQ8OPmv+3kZyczI0bN6RyWVtb\nk56ezoULF6Q05ubmfPPNNxgYGPDdd9+RkZGhFEQ6ODjQqFEjmjRp8tHz/yYfog5tbW359ddfpfSn\nT5/+LDro0hR9YM3Ly2Pu3Lk0atSIHj160Lx582KzMp+zz2m0+m2uxdIkJCQQERHBggULaN68OZ07\nd2bcuHHlqvwuLi4sXryYBg0acPjwYebNm4e9vT2BgYEAbN++HVdXVzp06ICBgQEzZ85ETU1N6WFz\n1KhRdOrUiZYtWzJjxgzOnj3Ls2fPPlWRiikcySxtiV/h55cvX6Zq1arMnj2bRo0aYWtry9SpU8nL\ny5MepKtXr06VKlU+TsbfUbdu3ejSpQvLli1TGhyJi4vj+vXruLu7Y2RkhJGREQsXLuS3334jLi6O\n7t278+effxIfHw8UvE+hr69fLu+Nr6tWrRoAMTExhISE4OHhQbNmzTA0NMTd3Z1z587x5MkTTp8+\nXWrdlkXtYxTiY7p16xZr167ljz/+QCaT0a5dO+bNm0edOnU4cuQIBw8eRC6Xs3fvXnJzc+nduzdu\nbm7l6ikdYMyYMXz99ddKn2lpaREfH8/69evx8/OTPs/NzUVPT0/6veiTr76+PjVq1CA+Pp6mTZv+\n+xl/BzKZDAsLC2bMmEFeXh4RERE0a9YMHR0dpXQdOnTgzp07rFu3jvj4eKKiokhNTZWm7WQyGfr6\n+p+iCG/l1KlTqKio0KlTJwBatWpF7dq1OXr0KN26dUMmk9G2bVspvaamJg0bNiQuLo5u3boBlNvy\nfag6tLW1ZevWraSmppKens6jR4+wtLT8BCX68LS1tZWWd1StWvWNHbPw73jTtViWmJgYqlatSsOG\nDaXPjI2N/9X8/hM2NjbY2NiQmZnJlStX2L9/P2vXrsXAwIDk5GTmz5+vtBQgJydHaVlD0b7I0NAQ\nhUJBQkJCuSlrYUCbmppKnTp1im1PTk4GCv5jqi+//FLp3j5o0KCPk8kPZObMmQwePJjdu3fTokUL\noCDg1dTUxMDAQEpnYGBA9erViY+Px8rKiq+++oqzZ8/i7OzMr7/+io2NzacqwjspXD7zxRdfkJ+f\nT9++fZW2y2Qy/vzzT+Li4v5R3VaogPfFixdMnz4dR0dHFi5cSHJyMgsXLmTz5s3Mnj0bKJhe1NPT\nIyAggMjISDw9PenUqZPUAZYXOjo61K9fv9jnCoWCadOmYWZmJn2Wn5+v9JSqqqpa7G/U1dX/vcy+\nh9atW6OmpsbNmzcJDQ0tMcg5cOAAq1atol+/ftK6s4kTJyqlqVSp0kfK8bs7deoUr169Uup08vPz\n+e2336T1xq+vRVMoFEr1qKGh8XEy+w98iDps2rQpzZo149y5czx9+pQuXboUWwP8KaWmpkpTw4XU\n1NRKfFB+PZhVUyvezZanUcHXvU9Zy7u3uRaLKlo+VVXVYvVWnuoxOjqao0ePMm3aNKBgtMza2hpr\na2tGjRolLaNZsmSJ0uBHfn6+NLIGyvePwgfS8vS/mRoZGaGiokJkZGSxmSQouMdra2tjYGBQ4lcm\nfk709fUZPXo0AQEBzJkzByj4etaSKBQKqb3a2tqyb98+vvnmGyIiIpgyZcpHy/P7iImJASAxMRFN\nTU1pZqJQfn4+tWvXJjw8/B9de+WnFX8AWVlZjB49GhcXF/T19WnTpg1WVlZKU9+f+/SigYEBT548\noX79+tLPzp07uXbtmpSm6FvHCQkJZGZmSmtjyhsVFRW6dOlCSEgI4eHhJQZLwcHBjB49Gjc3N+zt\n7dHS0uLp06fl6mZTmj///JN79+4xffp0duzYIf34+PiQk5PDyZMngYIF+IUyMzNJTEykefPmnyrb\n7+RD1aGtrS2hoaFcuHCh3C1nCAwMxMfHR/o9MzMTbW1tKZgt+mLPw4cPy92M0buoqGV9m2tRXV29\nWPkKNWnShBcvXiiNht67d++jlqEseXl5/PLLLyXmSVNTEx0dHXR0dEhJSZHuHfr6+vj6+kqBBij3\nRXfv3kVdXb1cLaXS1tame/fubNy4sdgDV2ZmJjt37qRv3740bNiQ6OhopT5m0aJFSi88fw6GDx9O\nnTp1WL9+PTKZjEaNGvHixQtpyQIUrHl9/vy59JBaGPcEBwdjYGBQ7mZ3S3Po0CFatmxJp06dePHi\nBa9evZLaKsDKlSvJzMz8x3VboQLeWrVq0atXL3bs2IGHhwcjR45kx44dSm+sfu7Ti46OjuzevZuj\nR4+SmJhIQEAAhw4dUgpot2/fTmhoKFFRUXh6emJubq40DVfeWFhYcOjQIbS1taWp+6INWVtbm4iI\nCBISErh79y7fffcdMplMeqkrPz+/3Aa/p06donr16vTv35+mTZtKP4Vrjgu/B/TEiRMcO3aMuLg4\nFi9ejL6+Ph07dvzEuX97/7QOc3JypDR2dnZcv36dxMREunbt+tHLUJb27dtz7do1rly5QnR0tPR2\nfq1atdDT02PHjh08fPiQY8eO8dtvv5W5r/LcXuHDlrU8eZtr0cjIiLNnzxIZGUlkZCT+/v5SQG9g\nYICZmRlLliwhOjqaK1euKG3/1AwNDenatSszZ87k+PHjPHz4kMjISH766SdiYmLo168fQ4cOxc/P\nj5CQEB48eMCyZcu4fPmy0v1jw4YNXLt2jTt37rBixQp69epV7ta5urm58eLFC1xdXbl27RqPHz/m\nt99+Y/z48ejr6zNmzBh69OhBVlaW9MLTiRMnOHXqlDSbq6mpSWxsrNI3zJRHampqzJo1i8ePHwPQ\noEEDunbtiqenp9ROPT09adeunTRIoqWlhampKZs3by63yxkyMzNJSUkhJSWFmJgY1q1bx5kzZ5g6\ndSqNGzemU6dOeHh48L///Y+oqCjc3d1JS0ujdu3ab6zb0nyWSxpKm3JLTk5mxIgRGBoaYmZmhoOD\nA+Hh4dy4cUMp3evK883ndTY2NqSlpbFx40ZSUlJo3Lgxy5cvVxoNHD58OD/99BNJSUl06dKFuXPn\nfsIcv5mpqSl5eXlK01NFbyIzZsxg4cKFODk5oaenx6hRo9DV1ZVGIsrzf3Bw+vRp7OzsSlxSMmDA\nANzd3dHS0sLOzo6goCBiYmJo3749q1atKlfTiG/yT+uw6GyEnp4ehoaG1K9fv9wt4TA3N8fJyQkP\nDw+ysrKwtrZm5MiRyGQy5s2bh7e3N0OGDMHExAQXFxdCQkKkv329bZbn9goftqzlyZuuRQ8PD9zc\n3IiJiWH8+PHo6uoybdo0/vvf/0rp5s+fj5eXF87Ozujq6tKnTx+2b9/+MYtRJi8vL7Zu3crmzZtJ\nSkpCQ0OD9u3b4+/vT506dXByciI7O5vly5eTkZFBixYtWLNmDbVr15b20atXLzw9PcnMzMTOzq7c\nfTMMFAxubdq0iS1btuDp6cnTp0+pW7cuPXr0YPjw4WhoaFCpUiVWrlzJihUr2L9/P3Xr1mX+/Pm0\nbt0aKBg8KrxPFi4DKa86duyIra0tp0+fRiaT4e7ujre3N99++y2qqqpYWFjg5uam9Dd2dnZcvHix\n3M2WFVq9ejWrV69GJpOhra1Ny5Yt8fX1pU2bNgB4eHjg4+ODq6srMpkMuVzOzJkzgYLlOmXVbWlk\n6enpn0+09/+tXr2a2NhYVq9eDRRMwZ09exZ7e3v27NnD3r17pbRz584lJSWFgIAAjhw5woYNG5S+\nd3HixIm0a9eO8ePHf/RyCAIUtMEOHTowZsyYT52VTyo/P58BAwYwa9ascremXhCys7O5cuUKnTt3\nlgZOzpw5w9q1azl48OAnzt2HIZfL8fX1pX379p86K4LwwX2WI7zt27cnKCiIK1euoKOjQ3BwMD16\n9EBLS4vk5GSuXLlC/fr1OXPmDOHh4WWuXynv04tCxSfaIFy4cEH6wvyiL2QKQnmhoaHB4sWL6d+/\nP3369CE1NZWNGzcW+zYdQRDKp88y4C1tyk1dXZ3r16/z3XffAdC9e3e8vLxYsGCBtFbwc5teFCo+\n0QZh165d3L9/n4ULF/6fPxdC+aSiosLy5ctZvXo1O3fupGrVqtjb2xf7xhhBEMqnz3JJgyAIgiAI\ngiC8rc/nrRhBEARBEARB+AdEwCsIgiAIgiBUaCLgFQRBEARBECo0EfAKgiAIgiAIFZoIeAVBEARB\nEIQKTQS8giAIgiAIQoUmAl5BEARBEAShQhMBryAIgiAIglChiYBXEARBEARBqNBEwCsIgiAIgiBU\naCLgFQRBEARBECo0EfAKgiAIgiAIFZoIeAVBEARBEIQKTQS8giAIgiAIQoUmAl5BEARBEAShQhMB\nryAIgiAIglChiYBXEARBEARBqNBEwCsIgiAIgiBUaCLgFQRBEARBECo0EfAKgiAIgiAIFZoIeAVB\nEARBEIQKTQS8giAIgiAIQoUmAl5BEARBEAShQhMBryAIgiAIglChiYBXEARBEARBqNBEwCsIgiAI\ngiBUaCLgFQRBEARBECo0EfAKb0UulzN06FCcnJykHy8vr0+dLYmnpyc7dux4r31kZmYyceLEUrc7\nOTmRmZn5xnTPnz9nypQpvHz5En9/f+RyOYcPH1ZKk5WVhaWlJdOnTwfA39+f48ePAwXn+u+//36n\nvBetn+HDhzNo0CBGjRrF3bt3ldLFxMQgl8vZunXrO+2/PFEoFAwdOrTU7Y8ePcLS0vK9j3PgwAGC\ngoJK3BYcHCydw6Lp7t69y9KlS0vd54QJE0hKSipx27Zt23BycmLYsGE4OjqyZs0aXr169Z6lEErj\n5uZGfHw8AK6urm+85q5evYqjoyNQ0N+Udg0V9hNHjhyRru/39SH6t/Li2bNnuLi4fNB9vk39fSiR\nkZH069fvjenK6j+ET0PtU2dA+Hz4+vqipaX1qbNRIplM9t77yMjIKBYgFhUYGAgUBFRlpfvpp59w\ncHCgUqVKANStW5fjx4/Tp08fKc3Zs2epUqWKlO9x48a9d/5fr58dO3bg7e3Npk2bpM/27dtHjx49\nCAoKwsnJCVVV1fc+7sd2+/ZtjI2N//Xj3Lx5ky+++KLEbf379y8xXcuWLQkKCiI8PJyuXbsW+zuZ\nTFZiWz1z5gwhISH8/PPPaGhokJOTw5w5c/D392fSpEkfqERCUStXrpT+feXKFfLz89/6b8vqbwr7\niQ/pQ/Rv5cWFCxdKvDbex7vW38dQVv8hfBoi4BXeWmkdSpcuXbCwsCA6OpqFCxeSnZ3N2rVryc7O\nRl1dnQkTJtCpUyeOHDnC2bNnycnJISkpCT09PQYNGsSePXt48OABjo6ODBs2DCgYJZk3bx6GhoZK\nx3rx4gXe3t7cunULVVVVLCwspIDg1q1bnDt3jqdPn9K0aVMWL15M5cqVOXToEAcOHCA3N5eMjAxG\njBjBgAEDOHLkCAcPHuTly5dUrVoVgJcvXzJ8+HC2bt2KioryBIhcLufkyZMsWrSo1HRPnjzhwoUL\nzJo1Cyi4UZmZmRESEsJff/2Frq4uAEePHsXe3l4aYfL09OSLL76Qyg+QkpLC5MmTGThwIAMHDiQu\nLg4fHx/+/vtvFAoFgwcPVgqii9bPq1evSEpKUgqAnz9/zokTJ9i8eTNRUVH8+uuv2NraArBo0SL+\n+OMPAHJzc4mPj2fdunU0adKEpUuXkpaWRmpqKvr6+nh5eaGjo0O/fv0wNjYmJiaGSZMmYWFhIR0r\nLCwMPz8/FAoFVapUYc6cOTRv3pzz58+zadMm8vLyqFq1Km5ubhgZGeHv78/Dhw95+PAhycnJGBsb\nI5fLOXr0KI8ePcLV1VXKa0hICN26dSv1OFWrViUvL48ffviByMhInj17xpQpU7CysiI1NfWtyjNx\n4kTCwsKIiIigUqVKDBw4UKkt+Pv78/fff9OxY8di6RwcHFi2bNk73dRTU1NRKBRkZ2ejoaGBhoYG\ns2bNIi0tDSiYffjxxx+Jjo5GJpPRqVMnJk2ahKqqKnK5nFOnTkl1Xfh7TEwMK1asQFNTk+zsbDZv\n3szx48fZuXMnKioqaGtr4+7ujp6eHmFhYWzevJnc3FwqV67MlClTaN26NcnJybi5ubFq1Spq164t\n5TckJITAwEACAgIAGDRoEDY2NowbN44nT54wevRojI2N6dKlC/369eP27duMGTOG/fv3U69ePX7+\n+WeSkpI4deoUJ0+epHLlyixdupT4+Hj8/PwAGDBgACtWrKBx48ZvbFebN28mNDSUly9fkp2dzZQp\nU7C0tMTf35/Y2Fipvps3b868efOoWrUq/fr144cffmDv3r0ATJo0iZUrVxIVFcXWrVvJzc0lLS2N\nXr16MX78eKX6ys/P5/bt2zg7O/P8+XPkcjlTp05Vqo+ifv31V9atW8eqVato1KgRBw8eZN++feTn\n56OlpcWsWbMwMDDgxo0brF69mry8PGQyGaNGjcLKygp4v/6tWrVqrF+/vtTjvu7QoUMltpP9+/ez\nZ88eVFRUqFmzJrNmzaJRo0Z4enpSqVIl7t69S2pqKl9//TU6OjqEhYWRmprK999/j4mJidR2xowZ\nw4sXL1i4cCGJiYmoqKhgaGjI3LlzpeuxsF8/ceIEZ8+exdPTE09Pz2LpFy1aJNXfqlWrAPD29ubx\n48e8evUKW1tbRo0axaNHj5g0aRIdO3bk9u3bvHr1iqlTpxIcHExCQgItW7Zk8eLFJT5cBAUFsWvX\nLqpVq0bTpk2VrtuS+pMbN24o9QtWVlal9jvCxyMCXuGtTZo0SSm4++mnn9DW1ubVq1d069YNLy8v\n0tPTGTJkCD4+PhgZGREbG8uECRPYsmULUPDU+8svv1CnTh0cHR05ffo0vr6+REdH4+zsLAV8pY2S\n+Pn5kZuby969e8nLy2Py5Mlcu3aN/Px8kpOT8fX1RV1dnVGjRnHu3DksLS05ePAgq1atokaNGty+\nfZspU6YwYMAAAOLi4jh06BCampokJSXh6OjI9u3bSz0HMpmMBQsWlJouJCSEjh07Kp0nNTU1vv76\na06cOMGIESN4/PgxWVlZNG3aVAp4X+9knzx5wvz583F2dsbOzo5Xr14xZ84cFi5cSIsWLcjMzMTF\nxYUmTZpIo52TJk1CJpORnp6OhoYG5ubmLFiwQNrn8ePHMTAwoHHjxvTq1Ytdu3ZJQeT8+fOldPPm\nzcPExAQTExN2795N27ZtGT58OFAwDXzs2DGpnpo1a8aSJUuU8p6amoqHhwcbNmygefPmnDt3jnXr\n1uHm5sayZcvYtGkT9erV4/fff2fmzJlSwHHz5k127NiBmpoavXr1Qk9PDz8/P0JDQ1mzZo2U14iI\nCCZOnFjicdavX8/s2bPJyclBLpczZ84czp8/z5o1a7CysuLMmTNvXZ7Q0FCaNWtWLNgtrC+ZTIal\npWWxdMbGxiQnJ5OUlIS+vn4pLUlZr169CA8Px97eHkNDQ9q0aUO3bt346quvgIIbuLa2Nr/88gu5\nubnMmDGDwMBARo4cWeZ+4+LiOHDgAHp6ekRFRbFu3Tq2b9+Orq4uu3btYvPmzQwdOhRfX182bNhA\njRo1uH//Pq6urgQHB1OnTp0Sr0W5XI6npyeZmZlkZGTw/PlzIiIiGDduHGFhYVhZWdGqVStCQ0Pp\n168fFy9epFatWly5coX//Oc/hIWFMWvWLB4+fMjvv/9O165duXr1Ki9evCArK4ukpCTU1NSUgt3S\n2tWcOXOIiIjAz88PDQ0NTp06hb+/v7Ss5fbt22zfvh0dHR0WLFjApk2bmDJlilSPCxYs4OjRo/j6\n+lKjRg08PDzw8PCgQYMGJCcn07dvX4YMGVLsHKSkpLBhwwbU1NRwdXXlwIEDUr9S1IkTJ9i6dSsb\nNmxAV1eXa9eucezYMfz9/alcuTKXLl1i9uzZ7N69G39/f4YOHYqNjQ0xMTHs378fKyurD9K/lXXc\nokprJ927dycwMJBNmzahra3NkSNHmDVrlvT30dHR/Pzzz6Snp9OzZ09mzpzJxo0b2b17N1u3bsXE\nxIScnBwePHhAs2bNOHbsGFlZWQQGBqJQKPjhhx949OgRgwYNws3NjQkTJqCiosL+/ftxdnbm3Llz\nJaYvWn9aWlpMnDiRoUOHYm5uzsuXL5k2bRoNGjTAyMiIpKQkunXrxvfff8+yZctYsWIFO3fuRE1N\nDQcHB27fvk2bNm2KnY+NGzeyc+dOatasyfLly6X+uqz+JCwsTOoX3tSPCh+HCHiFt1bWkoZ27doB\n8L///Y+GDRtiZGQEQNOmTWnTpg3Xrl0DwMjISBrlrFevHnK5HID69euTk5NDdnY2lStXLjUPERER\nuLm5IZPJUFNTY8OGDQAcOXIECwsLaRlBs2bNePr0KVWqVMHHx4ewsDASExOJiooiKytL2l/z5s3R\n1NQESh/Bfl1Z6RISEqhfv36xz3v27MnixYsZMWIEx44do1evXmUew83NDT09Pezs7AD4888/efTo\nkTSaAZCTk0NUVJQU8BbWT1RUFFOnTqV169Zoa2tL6YODg/nPf/4DQI8ePVi3bh23bt1S6uBXrlxJ\nVlaWdJzBgwdz/fp1duzYwYMHD7h//77ScoLCei/q1q1bNG3alObNmwNgZWWFlZUVQUFBmJqaUq9e\nPQBMTEzQ0dHh3r17yGQy5HK5NNJep04dzMzMgIK2kZGRAUBsbCz16tVDXV291OM8evQIdXV1aWSs\nefPm0kjpPylPacpqB/Xq1SM+Pv6tA95q1aqxdu1aHj58yNWrV7l69SrTp09nwIABTJ48mUuXLrFx\n40YA1NXV6d+/P7t27XpjwKurq4uenh5QcO2YmZlJ119hEBcUFERKSorS0gkVFRUSExNLnZKtXLky\npqamXL58mb///hsHBwcOHDhAZmYmISEhjBw5khYtWrBq1Sry8vK4fPkyzs7OXL58ma5du/L06VOM\njIywtLTk4sWLNGzYEF1dXWrUqMG1a9eIjo6me/fuSscsrb4B3N3dOXbsGA8fPuTOnTtK13j37t2p\nWbMmAH379mXlypVSwPs6mUwm9RcnTpyQHkizs7OLpbO3t5f6Knt7ey5cuFAs4I2MjOTixYvMmDFD\nOu/h4eEkJiYyZswYKd2zZ8/IyMjAxsaGH3/8kbCwMExNTaV3BWQy2Xv3b6Ud99mzZ1SvXl36rLR2\nsmbNGmxsbKQ+pXfv3vj4+PDo0SNkMhnm5uaoqqpSq1YtqlSpQqdOnYCCa6Hw+o2IiKBjx45AwbXm\n6+vLxIkTMTU1ZciQIVLfWa9ePcLDw2nYsCEpKSnI5XIePXpUavpCWVlZXL9+nWfPnkkzBVlZWURH\nR2NkZISamhrm5uYANGjQgLZt20rnp3bt2jx79qxYmyg8H4VtyMHBgfDwcODN/Umht00n/LtEwCt8\nEFWqVAFKDgIUCgWvXr1CTU0NdXV1pW3vuoZUTU25yf71119oaGgU21b4BP7kyRNcXFzo378/7dq1\nw9raWuqsiub7daGhofj7+wMFwVfR9X5lUVFRQaFQKH0mk8kwMjIiLy+PqKgozpw5g5+fHyEhIaXu\nZ+7cufz888/s2LGDYcOGoVAoqFatmtJoW0pKitKNqtCXX36Jm5sbS5YswdjYGH19fW7cuEFsbCzb\nt2+XXn5RV1dn165dUsC7Y8cObty4gZ+fn3T+1q5dK72k0bFjR/Ly8pTquPBmUZSamlqxEev79++T\nn59frH3k5+dLL2a9Xrev/w4F9VI4clfacapUqVKsLRQe95+UB2DatGmkpKQAFJveLolCoXintr11\n61a++uor2rRpQ/369enbty83b95k6tSpTJ48GYVCoZRPhUJBXl6e9HvhttzcXKX9Fi3P6+ezcGmR\nQqGgY8eOSiP1jx8/lgKe0lhaWnLhwgUyMzMZPnw4CQkJnD9/nri4ONq3b4+KigotWrQgNDSUzMxM\nevbsycaNGzl//rxUh5aWlowfP55GjRohl8upXr06ly5dIjIykjlz5igdr7T6zkWqX6IAAAfkSURB\nVM3NZebMmQwbNgwzMzPat2/PDz/8IKUpOtvypnrJysrCyckJKysr2rVrR58+fQgJCSmxX3t9v6/3\nbQDVq1dnyZIlzJ07ly5duqCvr09+fj729vZMnjwZKKi7J0+eUKNGDRwcHDA3N+fSpUtcunSJgIAA\n6Xp93/6ttOO+3oeU1k4K/6aootfv6+Uv7fq1t7cHCoLa4OBgrl69yu+//87kyZOZOXMm1tbWDBw4\nkEOHDtGoUSMcHBzemL5Q4TWxadMm6eEgPT2dSpUqkZaW9sb7T35+PsHBwQQHBwMFa/KbNGmiVO6i\n9f6m/qSsdK/fJ4R/n/iWBuGDMjY2JiEhgcjISKDghnTjxg06dOjwQfbfsWNHjh49Sn5+vvRiz/Xr\n10tNf+/ePWrWrImzszNyuZywsDCAEjsbVVVVqcPs1q0bgYGBBAYGFgt2i6Z7XaNGjXj48KH0e9Eg\nr2fPnqxcuRIDA4NiN5nXO8nWrVvj7u7O5s2buX//PgYGBmhoaHDixAmg4Ebn5OQkrbt9na2tLa1b\nt8bHxwcoGMXr2bMnhw8f5uDBgxw8eBAfHx/OnTvHkydPOHnyJEFBQaxYsUJphP3y5cs4OjrSo0cP\ntLW1uXLlyhs7aiMjI+Lj44mNjQXg/PnzzJ8/HxMTEy5fviydn4iICP766y+MjY3fenS96AsvpR2n\nrBd83qU8qqqq0s181apVUnswNzdXym/RdFBQl0lJSSWujSxNTk4O69atIz09XfosLi5OWsNuZmYm\nLf3Iyclh//79mJqaAqCjoyO9RHnu3LlSj2FiYkJERIQUuO/bt4+1a9dK9ZKQkADAxYsXcXJyIicn\np8w8d+3alYiICKKjo2nVqhVyuRw/Pz86d+4sBQUWFhb4+vpiamqKpqYmBgYGbNu2TRq91dXVRVtb\nm+DgYMzMzJDL5Zw7d46MjAxpJLdQafV948YNjIyMcHR0pF27dpw/f16pTsPCwsjMzEShUHDgwAFp\nhK8oFRUVcnNzefDgAc+fP2fChAl07dqVa9eukZOTU+x6z8/P59SpU+Tm5vLy5UuOHj0qjWgW1bBh\nQzp06MA333yDh4cH+fn50hrfwno4cOAArq6uALi4uPDHH3/Qu3dv5syZI43AluZd+reyjltUae3E\nzMyMM2fOSG308OHDaGtr07Bhw7e+fm/fvk3btm2Bgj5p4cKFmJmZMXnyZMzMzKS67d69O1FRUZw/\nf156T6Gs9IX1V61aNYyNjaWHhMzMTMaNG0doaGixvJSUZ5lMRv/+/aVr/fvvv0cul3P58mX++usv\noGA2sVBZ/UnRfuGf9KPChydGeIW3UlYQUXSbtrY2S5cuxdvbm+zsbGmNXMOGDbl582ax/RT9vei/\nS3tpbezYsaxYsYJhw4aRl5eHra0tVlZWUkf/usKvBBs4cCA6OjpYWFhQu3ZtHjx4UOyYderUwdDQ\nkMGDB+Pv719s+UZh2qLpAgICqFGjhpTGwsKC7du3k5+fL63zLPy7Hj16sGHDBry9vYvts6TzYGBg\ngLOzM+7u7mzZsgVvb298fHzYtm0beXl5jB8/XhqdLal+Zs6ciZOTE6dPnyYkJKTY1yiZmJjQunVr\ndu/ezZ49e9DV1WX69OlSR9y/f39cXFxYvXo1W7ZsQUdHB2tra+ncFfX6y00LFy7E09OTvLw8qlWr\nhpeXF40bN2b27Nn897//JS8vjypVqrBixQqqVq1a6rcXFD0nKSkpaGhoSA8LtWrVKvE4hee+pLp7\n2/IAdO7cmeXLlwMUWzpQNL+vp7t79y4NGjSQlhK8DRcXF1RUVBg7diwymQyFQkGrVq2kr/6bMWMG\n3t7eODo6kpubS+fOnRk9erS07ccff6R69eqYmppSp06dYuWGgmnwKVOmMHXqVKCgHc+bN4/atWsz\nd+5cvv/+e/Lz81FTU5MefEp7aQ0KlmE0adIETU1NVFRUMDU1ZcmSJdIyAyi4Hry9vaXAyszMjKCg\nIKVlNJaWluzcuZMWLVoAUKlSJWkE+G3aVY0aNTh79ixDhgxBS0sLGxsbTp06xYsXLwCoWbMmbm5u\npKWl8dVXXzFq1Khi59/Kyorx48dLLxt+88031KpVi7Zt29KyZUsSExNRV1dXul7r16/P2LFjpa8Y\nLFymVNK1PHr0aEJDQwkMDGT48OGMGDECV1dXZDIZ1apV48cffwRgypQprFixgg0bNiCTyRg7dmyZ\ny2LepX8zMzMr9biRkZF4eXkRGBhYZjtxdHRk0qRJKBQKdHR08PHxKfHaff0cyGQy7ty5Q8uWLaVt\nvXv35vr16wwePJjKlSujr68vLZ9QU1PD2tqatLQ0qR8uK72VlRXjxo3D29ubRYsWsXz5coYOHUpu\nbi52dnbY2dlJSy9ez9ebNGvWjMmTJ/Ptt9+iqalJq1at3qo/KdovlJQuMTHxjccWPixZenp6+fou\nD0H4zC1dupSOHTvy9ddff+qsCJ+Ap6cnNjY2dO7cudi2iRMn4u7uTt26dT9Bzv7v8ff35+nTp8WW\nRwjlW1ZWFuPHj2fOnDnS+yCC8L7EkgZB+MAK39h+05SwUPHcvXsXVVXVEoNd4eN721E8ofy4ePEi\nffr0wcTERAS7wgclRngFQRAEQRCECk2M8AqCIAiCIAgVmgh4BUEQBEEQhApNBLyCIAiCIAhChSYC\nXkEQBEEQBKFCEwGvIAiCIAiCUKH9P7HCEd9xHJ42AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x91ebcc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot ride data\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "def func(x, pos):  \n",
    "   s = '{:,.0f}'.format(int(x)/1000)\n",
    "   return s\n",
    "\n",
    "ax10 = bike_share_monthly_minutes_count.Registered.plot(kind='area', stacked=False, grid=False, figsize=(10,6), fontsize=14)\n",
    "ax10 = bike_share_monthly_minutes_count['Casual'].plot(kind='area', stacked=False, grid=False, figsize=(10,6), fontsize=14, \\\n",
    "                                                        alpha=0.4)\n",
    "ax10.set_xlabel('', size=14)\n",
    "ax10.set_ylabel('Rides (thousands)', size=14)\n",
    "ax10.tick_params(\n",
    "    axis='both',\n",
    "    which='both',      \n",
    "    bottom='off',      \n",
    "    top='off',         \n",
    "    right='off',\n",
    "    left='off',\n",
    "    labelbottom='on')\n",
    "\n",
    "date_fmt = 'Jan'\n",
    "formatter = mdates.DateFormatter(date_fmt)\n",
    "ax10.xaxis.set_major_formatter(formatter)\n",
    "y_format = tkr.FuncFormatter(func)  # make formatter\n",
    "ax10.yaxis.set_major_formatter(y_format)\n",
    "legend = plt.legend(loc=2, fontsize=14)\n",
    "\n",
    "ax10.text(0.13, -0.15, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
    "          fontsize=12, transform=ax10.transAxes) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Casual         620706\n",
       "Registered    2326215\n",
       "dtype: int64"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_share_monthly_minutes_count.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x9e87e10>"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax1.text(0.13, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
    "          fontsize=12, transform=ax1.transAxes) "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}