03_Analysis of BiciMAD trips.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import json\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "TRIPS_STATIONS_PATH='/Users/nicolaesse/Documents/Data science/Py/Analisi biciclette Madrid/Trips analysis/Trips_stations.csv'\n",
    "TRIPS_HOURLY_PATH='/Users/nicolaesse/Documents/Data science/Py/Analisi biciclette Madrid/Trips analysis/Trips_hourly.csv'\n",
    "STATIONS_PATH='/Users/nicolaesse/Documents/Data science/Py/Analisi biciclette Madrid/Stations analysis/df_stations.csv'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unplug_Month</th>\n",
       "      <th>user_type</th>\n",
       "      <th>idplug_station</th>\n",
       "      <th>idunplug_station</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  unplug_Month  user_type  idplug_station  idunplug_station  count\n",
       "0   2017-05-01          0               1                 1     13\n",
       "1   2017-05-01          0               1                 2      1\n",
       "2   2017-05-01          0               1                 5      1\n",
       "3   2017-05-01          0               1                13      2\n",
       "4   2017-05-01          0               1                15      1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_trip_stations = pd.read_csv(TRIPS_STATIONS_PATH)\n",
    "df_trip_stations.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>address</th>\n",
       "      <th>id</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>number</th>\n",
       "      <th>total_bases</th>\n",
       "      <th>neighbours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Puerta del Sol nº 1</td>\n",
       "      <td>1</td>\n",
       "      <td>40.416896</td>\n",
       "      <td>-3.702425</td>\n",
       "      <td>Puerta del Sol A</td>\n",
       "      <td>1a</td>\n",
       "      <td>24</td>\n",
       "      <td>Centro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Puerta del Sol nº 1</td>\n",
       "      <td>2</td>\n",
       "      <td>40.417001</td>\n",
       "      <td>-3.702421</td>\n",
       "      <td>Puerta del Sol B</td>\n",
       "      <td>1b</td>\n",
       "      <td>24</td>\n",
       "      <td>Centro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Calle Miguel Moya nº 1</td>\n",
       "      <td>3</td>\n",
       "      <td>40.420589</td>\n",
       "      <td>-3.705842</td>\n",
       "      <td>Miguel Moya</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>Centro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Plaza del Conde Suchil nº 2-4</td>\n",
       "      <td>4</td>\n",
       "      <td>40.430294</td>\n",
       "      <td>-3.706917</td>\n",
       "      <td>Plaza Conde Suchil</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>Chamberí</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Calle Manuela Malasaña nº 5</td>\n",
       "      <td>5</td>\n",
       "      <td>40.428552</td>\n",
       "      <td>-3.702587</td>\n",
       "      <td>Malasaña</td>\n",
       "      <td>4</td>\n",
       "      <td>24</td>\n",
       "      <td>Centro</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         address  id   latitude  longitude  \\\n",
       "0            Puerta del Sol nº 1   1  40.416896  -3.702425   \n",
       "1            Puerta del Sol nº 1   2  40.417001  -3.702421   \n",
       "2         Calle Miguel Moya nº 1   3  40.420589  -3.705842   \n",
       "3  Plaza del Conde Suchil nº 2-4   4  40.430294  -3.706917   \n",
       "4    Calle Manuela Malasaña nº 5   5  40.428552  -3.702587   \n",
       "\n",
       "                 name number  total_bases neighbours  \n",
       "0    Puerta del Sol A     1a           24     Centro  \n",
       "1    Puerta del Sol B     1b           24     Centro  \n",
       "2         Miguel Moya      2           24     Centro  \n",
       "3  Plaza Conde Suchil      3           18   Chamberí  \n",
       "4            Malasaña      4           24     Centro  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stations = pd.read_csv(STATIONS_PATH, sep=';', encoding='latin-1')\n",
    "df_stations.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unplug_Day</th>\n",
       "      <th>unplug_Hour</th>\n",
       "      <th>user_type</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>109.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   unplug_Day  unplug_Hour  user_type  count\n",
       "0  2017-05-01          1.0        0.0   39.0\n",
       "1  2017-05-01          1.0        1.0  126.0\n",
       "2  2017-05-01          1.0        3.0   29.0\n",
       "3  2017-05-01          2.0        0.0   18.0\n",
       "4  2017-05-01          2.0        1.0  109.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_trips_hourly = pd.read_csv(TRIPS_HOURLY_PATH, sep=',', encoding='latin-1')\n",
    "df_trips_hourly.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory data analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5478168"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Total number of trips\n",
    "df_trip_stations['count'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_type</th>\n",
       "      <th>idplug_station</th>\n",
       "      <th>idunplug_station</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>586011.000000</td>\n",
       "      <td>586011.000000</td>\n",
       "      <td>586011.000000</td>\n",
       "      <td>586011.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.188874</td>\n",
       "      <td>87.843836</td>\n",
       "      <td>88.693888</td>\n",
       "      <td>9.348234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.698160</td>\n",
       "      <td>51.643694</td>\n",
       "      <td>51.406950</td>\n",
       "      <td>12.579709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>132.000000</td>\n",
       "      <td>133.000000</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>266.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           user_type  idplug_station  idunplug_station          count\n",
       "count  586011.000000   586011.000000     586011.000000  586011.000000\n",
       "mean        1.188874       87.843836         88.693888       9.348234\n",
       "std         0.698160       51.643694         51.406950      12.579709\n",
       "min         0.000000        1.000000          1.000000       1.000000\n",
       "25%         1.000000       44.000000         45.000000       2.000000\n",
       "50%         1.000000       88.000000         89.000000       5.000000\n",
       "75%         1.000000      132.000000        133.000000      12.000000\n",
       "max         3.000000     2008.000000       2008.000000     266.000000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_trip_stations.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Distinct of user_type\n",
    "df_trip_stations['user_type'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{22, 2008}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plug stations not in df_stations\n",
    "a=df_trip_stations['idplug_station'].unique()\n",
    "b=df_stations['id'].unique()\n",
    "set(a) - set(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{22, 2008}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# unplug stations not in df_stations\n",
    "a=df_trip_stations['idunplug_station'].unique()\n",
    "b=df_stations['id'].unique()\n",
    "set(a) - set(b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Station 2008"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unplug_Month</th>\n",
       "      <th>user_type</th>\n",
       "      <th>idplug_station</th>\n",
       "      <th>idunplug_station</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>76451</th>\n",
       "      <td>2017-06-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81354</th>\n",
       "      <td>2017-06-01</td>\n",
       "      <td>3</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152803</th>\n",
       "      <td>2017-08-01</td>\n",
       "      <td>3</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187928</th>\n",
       "      <td>2017-09-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194129</th>\n",
       "      <td>2017-09-01</td>\n",
       "      <td>3</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267229</th>\n",
       "      <td>2017-11-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273263</th>\n",
       "      <td>2017-11-01</td>\n",
       "      <td>3</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299024</th>\n",
       "      <td>2017-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328541</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423096</th>\n",
       "      <td>2018-04-01</td>\n",
       "      <td>3</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>481368</th>\n",
       "      <td>2018-06-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545947</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       unplug_Month  user_type  idplug_station  idunplug_station  count\n",
       "76451    2017-06-01          1            2008              2008      1\n",
       "81354    2017-06-01          3            2008              2008      2\n",
       "152803   2017-08-01          3            2008              2008      4\n",
       "187928   2017-09-01          1            2008              2008      2\n",
       "194129   2017-09-01          3            2008              2008      4\n",
       "267229   2017-11-01          1            2008              2008     14\n",
       "273263   2017-11-01          3            2008              2008      8\n",
       "299024   2017-12-01          1            2008              2008      3\n",
       "328541   2018-01-01          1            2008              2008      1\n",
       "423096   2018-04-01          3            2008              2008      1\n",
       "481368   2018-06-01          1            2008              2008      1\n",
       "545947   2018-08-01          1            2008              2008      1"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Trips with idplug_stations=2008\n",
    "df_trip_stations.loc[df_trip_stations['idplug_station'] == 2008]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "42"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# count trips with idplug_stations=2008\n",
    "df_trip_stations['count'].loc[(df_trip_stations['idplug_station'] == 2008) | (df_trip_stations['idunplug_station'] == 2008)].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_id</th>\n",
       "      <th>ageRange</th>\n",
       "      <th>idplug_base</th>\n",
       "      <th>idplug_station</th>\n",
       "      <th>idunplug_base</th>\n",
       "      <th>idunplug_station</th>\n",
       "      <th>travel_time</th>\n",
       "      <th>unplug_hourTime</th>\n",
       "      <th>user_day_code</th>\n",
       "      <th>user_type</th>\n",
       "      <th>zip_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2581</th>\n",
       "      <td>{'$oid': '5a300b742f38432284ee7845'}</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>803</td>\n",
       "      <td>{'$date': '2017-12-01T09:00:00.000+0100'}</td>\n",
       "      <td>7dfb6e8ca390440579499a9993b3820694cd6d63c08975...</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3206</th>\n",
       "      <td>{'$oid': '5a300b772f38432284ee7b67'}</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>2422</td>\n",
       "      <td>{'$date': '2017-12-01T09:00:00.000+0100'}</td>\n",
       "      <td>7dfb6e8ca390440579499a9993b3820694cd6d63c08975...</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195862</th>\n",
       "      <td>{'$oid': '5a42d7032f384324cc1a8d3d'}</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>618</td>\n",
       "      <td>{'$date': '2017-12-22T11:00:00.000+0100'}</td>\n",
       "      <td>0a4a58417a1492e5beb5d6b89c8e829cf9c8b3a593a2c6...</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         _id  ageRange  idplug_base  \\\n",
       "2581    {'$oid': '5a300b742f38432284ee7845'}         0            1   \n",
       "3206    {'$oid': '5a300b772f38432284ee7b67'}         0            1   \n",
       "195862  {'$oid': '5a42d7032f384324cc1a8d3d'}         0            2   \n",
       "\n",
       "        idplug_station  idunplug_base  idunplug_station  travel_time  \\\n",
       "2581              2008              1              2008          803   \n",
       "3206              2008              1              2008         2422   \n",
       "195862            2008              2              2008          618   \n",
       "\n",
       "                                  unplug_hourTime  \\\n",
       "2581    {'$date': '2017-12-01T09:00:00.000+0100'}   \n",
       "3206    {'$date': '2017-12-01T09:00:00.000+0100'}   \n",
       "195862  {'$date': '2017-12-22T11:00:00.000+0100'}   \n",
       "\n",
       "                                            user_day_code  user_type zip_code  \n",
       "2581    7dfb6e8ca390440579499a9993b3820694cd6d63c08975...          1           \n",
       "3206    7dfb6e8ca390440579499a9993b3820694cd6d63c08975...          1           \n",
       "195862  0a4a58417a1492e5beb5d6b89c8e829cf9c8b3a593a2c6...          1           "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load 201712 usage dataset\n",
    "data = []\n",
    "\n",
    "with open('/Users/nicolaesse/Downloads/BiciMad usage/201712_Usage_Bicimad.json', encoding='latin-1') as f:\n",
    "    for line in f:\n",
    "        data.append(json.loads(line))\n",
    "\n",
    "df_routes = pd.DataFrame(data)\n",
    "df_routes.loc[df_routes['idplug_station'] == 2008]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Station 22"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3677"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Count trips with plug/unplug stations = 22\n",
    "df_trip_stations['count'].loc[(df_trip_stations['idplug_station'] == 22) | (df_trip_stations['idunplug_station'] == 22)].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2017-05-01'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# First trip from/to station 22\n",
    "df_trip_stations['unplug_Month'].loc[(df_trip_stations['idplug_station'] == 22) | (df_trip_stations['idunplug_station'] == 22)].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2017-12-01'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Last trip from/to station 22\n",
    "df_trip_stations['unplug_Month'].loc[(df_trip_stations['idplug_station'] == 22) | (df_trip_stations['idunplug_station'] == 22)].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>address</th>\n",
       "      <th>id</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>number</th>\n",
       "      <th>total_bases</th>\n",
       "      <th>neighbours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Calle Alcalá nº 49</td>\n",
       "      <td>21</td>\n",
       "      <td>40.419234</td>\n",
       "      <td>-3.695461</td>\n",
       "      <td>Banco de España A</td>\n",
       "      <td>20a</td>\n",
       "      <td>30</td>\n",
       "      <td>Centro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Calle Montera nº 48</td>\n",
       "      <td>23</td>\n",
       "      <td>40.419787</td>\n",
       "      <td>-3.701481</td>\n",
       "      <td>Red de San Luis A</td>\n",
       "      <td>21a</td>\n",
       "      <td>24</td>\n",
       "      <td>Centro</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                address  id   latitude  longitude               name number  \\\n",
       "20   Calle Alcalá nº 49  21  40.419234  -3.695461  Banco de España A    20a   \n",
       "21  Calle Montera nº 48  23  40.419787  -3.701481  Red de San Luis A    21a   \n",
       "\n",
       "    total_bases neighbours  \n",
       "20           30     Centro  \n",
       "21           24     Centro  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Station 21 and 23\n",
    "df_stations.loc[df_stations['id'].isin(['21','23'])]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis: global"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graph of number of trips in a month per user_type\n",
    "data_plot_1=df_trip_stations.loc[df_trip_stations['user_type'] == 1].groupby(['unplug_Month','user_type'])['count'].agg('sum').unstack()\n",
    "data_plot_2=df_trip_stations.loc[df_trip_stations['user_type'] == 2].groupby(['unplug_Month','user_type'])['count'].agg('sum').unstack()\n",
    "unplug_Month=df_trip_stations['unplug_Month'].unique()\n",
    "\n",
    "\n",
    "fig, ax1 = plt.subplots(figsize=(20,7))\n",
    "color = 'tab:red'\n",
    "ax1.set_xlabel('months')\n",
    "ax1.set_ylabel('Usuario anual (poseedor de un pase anual)', color=color)\n",
    "ax1.plot(unplug_Month, data_plot_1, color=color)\n",
    "ax1.tick_params(axis='y', labelcolor=color)\n",
    "plt.grid()\n",
    "ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axis\n",
    "\n",
    "color = 'tab:blue'\n",
    "ax2.set_ylabel('Usuario ocasional', color=color)  # we already handled the x-label with ax1\n",
    "ax2.plot(unplug_Month, data_plot_2)\n",
    "ax2.tick_params(axis='y', labelcolor=color)\n",
    "\n",
    "fig.tight_layout()  # otherwise the right y-label is slightly clipped\n",
    "plt.title('Number of trips per user_type', loc='center')\n",
    "\n",
    "plt.show()\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Trips per day of week per user_type\n",
    "DayWeek ={0: \"Mon\",1: \"Tue\",2: \"Wed\",3: \"Thu\",4: \"Fri\",5: \"Sat\",6: \"Sun\"}\n",
    "df_trips_hourly['unplug_DayOfWeek']=(df_trips_hourly['unplug_Day'].map(lambda x : datetime.date(*map(int, x.split('-'))).weekday())).map(DayWeek)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unplug_Day</th>\n",
       "      <th>unplug_Hour</th>\n",
       "      <th>user_type</th>\n",
       "      <th>count</th>\n",
       "      <th>unplug_DayOfWeek</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   unplug_Day  unplug_Hour  user_type  count unplug_DayOfWeek\n",
       "0  2017-05-01          1.0        0.0   39.0              Mon\n",
       "1  2017-05-01          1.0        1.0  126.0              Mon\n",
       "2  2017-05-01          1.0        3.0   29.0              Mon\n",
       "3  2017-05-01          2.0        0.0   18.0              Mon\n",
       "4  2017-05-01          2.0        1.0  109.0              Mon"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_trips_hourly.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "'''\n",
    "fig, ax = plt.subplots(figsize=(20,7))\n",
    "width = 0.35 \n",
    "df_trips_hourly_week=df_trips_hourly.groupby(['unplug_DayOfWeek','user_type'])['count'].agg('sum').unstack()\n",
    "plt.bar(['Mon','Tue','Wed','Thu','Fri','Sat','Sun'], df_trips_hourly_week,width)\n",
    "'''\n",
    "\n",
    "\n",
    "df_trips_hourly_week_1=df_trips_hourly.loc[df_trips_hourly['user_type'] == 1].groupby(['unplug_DayOfWeek','user_type'])['count'].agg('sum').unstack()\n",
    "df_trips_hourly_week_2=df_trips_hourly.loc[df_trips_hourly['user_type'] == 2].groupby(['unplug_DayOfWeek','user_type'])['count'].agg('sum').unstack()\n",
    "DayW=['Mon','Tue','Wed','Thu','Fri','Sat','Sun']\n",
    "fig, ax1 = plt.subplots(figsize=(15,7))\n",
    "color = 'tab:red'\n",
    "ax1.set_xlabel('Day of week')\n",
    "ax1.set_ylabel('Usuario anual (poseedor de un pase anual)', color=color)\n",
    "ax1.plot(DayW, df_trips_hourly_week_1, color=color)\n",
    "ax1.tick_params(axis='y', labelcolor=color)\n",
    "plt.grid()\n",
    "ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axis\n",
    "\n",
    "color = 'tab:blue'\n",
    "ax2.set_ylabel('Usuario ocasional', color=color)  # we already handled the x-label with ax1\n",
    "ax2.plot(DayW, df_trips_hourly_week_2)\n",
    "ax2.tick_params(axis='y', labelcolor=color)\n",
    "\n",
    "fig.tight_layout()  # otherwise the right y-label is slightly clipped\n",
    "plt.title('Number of trips per user_type', loc='center')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Trips per hour per user_type\n",
    "df_trips_hourly_hour_1=df_trips_hourly.loc[df_trips_hourly['user_type'] == 1].groupby(['unplug_Hour','user_type'])['count'].agg('sum').unstack()\n",
    "df_trips_hourly_hour_2=df_trips_hourly.loc[df_trips_hourly['user_type'] == 2].groupby(['unplug_Hour','user_type'])['count'].agg('sum').unstack()\n",
    "Hours=np.arange(24)\n",
    "\n",
    "fig, ax1 = plt.subplots(figsize=(15,7))\n",
    "color = 'tab:red'\n",
    "ax1.set_xlabel('Hours')\n",
    "ax1.set_ylabel('Usuario anual (poseedor de un pase anual)', color=color)\n",
    "ax1.plot(Hours, df_trips_hourly_hour_1, color=color)\n",
    "ax1.tick_params(axis='y', labelcolor=color)\n",
    "plt.grid()\n",
    "ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axis\n",
    "\n",
    "color = 'tab:blue'\n",
    "ax2.set_ylabel('Usuario ocasional', color=color)  # we already handled the x-label with ax1\n",
    "ax2.plot(Hours, df_trips_hourly_hour_2)\n",
    "ax2.tick_params(axis='y', labelcolor=color)\n",
    "\n",
    "fig.tight_layout()  # otherwise the right y-label is slightly clipped\n",
    "plt.title('Number of trips per user_type', loc='center')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Top trips for year (rolling)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_type</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>idplug_station</th>\n",
       "      <th>idunplug_station</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <th>135</th>\n",
       "      <td>3152.0</td>\n",
       "      <td>377.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <th>9</th>\n",
       "      <td>2877.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <th>57</th>\n",
       "      <td>2631.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <th>132</th>\n",
       "      <td>2584.0</td>\n",
       "      <td>557.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <th>52</th>\n",
       "      <td>2528.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <th>90</th>\n",
       "      <td>2347.0</td>\n",
       "      <td>272.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <th>135</th>\n",
       "      <td>2343.0</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <th>163</th>\n",
       "      <td>2343.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "user_type                             1      2\n",
       "idplug_station idunplug_station               \n",
       "135            135               3152.0  377.0\n",
       "149            9                 2877.0   12.0\n",
       "135            57                2631.0   17.0\n",
       "132            132               2584.0  557.0\n",
       "135            52                2528.0   22.0\n",
       "90             90                2347.0  272.0\n",
       "132            135               2343.0  192.0\n",
       "149            163               2343.0    8.0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Most famous path for user_type=1\n",
    "df_trip_stations_year=df_trip_stations[df_trip_stations['user_type'].isin([1,2])].groupby(['idplug_station','idunplug_station','user_type'])['count'].agg('sum').unstack()\n",
    "df_trip_stations_year.reset_index()\n",
    "df_trip_stations_year.nlargest(8, 1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_type</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>idplug_station</th>\n",
       "      <th>idunplug_station</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <th>64</th>\n",
       "      <td>2264.0</td>\n",
       "      <td>1903.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <th>132</th>\n",
       "      <td>2584.0</td>\n",
       "      <td>557.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <th>135</th>\n",
       "      <td>3152.0</td>\n",
       "      <td>377.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <th>73</th>\n",
       "      <td>940.0</td>\n",
       "      <td>300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <th>90</th>\n",
       "      <td>2347.0</td>\n",
       "      <td>272.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <th>86</th>\n",
       "      <td>856.0</td>\n",
       "      <td>217.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <th>64</th>\n",
       "      <td>588.0</td>\n",
       "      <td>209.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <th>132</th>\n",
       "      <td>2122.0</td>\n",
       "      <td>209.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "user_type                             1       2\n",
       "idplug_station idunplug_station                \n",
       "64             64                2264.0  1903.0\n",
       "132            132               2584.0   557.0\n",
       "135            135               3152.0   377.0\n",
       "73             73                 940.0   300.0\n",
       "90             90                2347.0   272.0\n",
       "86             86                 856.0   217.0\n",
       "73             64                 588.0   209.0\n",
       "135            132               2122.0   209.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Most famous path for user_type=2\n",
    "df_trip_stations_year.nlargest(8, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis: round trip VS a-B trip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_type\n",
       "0     5.336718\n",
       "1     2.444495\n",
       "2    10.882962\n",
       "3    31.754358\n",
       "Name: count, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of ring trips % (per user_type)\n",
    "round_trips=df_trip_stations['count'].loc[df_trip_stations['idplug_station']==df_trip_stations['idunplug_station']].groupby(df_trip_stations['user_type']).sum()\n",
    "total_trips=df_trip_stations['count'].groupby(df_trip_stations['user_type']).sum()\n",
    "round_trips.div(total_trips)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_type\n",
       "0      96520\n",
       "1    4808436\n",
       "2      83084\n",
       "3     490128\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of total trips (per user_type)\n",
    "total_trips"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 1296x360 with 2 Axes>,\n",
       " array([<matplotlib.axes._subplots.AxesSubplot object at 0x10ecb0f28>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x111d0f978>],\n",
       "       dtype=object))"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create calmap per user_type\n",
    "import calmap\n",
    "\n",
    "df_calmap=df_trips_hourly.loc[df_trips_hourly['user_type'] == 1].groupby(['unplug_Day'])['count'].agg('sum')\n",
    "df_calmap.index = pd.DatetimeIndex(df_calmap.index)\n",
    "series_calmap = pd.Series(df_calmap,index=df_calmap.index)\n",
    "\n",
    "calmap.calendarplot(df_calmap, monthticks=1, daylabels='MTWTFSS',dayticks=[0, 2, 4, 6], linewidth=0,fig_kws=dict(figsize=(18, 5)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 1296x360 with 2 Axes>,\n",
       " array([<matplotlib.axes._subplots.AxesSubplot object at 0x10f4143c8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x1122a21d0>],\n",
       "       dtype=object))"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABK4AAAFgCAYAAACSQDEcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzs3XmcpFV97/HPb/Y5M+zrsK+CrBNACbiBonEhUVwixNxcoqg3BheiSV6veE3MTYxZJF41Go1rookYrxqMGkGBkSiGILsIsiOLLAPDDDNnZmBmzv2jnrZrmumu6uY809Xdn/fr9byq6qk63zpdXctTvzrPeaKUgiRJkiRJkjRoZk12ByRJkiRJkqQtsXAlSZIkSZKkgWThSpIkSZIkSQPJwpUkSZIkSZIGkoUrSZIkSZIkDaQ5k92BPlQ/7GHOuXakJGmKefYH/qt65mfOfEb1TIC3f+W66pmL09zqmQA/f2B19cwbv/bV6pltOfBlL6+eeds3z6+eCfA//uh3qmdec8tD1TMB7rvn0eqZzz5+3+qZAPc8VP818CtLl1TPBLjyzvqP63cv/HH1TIDXvPLY6pnnff6S6pkA3Hdz/cxoZ7zBXi94afXMe777jeqZU8nL3vb6VnK/+92fVM9Mi1P1TID5C+dXz7z/J/X//tY89nA7udvuXD9z7oL6mcDab5wdNfMccSVJkiRJkqSBZOFKkiRJkiRJA8nClSRJkiRJkgaShStJkiRJkiQNJAtXkiRJkiRJGkgWriRJkiRJkjSQLFxJkiRJkiSpNRFRIuILXZfnRMRDEfGNXm0tXEmSJEmSJKlNa4AjImJhc/mFwL39NLRwJUmSJEmSpLZ9C3hZc/4M4Iv9NLJwJUmSJEmSpLadB5weEQuAo4DL+2lk4UqSJEmSJEmtKqVcB+xHZ7TVt/ptN6etDkmSJEmSJEldvg58ADgJ2KmfBhauJEmSJEmStDV8Bni0lHJ9RJzUTwMLV5IkSZIkSWpdKeUe4MPjaWPhSpIkSZIkSa0ppSzewrplwLJebZ2cXZIkSZIkSQPJwpUkSZIkSZIGkoUrSZIkSZIkDSQLV5IkSZIkSRpIFq4kSZIkSZI0kCxcSZIkSZIkaSDNmewOSJI0GVKaWz3zzM/8d/VMgPvvXVE9c8leO1bPBLjp8utbyZ0q5s6dPdld6Ntl195XPXPTplI9E2D/A3eunvnjW5ZXzwRYeuiu1TNnRfVIAO65/7Hqmae86IjqmQC3/3xV/dB1q+tntuS41/16K7k/+t7Mfs9uw7rHN7aSO2tW/TEnK37+QPVMgFnzFtQPXV1/WwiAHfeon7lwm/qZANHCuKNZU2O7xRFXkiRJkiRJGkgWriRJkiRJkjSQLFxJkiRJkiRpIFm4kiRJkiRJ0kCycCVJkiRJkqSBZOFKkiRJkiRJA8nClSRJkiRJkgaShStJkiRJkiQNJAtXkiRJkiRJGkgWriRJkiRJkjSQLFxJkiRJkiRpIFm4kiRJkiRJ0kCycCVJkiRJkqSBZOFKkiRJkiRJA8nClSRJkiRJkgaShStJkiRJkiQNJAtXkiRJkiRJGkgWriRJkiRJkjSQLFxJkiRJkiRpIFm4kiRJkiRJ0kCycCVJkiRJkqSBNGesK3POtzdnnwB+J6V0cftdkiSpfbff+lD1zNlzZlfPBFh547XVM/fZ/wXVMwFYtbyd3Cniph/dNNldmFTz5rXzGrjn7pXVM3dfsk31TIB7lq+pnrlowZib7BO24w4Lq2feeMvD1TMBDjlwx/qha1fXz2zJunUb2glefnc7uTPYG0/cu5Xci/798vqh0c44ljnz6r9nPb6undfrXk8/qHrmPd9fVj0TgI0bq0fuc/Th1TPb0OuZuh+wL3Aw8B8553Na75EkSZIkSZJE/7sKFmAu8IGc83dyzvu11yVJkiRJkiRpfHNcFSCAFwA35Jzfm3NO7XRLkiRJkiRJM12/hatoFugUsBYC7wHuyjn/Sc55pzY6J0mSJEmSpJlrPLsK/gdwJZ0C1tDoq52AP6ZTwPpIzvmYVnopSZIkSZKkGWc8uwreBpwAvA8YOqzFUAErAW8Brsg535Fz/mDO+Tk553YOLSNJkiRJkqSBFxEfjIh3dF2+ICI+1XX53Ij4vdHaj+v4lymlDSml9wBHAt9m890Hh3Yn3Bd4G7AMWJVz/l7O+f/mnN+Yc35RzvnInPMB47lfSZIkSZIkTUk/AE4EiIhZwM7A4V3XnwhcNlrjORO5x5TSzcBLc87PozPX1fObq0pzOlTQWgg8u1m6lYnetyRJkiRJkqaMy4APNucPB34MLImIHYAMPB24arTG4xpxNVJK6XsppVOA44BPA2vYfBRWdyFr5CJJkiRJkqRprJRyH7AhIvahM7rqh8DldKajOg64vpTy+Gjtn1LhakhK6aqU0huBJcBvAP+P4SJWd5GqbKG5JEmSJEmSpq/L6BSthgpXP+y6/IOxGlbdXS+ltAY4DzivmZh9KZ0K2tHAQcB+wHbAopr3K0mSJEmSpIE1NM/VkXR2FbwbeCewCvjsWA1bm2cqpbQRuLJZJEmSJEmSNDNdBrwLuL2UshF4JCK2pzPn1RvHalhlV0FJkiRJkiRpFNfTOZrgf41Yt7KUsnyshv2MuHIidUmSJEmSJE1IM8pq2xHrzuynba/C1f5d51eNr1uSJEmSJEnSxI1ZuEop3bW1OiJJkiRJkiR1c44rSZIkSZIkDSQLV5IkSZIkSRpIFq4kSZIkSZI0kCxcSZIkSZIkaSCNOTl7zvm5bd1xSunStrIlSeplxZ13Vs888Lgjq2cCLF+/pnrmvXevqJ4JwMYn2smtLVr67W7Fz9vJbcG9dz5YPfOAQ/aongmw517b9r7ROG3cWKpnAqxfv6F6Zmmnqzz+xKbqmZs2tdPZ+fNm1w9dO3UOmr7ttvPbCZ4q79ltaeGz4AMX3lo9E2D3g/avnvnQfQ9VzwR4fN3jreS2YfHiefVDd96nfiawYLvtqmfuvHOqntmGMQtXwDKgjU+f0sd9S5IkSZIkaQbrt3gUrfZCkiRJkiRJGqHfwlXNUVcWwSRJkiRJktRTr5163w+sZrjYFBUWSZIkSZIkqacxR1yllN6dc/448BXgODojrwK4DngVUH/2SUmSJEmSJIk+dhVMKd2dcz6JzkTtxzarjwTOTimd017XJEmSJEmSNJP1dfzPlFIGTgNWMjzq6q0552e12DdJkiRJkiTNYH0VrgBSSvcCb6dTtCpN23Nb6pckSZIkSZJmuL4LVwAppc8DVzI8yfozcs6nVO+VJEmSJEmSZrxxFa4afw5c2yzXAc+u2iNJkiRJkiSJPiZnHymldD5wfgt9kSRJkiRJkn5hIiOuJEmSJEmSpNZZuJIkSZIkSdJAsnAlSZIkSZKkgTSuOa5yzgGcBDwfOAw4BNgBWAwsBNYCq4FHgZuAnwCXAJeklEq1XkuSJEmSJGna66twlXOeDZwDvBPYteuqGHHTbZplCXAo8Argj4AHc84fBP42pbThqXZakiRJkiRJ01/PXQVzzrsAVwB/BexGp1g1tJQxlu7b7Qa8H7gy57xb9b9CkiRJkiRJ086Yhauc8yzgm8BSnlyogs2LUyMXeHIh60jgW02uJEmSJEmSNKpeuwqeCRzH5oUqgJXArcCDwGPAE8DGJm8und0FdwcObM7DcPFqKfDbwKdr/AGSJEmSJEmannoVrk4fcfnbwPtSSj/o9w5yzscD7wFeynAB7AwsXEmSJEmSJGkMvQpXRzE8Uuq6lNJLx3sHKaXLc86/ClwDHMHwLoOSJEmSJEnSqHoVrrZvTgtw5UTvJKVUcs4/Yrhgte1EsyRJqmLuguqR221XPxOADY9Xj9z/wJ2rZwI8csX6VnJrO/Tlr2gl96ZvfKN+6KzZ9TOBAw7Zo3rm7NkjDzhdx7x5fR0Ie1w2btxUPRPggCX1N3NvuW9l9UyAnVt4z3rkkVw9E+DIPes/ri28Wluz4zbz2wnetLGd3Cni9D94Y/XMA3ZeWD0T4JN3PlI986DD9q6eCXD/vSuqZ668o5337IUL63++zF6YqmcCLNlnl+qZe++6uHpmG3pNkv5wcxrAc3PO8yZyJznn+cDzGN5VcPlEciRJkiRJkjRz9CpcXcnw0QQPAC7LOb8657z92M06cs6Lc86vAX7YtB/KumLiXZYkSZIkSdJM0Gtc3BeAU5vzARwDfAkg57wCeABYBTxO56iCs4B5wGJgl2YJhgtWQ+PHP1frD5AkSZIkSdL0NGbhKqX0rznns4BTGN7Nb6j4tGOzlC00HTnBQek6/WZK6esT664kSZIkSZJmil67CgKcBlzAcDGqjFiGdBertnSbAJYBr514dyVJkiRJkjRT9CxcpZTWpJReAvwGcDXDu/51L7B5gWrkcifwO8ApKaW1FfsvSZIkSZKkARYRGyPimq5lv37b9n3sx5TSecB5OecDgZOBw4FDgB2AbYAFwDpgDbASuBW4Cbg0pXRNv/cjSZIkSZKkaWVtKWXpRBr2XbgaklK6DbhtIncmSZIkSZIk9Wvchauc81w6k7I/mlJaP4522wPbDl1OKf1svPctSZIkSZKkKWdhRAztjXdHKeW0fhv2XbjKOf8mcDZwHM28Vjnn24HzgY+klO7qEfFnwFua82U89y1JkiRJkqQpa8K7CvacnD3nvCDn/DXgH4FnNG2GJl0/EDgHuDnn/Jc553k94kZO6C5JkiRJkiRtUc/CFfBJ4OVsfvTA7iWAucDvA1fknPduoZ+SJEmSJEmaYcYsXOWcnwW8juEiFWw+airYvIB1JPCDnPNBbXVYkiRJkiRJM0OvEVdndZ0P4AHgncCpwJuBZTx5JNZewCU55wOq9lSSJEmSJElTTill8UTb9pog/USGR1OtAU4YMQn7J3POvwZ8HhjqRAH2BC7KOT8npXTPRDsnSZIkSZKkmavXiKslzWkBLtrSkQNTSl8HXgA82rW6APsCF+ecl4xsI0mSJEmSJPXSq3A1t+v8o6PdKKX0I+CFwMqu1QU4CFjmnFeSJEmSJEkar16Fq4ea0wCOzznHaDdMKV0FvIzOLoXdDgauAp430U5KkiRJkiRp5ulVuLqa4cnXnwZ8MOe8YLQbp5R+CPwasK5ZNXQkwsXA4V2XJUmSJEmSpDH1mpz9K8CvMjxB+1uBN+ScfwKclVK6fmSDlNKynPMrgH8DFjBcrAosXEmSxmmnZ/1BO8F7HdZOriRJkqRqehWuzgPeTWeuqqHi1SLgOGD9aI1SSt/JOb8Y+Hdgm2a1RStJ0sD4P+98cfXM5+69U/VMgJP+5UvVM3/3BQdUzwR4/Rc3tZJb2+tP2b+V3D84f0P1zHP+/OzqmQBX3rmieuZZJ+5dPRPg4ttGnWp1wu56aHX1TIAj91hUPfOgXRZWzwTYb/tRd6SYsMNfcHD1TIAf3P1wK7lTxXtfeEgrud/40OOt5E4VHz7t8OqZH//hndUzAf7w9KOqZ67b0M5n9mPr96me+Vc/WlY9E+CZh+xaPfPun9X/fAVYvHhe9cxDlyyuntmGMXcVTCk9DrwOWMWTR0zd16PtfwLPAu5keHdDSZIkSZIkqS+95rgaOmLgs4BLGS5ArU4p9fyZKqV0A/BLwGeATVjAkiRJkiRJUp96Fq4AUko/SSmdRGeC9d8HPtbvHaSUVqWUzqIzufvH6IzAkiRJkiRJksbUa46rzaSUbgRunMgdpZTuAM4GyDnvNpEMSZIkSZIkzRx9jbiqLaX0wGTcryRJkiRJkqaOSSlcSZIkSZIkSb1YuJIkSZIkSdJAsnAlSZIkSZKkgWThSpIkSZIkSQPJwpUkSZIkSZIGkoUrSZIkSZIkDSQLV5IkSZIkSRpIFq4kSZIkSZI0kCxcSZIkSZIkaSBZuJIkSZIkSdJAsnAlSZIkSZKkgWThSpIkSZIkSQPJwpUkSZIkSZIGkoUrSZIkSZIkDSQLV5IkSZIkSRpIcya7A73knCe7C5IkSZIkSZoEA1+4kiTNcLNmtxJ7+lF7Vs+85t5Hq2cCEPUHSF/400eqZwKwaWM7uZX9fOUT7QSXTdUjX3XY7tUzAWbPiuqZ3711RfVMgMXz62+yPm3JttUzAV50wK7VMy+8/cHqmQCPrttQPfOJDfVfAwBH7bJdK7lTxYG7LZrsLkxLD69+vHrmftsvqJ4JkObUfx8slOqZAF+8+uf1Q1vYFgL47hV3V89csHB+9UyATZvq/7+uuKOdz+3a3FVQkiRJkiRJA8nClSRJkiRJkgaShStJkiRJkiQNJAtXkiRJkiRJGkgWriRJkiRJkjSQLFxJkiRJkiSpNRHx7oi4ISKui4hrIuL4ftvWP6amJEmSJEmSBETECcCpwDGllPURsTMwr9/2Fq4kSZIkSZLUliXA8lLKeoBSyvLxNHZXQUmSJEmSJLXlQmDviLg5Ij4WEc8bT2MLV5IkSZIkSWpFKWU1cCzwJuAh4EsRcWa/7d1VUJIkSZIkSa0ppWwElgHLIuJ64H8Cn+unrSOuJEmSJEmS1IqIOCQiDu5atRS4q9/2jriSJEmSJElSWxYDH4mI7YENwK10dhvsi4UrSZIkSZIktaKUciVw4kTbu6ugJEmSJEmSBpKFK0mSJEmSJA0kC1eSJEmSJEkaSBauJEmSJEmSNJAsXEmSJEmSJGkgWbiSJEmSJEnSQIpSymT3QZIkSZIkSXoSR1xJkiRJkiRpIFm4kiRJkiRJ0kCycCVJkiRJkqSBZOFqAiJi9WT3QWOLiI0RcU3Xst8Ytz0pIr6x9Xo3dUVEiYgvdF2eExEP+fjVERGvaB7jQye7L3oyn//t8/O1Xb0e34hYFhHHba3+aHN+BrQjIt4dETdExHXNNuHxk92n6SAi9oqI8yPiloi4LSI+FBHzxrj9OyIibc0+6hfbLud2XX5XRLx3Ers0LXR917whIq6NiHdGhLWVFvngarpaW0pZ2rXcOdkdmibWAEdExMLm8guBe8cTEBFzqvdq+jgD+H5z2reImN1OdzTCU37+S9IYJvQZoNFFxAnAqcAxpZSjgFOAuye3V1NfRATwVeDfSikHA08DFgPvG6PZOwALV1vfeuCVEbHzZHdkmhn6rnk4ne3BlwB/Msl9mtYsXE1QRCyOiIsi4qqIuD4iXt6s3y8iboyITzYV2Au7vuRoEkXE7Ij4m4i4ovnV7c1dV28bEd+MiJ9GxMetmI/pW8DLmvNnAF8cuiIinhkRP4yIqyPisog4pFl/ZkR8PSIuBi7a+l0efBGxGHg28Abg9GbdSRFx6ZaemxGxOiLOjYhrgRMmr+czzkSe/5dGxNKu230/Io7eqr2eQkaOgo2Iv4uIM5vzd0bEn3Z99joyZZzGenw1ecb4DBjttfDSiLgpIq6MiA878nNUS4DlpZT1AKWU5aWU+yLi2Ij4XvP4XRARS+AXow4/1Iyk+HFEPHNSez+4ng+sK6V8FqCUshE4B3h9RCyKiA80j991EfHWiHgbsAdwSURcMon9nok2AP9A5/+zmeZ768XN/+miiNgnIraLiLu6tjcXRcTdETF3a3d8qiilPAi8CTg7Okb9zhkRf9hsv1wbEX85eb2eevxyPnHrgNNKKccAJwPnNr8+ABwMfLSpwD4KvGqS+jiTLYzh3QS/1qx7A7CylPIM4BnAGyNi/+a6ZwJvBQ4DDgReudV7PHWcB5weEQuAo4DLu667CXhOKeWXgD8G/qLrumOAV5dSnrfVejq1vBz4dinlZuDhiDi2WT/ac3MRcHkp5ehSyve3em9nrok8/z8NnAkQEU8DFpRSrt1qPZ5+ljefvX8PvGuyOyNVMtpnwJM07z+fAF5SSjkW2GUr9XEquhDYOyJujoiPRcTzmi/gH6GzTXIs8Bk2HymUSilLgbc01+nJDgeu7F5RSlkF/Aw4C9gPWNqMcvvnUsqHgfuAk0spJ2/lvgo+CrwuIrYbsf4jwD8O/Z+AD5dSVgLXAEPb66cCF5RSnthqvZ2CSim3A7OBXRnlO2dEvITOe/3xpZSjgb+etA5PQRauJi6Av4iI64DvAnsCuzXX3VFKuaY5fyWdN29tXd27Cp7WrHsR8FsRcQ2dL5s70SkyAvx3KeX25hejL9L51VNbUEq5js5z+gw6o0+6bQd8OSJ+DHyQzobNkO+UUh7ZKp2cms6gUxShOR3aVWS05+ZG4Ctbt4ua4PP/y8CpzZel1wOf2yqdnb6+2pz6+arpZLTPgC05FLi9lHJHc/mLY9x2RiulrAaOpTMa4iHgS8CbgSOA7zTbhP8b2Kur2RebtpfSGZG//Vbt9NR3EvCJUsoGALf9Jl9TVPwn4G0jrjoB+Jfm/OcZ3sb8EvDa5vzpzWX1b7TvnKcAny2lZPC1MV7ONTNxr6PzC9expZQnIuJOYEFz3fqu220E3FVwMATw1lLKBZutjDgJKCNuO/KyNvd14AN0Nk526lr/Z8AlpZTTojMh/rKu69Zspb5NORGxI51h90dGRKHzi00Bvsnoz811TTFLW9+4nv+llBwR36HzK9uv0/kSpdFtYPMf1haMuH7oM3YjbsdMRK/HV1vZGJ8B5+P/6ilrPiuXAcsi4nrgd4EbSimj7WbvNmFvPwFe3b0iIrYF9gHunIwOqaf/C1wFfLaP236dzgCNHelss1zcZsemg4g4gM52yYOM/p3zVyajb9OFI64mbjvgwaZodTKw72R3SD1dAPzO0D7aEfG0iFjUXPfMZgjnLDq/MLjr1dg+A/xpKeX6Eeu3Y3iy6jO3ao+mtlcDny+l7FtK2a+UsjdwB/AcfG4Oook8/z8FfBi4opSyot3uTXl3AYdFxPxmpMMLJrtD04yP7+AZ7TNgFlv+X/0UOCCGj5j82pGB6oiIQyLi4K5VS4EbgV2iM3E7ETE3IrpHiL+2Wf9sOrv7rNxqHZ46LgJSRPwW/OIgMefSGVF8AfDmaA7G0xQ/AB4Dttn6XRX8YnTPv9LZjW3IZTRz6tEZlPGfzW1XA1cAHwK+4Q+lY4uIXYCPA39XSimM/p3zO8BvR3N0za7Xhvpg4Wqcmjfh9XT2Az6u+eXmt+jMbaLB9ik6vxBd1ezK8wmGf62/Avg7OhszdwBf22KCACil3NPMVzDSXwPvj4ircSTEeJzBk59zX2nW+9wcMBN5/pdSrgRW0d8vnTPS0OdrKeVuOhvXP25Or57Ujk0TPr4DbbTPgNPZwv+qlLKWzvxL346IK+kUBCyubNli4B8j4ifN9B6H0ZmD8NXAX0XnACfXACd2tVnXvI9/nM2/5KvRfDk/DXhNRNwC3Exn/t8/orO9/TPguubx/Y2m2T/Qec46OfvkORfoPrrgW+kUUq4D/gfw9q7rvgT8Ju4mOJqh+ZRvoDNt0IXAnzbXbfE7Zynl23RGs/2o2Y3QeTrHITrvO+pXdI4E9clSikcZkdSqZjfWd5VSTp3svuipiYg96OyqcmgpZdMkd2cg+fnaLh/f6SUiFpdSVjcHBvoocEsp5YOT3a+pLiKW0fnc/dFk90WSNMwRV+MQEf+LzoSN/3uy+yJJmhqaXSkuB95t0WrL/Hxtl4/vtPTG5hf7G+jspvyJSe6PJEmtccSVJEmSJEmSBpIjriRJkiRJkjSQLFxJkiRJkiRpIFm4kiRJkiRJ0kCycCVJkiRJkqSBZOFKkiRJkiRJA8nClSRJkiRJkgaShStJkiRJkiQNJAtXkiRJkiRJGkgWriRJkiRJkjSQ5kx2B3p574W3lNqZf/XXX6kd2TFnXv3M2e38i2LB4uqZ5c5rq2cCzDpgafXMTevWVs+cu6j+YwrwxMM/r545f9c9q2cCrL/71uqZTz/ludUzAV503F7VMz/0F5+vngmw3dOPrp55+FHtPAfWrn2ieubuOy2qngnw8+VrqmcedeBO1TMB/ul9f189c+npv149E2D9+g3VM2fNiuqZixa18JkN3HnHI9Uzf/nY+u9XALfctaJ65j57bFs9E+CxFt5b1qx5vHomwFEH7lw98+HH1lXPBFiV6z+uj6yov40F7bxmr/iP71fPBDj2V05sJffCtxzbSq4k1ZZSqrrx5ogrSZIkSZIkDSQLV5IkSZIkSRpIFq4kSZIkSZI0kCxcSZIkSZIkaSBZuJIkSZIkSdJAsnAlSZIkSZKkgWThSpIkSZIkSa2JiBIRX+i6PCciHoqIb/Rqa+FKkiRJkiRJbVoDHBERC5vLLwTu7aehhStJkiRJkiS17VvAy5rzZwBf7KeRhStJkiRJkiS17Tzg9IhYABwFXN5PIwtXkiRJkiRJalUp5TpgPzqjrb7Vb7s5bXVIkiRJkiRJ6vJ14APAScBO/TSwcCVJkiRJkqSt4TPAo6WU6yPipH4aWLiSJEmSJElS60op9wAfHk8bC1eSJEmSJElqTSll8RbWLQOW9Wrr5OySJEmSJEkaSBauJEmSJEmSNJAsXEmSJEmSJGkgWbiSJEmSJEnSQLJwJUmSJEmSpIFk4UqSJEmSJEkDac5kd6CX/759Rf3QRx+onwmwx9OqR85ZmKpnAmxYm+uHbr9b/Uxg09o11TNnLVxUPfOJ26+rngnAdrtUj3xi/RPVMwFI21aPnD+/nbepT/zLFfVD166qnwnsumT76pkrV66rngnwgdccXT3zc1fdUz0TYP/D6r9nXXD5z6pntuXWm37eSu6Ou9Z/vm7YsKl6ZinVIwGYNbv+b4I/u/+x6pkA22wzv3rmwy29txyx347VM7/1vduqZwI8vYW+rsrtfG7vv9s21TMfWbG2eibAww/X3x5k1fL6mcCKlh4DSWpDSu3UHGpyxJUkSZIkSZIGkoUrSZIkSZIkDSQLV5IkSZIkSRpIFq4kSZIkSZI0kCxcSZIkSZIkaSBZuJIkSZIkSdJAsnAlSZIkSZKkgWThSpIkSZIkSQPJwpUkSZIkSZIGkoUrSZIkSZIkDSQLV5IkSZIkSRpIFq4kSZIkSZI0kCxcSZIkSZIkaSBZuJIkSZIkSdJAsnAlSZIkSZKkgWThSpIkSZIkSQPJwpUkSZIkSZIGkoUrSZIkSZIkDSQLV5IkSZIkSRpIFq4kSZIkSZI0kOZMdgd6WbV6ff3QWbPrZwKsWVE9csPaVdUzAebtskf1zMcffaB6JgDbzKseOWdu/acQ8YGSAAAZlUlEQVT+49UTG4t3qh656f7bq2cCsHiH6pHz5w/829SwfY5sJXbBgvqPwapVLby3An+z7NbqmfPntPOefeOd9d+zH1u1rnpmW1avWNlK7v4H71Y9c+3aJ6pn/uSCi6tnAuz77GdXz9y4cVP1TIC0YH71zLvvbWe7ZdO+pXrm0UfsXj0TYOfF9bdbrvjx/dUzAb7/6S9Uz9zzBS+rngkQEdUzdz/hpOqZAOvWbWwlV5JmqnF9G8o5zwZ2Ah5KKT1pCyLnPA94PfBi4ABgA3AH8G3g8ymlqbNFL0mSJEmSpEnV166COeen5Zy/CqwGfg6szTl/Oed8UNdtDgFuBj4K/CpwBLAUeAXwceC2nPPzK/dfkiRJkiRJ01TPwlXO+VnAFcDLgflAAPOAVwLfzzkfmnPeFbgU2Ke5HqA0SzTLEuDbOecX1v4jJEmSJEmSNP2Muatgznlb4F+BbZpV3bsHBrAL8Cngx8350nUdW2gzB/jnnPOBKaXHnkK/JUmSJEmSNM31muPqDXRGSm2pIDXkhGYZGl21DvgmcDuwK/AcOvNdDWXsBLwJOPepdFySJEmSJEnTW69dBU9tTocKVh8Bdgf2aM5H1/UB3AYcnlJ6TUrpD1NKvw0cSqdIFQwXr4ZyJUmSJEmSNE1FxAcj4h1dly+IiE91XT43In5vtPa9CleHM1xsuiGl9PaU0oMppftTSm8Hbui6bQF+N6V0R3dASmkD8AfAjUN9Ag7r9YdJkiRJkiRpyvsBcCJARMwCdqZTbxpyInDZaI17Fa52aE4LnQnaR7qCzXcf/MGWQlJKBbi867bb97hfSZIkSZIkTX2X0ZliCjoFqx8Dj0XEDhExH3g6cNVojXvNcbUOWNyc32kL148sQG0HrBkla/eu87nH/UqSJEmSJGmKK6XcFxEbImIfOqOrfgjsSaeYtRK4vpTy+Gjte424urc5DeBFOecDh65ozr+YzY8a+PtbCsk5Pxt4Uddtb+txv5IkSZIkSZoeLqNTtBoqXP2w6/IW994b0mvE1Q/oTK5egAXAf+ecz2uue22zrvuIg2/LOR8MfIxOcWoJ8FLgrQxP4F6AZX3/aZIkSZIkSZrKhua5OpLOroJ3A+8EVgGfHathr8LVp4A3NOcLnTmv/ldzuXtuqyuAZzTrXtIs3bqPKLipyZUkSZIkSdL0dxnwLuD2UspG4JGI2J7OnFdvHKvhmLsKppQuBz7OcJGqjDgPcDVwCp1qWffoq+6ldLX5SErppr7+LEmSJEmSJE1119M5muB/jVi3spSyfKyGvUZcAZwNrKezu99QoWuoeHUV8LKU0mM551cBF9KZsL2MyBi6/VfoVNgkSZIkSZI0AzSjrLYdse7Mftr2LFyllDYB5+Sc/x54BbA/8Cid/RO/mVIqze1+lHP+JeA9wG/Qmf9qyE+Bv00pfbKfTkmSJEmSJEn9jLgCIKV0M/DXPW5zF3BWzvl36RS4tgXuSynd85R6KUmSJEmSpBmn78LVeKSU1gPOYyVJkiRJkqQJG3NydkmSJEmSJGmyWLiSJEmSJEnSQLJwJUmSJEmSpIFk4UqSJEmSJEkDaczJ2XPOz23rjlNKl/Zzu5yfqH/ni3eonwks3GO/6plrb7m2eibA4/MX1Q9d0EImsOOSXapnPnLHHdUz2djCc7Wl3FlLDqieCUCpH7lw/uz6ocD2O29fPfP+5Q9UzwR44P7HqmfuuFM7r9fVLbxnv+DYnatnAvy/h9dUz9x5l8XVMwEWv/TXqmfu1NJzYOXKda3kVrdmRSuxGzZsqp45b14774MPr1hbPXPx4nnVMwFuuPOR6pm77ZiqZwL89L5V1TPnzm3nOdCG0sK2AMCSJfXfX0tLnX3sscdbyZWkmarXUQWX0cpXUUof9y1JkiRJkqQZrN/iUbTaC0mSJEmSJGmEfgtXNUddWQSTJEmSJElST70mZ38/sJrhYlNUWCRJkiRJkqSexhxxlVJ6d87548BXgOPojLwK4DrgVcCG1nsoSZIkSZKkGannroIppbtzzifRmaj92Gb1kcDZKaVz2uuaJEmSJEmSZrJeuwoCkFLKwGnASoZHXb015/ysFvsmSZIkSZKkGayvwhVASule4O10ilalaXtuS/2SJEmSJEnSDNd34QogpfR54EqGJ1l/Rs75lOq9kiRJkiRJ0ow3rsJV48+Ba5vlOuDZVXskSZIkSZIk0cfk7COllM4Hzm+hL5IkSZIkSdIvTGTElSRJkiRJktQ6C1eSJEmSJEkaSBauJEmSJEmSNJDGNcdVzjmAk4DnA4cBhwA7AIuBhcBaYDXwKHAT8BPgEuCSlFKp1mtJkiRJkiRNe30VrnLOs4FzgHcCu3ZdFSNuuk2zLAEOBV4B/BHwYM75g8DfppQ2PNVOS5IkSZIkafrruatgznkX4Argr4Dd6BSrhpYyxtJ9u92A9wNX5px3q/5XSJIkSZIkadoZs3CVc54FfBNYypMLVbB5cWrkAk8uZB0JfKvJlSRJkiRJkkbVa1fBM4Hj2LxQBbASuBV4EHgMeALY2OTNpbO74O7Agc15GC5eLQV+G/h0jT9AkiRJkiRJ01OvwtXpIy5/G3hfSukH/d5Bzvl44D3ASxkugJ2BhStJkiRJkiSNoVfh6iiGR0pdl1J66XjvIKV0ec75V4FrgCMY3mWwLzdedet477K32eM6mGLf5sxrIXe3A+pnAqx7rH7moh3qZwLbbJeqZ5Z996ueuWL53dUzAbj/tuqRu554cvVMgPtvrv963XnbBdUzAeYvqP96nbPdTtUzAXbcaVH1zOccvUf1TIAb7l5RPXP+7Hb2Lt+4sf7Bbn/y1a9UzwR45m+dUT3z6svrv7cAHPPLB1XPXLSw/uu1ha0LAHbZpf7rdf8l21bPBLj5Z49Wz9yvpb5+//K7qmfuves2vW80Afc+uLp65t5L2unrTS1kLl48r4VU2H2n+tuDP1++pnomwM3f+HorufzhCe3kStKA6/VtYPvmtABXTvROUkoF+BHDuxq2s1UjSZIkSZKkaaNX4erh5jSA5+acJ/QTSs55PvA8hncVXD6RHEmSJEmSJM0cvQpXVzJ8NMEDgMtyzq/OOW8/drOOnPPinPNrgB827Yeyrph4lyVJkiRJkjQT9Jo04gvAqc35AI4BvgSQc14BPACsAh6nc1TBWcA8YDGwS7MEwwWroV0FP1frD5AkSZIkSdL0NGbhKqX0rznns4BTGN7Nb6j4tGOzbGl22xhxuXSdfjOl1NKMhZIkSZIkSZou+jlU02nABQwXo8qIZUh3sWpLtwlgGfDaiXdXkiRJkiRJU0lEbIyIa7qW/fpt27NwlVJak1J6CfAbwNUM7/rXvcDmBaqRy53A7wCnpJTW9ts5SZIkSZIkTXlrSylLu5Y7+23Ya46rX0gpnQecl3M+EDgZOBw4BNgB2AZYAKwD1gArgVuBm4BLU0rX9Hs/kiRJkiRJEoyjcDUkpXQbcFsLfZEkSZIkSdL0szAihgY13VFKOa3fhuMuXOWc59KZlP3RlNL6cbTbHth26HJK6WfjvW9JkiRJkiRNOWtLKUsn0rCfydkByDn/Zs75v4C1wH2dVfmWnPMHcs779hHxZ8AdzXL7RDorSZIkSZKkmaNn4SrnvCDn/DXgH4FnNG2GJl0/EDgHuDnn/Jc553k94kZO6C5JkiRJkiRtUT8jrj4JvJzNjx7YvQQwF/h94Iqc894t9FOSJEmSJEkzzJiFq5zzs4DXMVykgs1HTQWbF7COBH6Qcz6orQ5LkiRJkiRp6iilLJ5o214jrs7qOh/AA8A7gVOBNwPLePJIrL2AS3LOB0y0U5IkSZIkSVKvowqeyPBoqjXACSmlu7qu/2TO+deAzwND1bMC7AlclHN+Tkrpnsp9liRJkiRJ0gzQa8TVkua0ABeNKFoBkFL6OvAC4NGu1QXYF7g457xkZBtJkiRJkiSpl16Fq7ld5x8d7UYppR8BLwRWdq0uwEHAMue8kiRJkiRJ0nj1Klw91JwGcHzOOUa7YUrpKuBldHYp7HYwcBXwvIl2UpIkSZIkSTNPr8LV1QxPvv404IM55wWj3Til9EPg14B1zaqhIxEuBg7vuixJkiRJkiSNqVfh6ivN6dAE7W8FHso5X55zPnJLDVJKy4BXsHnxaqi9JEmSJEmS1JdeRxU8D3g3nbmqhopPi4DjgPWjNUopfSfn/GLg34FtmtUTG211380Tajam+al+JvCcZx1YPfPWu0adWuwpmT27fh1xhx0WVs8EOGyv7atnrntiY/XMf3v8ieqZAPmxXD0zLZrb+0YTsPMB+1XP3D7Nq54JcPdt91XP/D9nt7NH9DOW1H8NbLugnefAnOP2qp6ZH6//egV48Vm7Vc884l+/XD0T4PdOqf/5MuuUdqafvPmRkTMGPHXH77FD9cyLP149EoCTj9y9euZ+O86vngnwzP22rZ651zbtbAvsuE39x+DkA+q/twL8x7zZ1TNfcHD91wDAXu95S/XMa297uHomwJuO36d65hObNlXPBOAl7+ak/Rf3vp0kqS9jjrhKKT0OvA5YRado1V18GvNbX0rpP4FnAXfiaCtJkiRJkiSNU69dBYeOGPgs4FKGC1CrU0qr+2h7A/BLwGeATVjAkiRJkiRJUp96Fq4AUko/SSmdRGeC9d8HPtbvHaSUVqWUzqIzufvH6IzAkiRJkiRJksbUa46rzaSUbgRunMgdpZTuAM4GyDnXn1hEkiRJkiRJ00pfI65qSyk9MBn3K0mSJEmSpKljUgpXkiRJkiRJUi8WriRJkiRJkjSQLFxJkiRJkiRpIFm4kiRJkiRJ0kCycCVJkiRJkqSBZOFKkiRJkiRJA8nClSRJkiRJkgaShStJkiRJkiQNJAtXkiRJkiRJGkgWriRJkiRJkjSQLFxJkiRJkiRpIFm4kiRJkiRJ0kCycCVJkiRJkqSBZOFKkiRJkiRJA8nClSRJkiRJkgbSnMnuQE8bn6geOWu3/atnApRSP3PRorn1Q4Gr/+3b1TNPOP1Xq2cCHLjzguqZP1uxvnpm2iZVzwRY/dBD1TMP3n/H6pkAj6yq/7i+87ntvF7nzalft7935ePVMwFmz1pZPfPvzr+peibA+ec8t3rmwnmzq2cCzJk1s3+7uXH56lZy99x2fvXM7/3s4eqZb37v2dUzAfbcbl71zDmzo3omwNJd638W3PTIquqZAHttV/95tWB2O+8tbzpu7+qZN61o53E9Yvf62y5/dPJB1TMBnv/+i6tn/tObfrl6piSpvpm91S5JkiRJkqSBZeFKkiRJkiRJA8nClSRJkiRJkgaShStJkiRJkiQNJAtXkiRJkiRJGkgWriRJkiRJktSaiHh3RNwQEddFxDURcXy/bee02TFJkiRJkiTNXBFxAnAqcEwpZX1E7AzM67e9hStJkiRJkiS1ZQmwvJSyHqCUsnw8jd1VUJIkSZIkSW25ENg7Im6OiI9FxPPG09jClSRJkiRJklpRSlkNHAu8CXgI+FJEnNlve3cVlCRJkiRJUmtKKRuBZcCyiLge+J/A5/pp64grSZIkSZIktSIiDomIg7tWLQXu6re9I64kSZIkSZLUlsXARyJie2ADcCud3Qb7YuFKkiRJkiRJrSilXAmcONH27iooSZIkSZKkgWThSpIkSZIkSQPJwpUkSZIkSZIGkoUrSZIkSZIkDSQLV5IkSZIkSRpIFq4kSZIkSZI0kKKUMtl9kCRJkiRJkp7EEVeSJEmSJEkaSBauJEmSJEmSNJAsXEmSJEmSJGkgWbiSJEmSJEnSQLJwNSAiYvVk92E6iYiNEXFN17LfGLc9KSK+sfV6N3VFRImIL3RdnhMRD/n41RERr2ge40Mnuy96Mp//7fOzsF29Ht+IWBYRx22t/mhzfga0IyLeHRE3RMR1zTbh8ZPdJ40uIvaKiPMj4paIuC0iPhQR88a4/TsiIm3NPk4lzXvKuV2X3xUR753ELk0LXd81b4iIayPinRFhbaVFPriartaWUpZ2LXdOdoemiTXAERGxsLn8QuDe8QRExJzqvZo+zgC+35z2LSJmt9MdjfCUn/+SNIYJfQZodBFxAnAqcEwp5SjgFODuye2VRhMRAXwV+LdSysHA04DFwPvGaPYOwMLV6NYDr4yInSe7I9PM0HfNw+lsD74E+JNJ7tO0ZuFqgETE4oi4KCKuiojrI+Llzfr9IuLGiPhkU9W9sOuLk/oUEbMj4m8i4ormV7c3d129bUR8MyJ+GhEft2I+pm8BL2vOnwF8ceiKiHhmRPwwIq6OiMsi4pBm/ZkR8fWIuBi4aOt3efBFxGLg2cAbgNObdSdFxKVbem5GxOqIODcirgVOmLyezzgTef5fGhFLu273/Yg4eqv2egoZOQo2Iv4uIs5szt8ZEX/a9TnpyJRxGuvx1eQZ4zNgtNfCSyPipoi4MiI+7MjPUS0BlpdS1gOUUpaXUu6LiGMj4nvN43dBRCyBX4w6/FAzkuLHEfHMSe39zPN8YF0p5bMApZSNwDnA6yNiUUR8oPm/XBcRb42ItwF7AJdExCWT2O9BtgH4BzqP42aa75gXN4/nRRGxT0RsFxF3dW1vLoqIuyNi7tbu+FRRSnkQeBNwdnSM+p0zIv6w2X65NiL+cvJ6PfX45XywrANOK6UcA5wMnNv88gBwMPDRpqr7KPCqSerjVLEwhncT/Fqz7g3AylLKM4BnAG+MiP2b654JvBU4DDgQeOVW7/HUcR5wekQsAI4CLu+67ibgOaWUXwL+GPiLruuOAV5dSnneVuvp1PJy4NullJuBhyPi2Gb9aM/NRcDlpZSjSynf3+q9nbkm8vz/NHAmQEQ8DVhQSrl2q/V4+lnefE7+PfCuye6MVMlonwFP0rz/fAJ4SSnlWGCXrdTHqehCYO+IuDkiPhYRz2u+gH+EzjbJscBn2HxETyqlLAXe0lynredw4MruFaWUVcDPgLOA/YClzei5fy6lfBi4Dzi5lHLyVu7rVPJR4HURsd2I9R8B/nHo8QQ+XEpZCVwDDG2vnwpcUEp5Yqv1dgoqpdwOzAZ2ZZTvnBHxEjrv9ceXUo4G/nrSOjwFWbgaLAH8RURcB3wX2BPYrbnujlLKNc35K+m8cWt03bsKntasexHwWxFxDZ0vmzvRKQgC/Hcp5fbml50v0vnVU1tQSrmOzvPvDDqjT7ptB3w5In4MfJDOBsiQ75RSHtkqnZyazqBTFKE5HdpVZLTn5kbgK1u3i5rg8//LwKnNl6XXA5/bKp2dvr7anPpZqOlktM+ALTkU/n979xYiZRnHcfz7EyIpyzC8icoQOiAFgREUBUZBN90IW2snqYuwCPOmq/JGuogi6YCBW5KUkGwQkRS4LdVSEMR6CG2NElqtruwiqs2UtH8XzzPOu9PMOrM68747/j43O/Mehj/vPDvP+Xn4MSIm8/vtM1x7TouIKWA5aTTEr8AwsAa4HhjNZcL1wOWF27bne78gjci/pKdBWysrgKGIOAHgMmX7cuPfO8BTDaduAd7Nr7dRL2MOA4P59ar83trXqs55F7A1Io6C03CnvNZMtTxI6jVbHhH/SDoEzM/njheuOwl4qmDnBKyNiJFpB6UVQDRc2/jeptsBvEQqRFxaOP4c8HlErFRaEH+scO6vHsU250haRBoef4OkIPXYBPAxrdPmsdyYZb3XUfqPiKOSRkm9bPeRKlHW2gmmd6zNbzhfyw9P4nLMbJzu+VqPzZAHfIi/qzOW88oxYEzSfuBJYCIiWk2zd5mwPAeAgeIBSRcDVwKHygioj7wC7AG2tnHtDtJgikWkMstn3QysH0haSiqXHKF1nfPuMmLrFx5xVS0LgSO50eoOYEnZAfWZEeCJ2hxtSddIujCfuzkP4ZxH6mHw1KuZvQVsiIj9DccXUl+s+pGeRjS3DQDbImJJRFwVEVcAk8DtOG1W0WzS/xbgNWA8In7rbnhz3mFgmaTz80iHO8sOqM/4+VZPqzxgHs2/q++BparvmDzY+IGWSLpW0tWFQzcC3wGLlRZuR9J5koojxAfz8dtI031+71nA9ilwgaTVcGrzmY2kkcojwBrlTX5yowrAn8BFvQ91bsmje94jTWOr+Yq8ph5pAMWX+dopYBx4FfjIHaUzk7QY2AxsioigdZ1zFHhUeRfMQhq2NrjhqgLyD/Bx0tzim3Jv0GrSeil29mwh9eTsyVN5hqj31o8Dm0iFmUngg6afYABExC95XYFGLwLPS9qLR0J04n7+n+bez8edNitmNuk/InYDf9BeT+c5qZYXRsTPpML1t/nv3lID6xN+vpXWKg9YRZPvKiL+Jq2/tFPSblLF3Y0rzS0A3pZ0IC/FsYy0BuEA8ILSBiffALcW7jmWf8c3M72Sb12WK/0rgXslHQR+IK0B/AypHP8TsC9/bw/k294g/S94cfbT2wgUdxdcS2pI2Qc8DKwrnBsGHsLTBFuprac8QVri5xNgQz7XtM4ZETtJo9l25WmEXqezA0q/D1Ympd2l3owI71xiZqfkaaxPR8Q9ZcdiZ0bSZaSpKtdFxL8lh1NJzgu7y8+3v0haEBFTeROf14GDEfFy2XHNdZLGSPnurrJjMTOzOo+4Kpmkx0mLQK4vOxYzMzv78pSHr4Fn3WjVnPPC7vLz7UuP5R77CdI05aGS4zEzM+saj7gyMzMzMzMzM7NK8ogrMzMzMzMzMzOrJDdcmZmZmZmZmZlZJbnhyszMzMzMzMzMKskNV2ZmZmZmZmZmVkluuDIzMzMzMzMzs0r6DyA0tH0Au15MAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_calmap=df_trips_hourly.loc[df_trips_hourly['user_type'] == 2].groupby(['unplug_Day'])['count'].agg('sum')\n",
    "df_calmap.index = pd.DatetimeIndex(df_calmap.index)\n",
    "series_calmap = pd.Series(df_calmap,index=df_calmap.index)\n",
    "\n",
    "calmap.calendarplot(df_calmap, monthticks=1, daylabels='MTWTFSS',dayticks=[0, 2, 4, 6],cmap='Blues_r',linewidth=0,fig_kws=dict(figsize=(18, 5)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 1296x360 with 2 Axes>,\n",
       " array([<matplotlib.axes._subplots.AxesSubplot object at 0x111dbcba8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x111e296a0>],\n",
       "       dtype=object))"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import calmap\n",
    "\n",
    "df_calmap=df_trips_hourly.loc[df_trips_hourly['user_type'] == 3].groupby(['unplug_Day'])['count'].agg('sum')\n",
    "df_calmap.index = pd.DatetimeIndex(df_calmap.index)\n",
    "series_calmap = pd.Series(df_calmap,index=df_calmap.index)\n",
    "\n",
    "calmap.calendarplot(df_calmap, monthticks=1, daylabels='MTWTFSS',dayticks=[0, 2, 4, 6],cmap='Greens_r', linewidth=0,fig_kws=dict(figsize=(18, 5)))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}