uber_stats.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> Uber Pickups </h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> The average number of active vehicles total </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1307\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from pprint import pprint\n",
    "\n",
    "uber_data = pd.read_csv('datasets/uber_Uber-Jan-Feb-FOIL.csv') #reading in the CSV file\n",
    "uber_data.rename(columns = {'dispatching_base_number':'Dispatch_Base_No', 'date':'Date', 'active_vehicles':'Active_Cars', 'trips':'Trips'}, inplace=True) #renaming the columns\n",
    "uber_data.Date = pd.to_datetime(uber_data.Date) #converting the Date column to date-time objects instead of strings\n",
    "\n",
    "avg_cars = sum(uber_data.Active_Cars) / len(uber_data.Active_Cars)\n",
    "print avg_cars #shows the total average number of active vehicles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> The average number of trips per day </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{Timestamp('2015-01-01 00:00:00'): 9406.166666666666,\n",
      " Timestamp('2015-01-02 00:00:00'): 6531.5,\n",
      " Timestamp('2015-01-03 00:00:00'): 9741.5,\n",
      " Timestamp('2015-01-04 00:00:00'): 6799.666666666667,\n",
      " Timestamp('2015-01-05 00:00:00'): 7125.333333333333,\n",
      " Timestamp('2015-01-06 00:00:00'): 8737.666666666666,\n",
      " Timestamp('2015-01-07 00:00:00'): 10350.333333333334,\n",
      " Timestamp('2015-01-08 00:00:00'): 11902.166666666666,\n",
      " Timestamp('2015-01-09 00:00:00'): 11716.0,\n",
      " Timestamp('2015-01-10 00:00:00'): 13080.666666666666,\n",
      " Timestamp('2015-01-11 00:00:00'): 9504.333333333334,\n",
      " Timestamp('2015-01-12 00:00:00'): 9607.666666666666,\n",
      " Timestamp('2015-01-13 00:00:00'): 10583.166666666666,\n",
      " Timestamp('2015-01-14 00:00:00'): 10554.833333333334,\n",
      " Timestamp('2015-01-15 00:00:00'): 11121.5,\n",
      " Timestamp('2015-01-16 00:00:00'): 12080.0,\n",
      " Timestamp('2015-01-17 00:00:00'): 12227.166666666666,\n",
      " Timestamp('2015-01-18 00:00:00'): 12078.833333333334,\n",
      " Timestamp('2015-01-19 00:00:00'): 7625.833333333333,\n",
      " Timestamp('2015-01-20 00:00:00'): 9128.666666666666,\n",
      " Timestamp('2015-01-21 00:00:00'): 9857.833333333334,\n",
      " Timestamp('2015-01-22 00:00:00'): 10933.666666666666,\n",
      " Timestamp('2015-01-23 00:00:00'): 11969.833333333334,\n",
      " Timestamp('2015-01-24 00:00:00'): 13451.5,\n",
      " Timestamp('2015-01-25 00:00:00'): 9649.166666666666,\n",
      " Timestamp('2015-01-26 00:00:00'): 7232.5,\n",
      " Timestamp('2015-01-27 00:00:00'): 4207.333333333333,\n",
      " Timestamp('2015-01-28 00:00:00'): 10074.333333333334,\n",
      " Timestamp('2015-01-29 00:00:00'): 11499.0,\n",
      " Timestamp('2015-01-30 00:00:00'): 13953.833333333334,\n",
      " Timestamp('2015-01-31 00:00:00'): 15376.166666666666,\n",
      " Timestamp('2015-02-01 00:00:00'): 12818.333333333334,\n",
      " Timestamp('2015-02-02 00:00:00'): 11496.666666666666,\n",
      " Timestamp('2015-02-03 00:00:00'): 11698.0,\n",
      " Timestamp('2015-02-04 00:00:00'): 11139.166666666666,\n",
      " Timestamp('2015-02-05 00:00:00'): 13485.5,\n",
      " Timestamp('2015-02-06 00:00:00'): 14323.333333333334,\n",
      " Timestamp('2015-02-07 00:00:00'): 13526.166666666666,\n",
      " Timestamp('2015-02-08 00:00:00'): 10500.0,\n",
      " Timestamp('2015-02-09 00:00:00'): 10326.0,\n",
      " Timestamp('2015-02-10 00:00:00'): 10794.333333333334,\n",
      " Timestamp('2015-02-11 00:00:00'): 12078.333333333334,\n",
      " Timestamp('2015-02-12 00:00:00'): 13872.333333333334,\n",
      " Timestamp('2015-02-13 00:00:00'): 16337.333333333334,\n",
      " Timestamp('2015-02-14 00:00:00'): 16724.166666666668,\n",
      " Timestamp('2015-02-15 00:00:00'): 14900.166666666666,\n",
      " Timestamp('2015-02-16 00:00:00'): 12016.333333333334,\n",
      " Timestamp('2015-02-17 00:00:00'): 12175.166666666666,\n",
      " Timestamp('2015-02-18 00:00:00'): 12040.5,\n",
      " Timestamp('2015-02-19 00:00:00'): 14792.833333333334,\n",
      " Timestamp('2015-02-20 00:00:00'): 16819.166666666668,\n",
      " Timestamp('2015-02-21 00:00:00'): 16396.666666666668,\n",
      " Timestamp('2015-02-22 00:00:00'): 11073.333333333334,\n",
      " Timestamp('2015-02-23 00:00:00'): 11869.5,\n",
      " Timestamp('2015-02-24 00:00:00'): 13185.833333333334,\n",
      " Timestamp('2015-02-25 00:00:00'): 12448.5,\n",
      " Timestamp('2015-02-26 00:00:00'): 13928.0,\n",
      " Timestamp('2015-02-27 00:00:00'): 14801.0,\n",
      " Timestamp('2015-02-28 00:00:00'): 14696.833333333334}\n"
     ]
    }
   ],
   "source": [
    "date_dict = {} #empty date: avg num trips dict\n",
    "date_set = set() #empty set for unique dates\n",
    "\n",
    "for date in uber_data.Date:\n",
    "    date_set.add(date)\n",
    "\n",
    "for date in date_set:\n",
    "    avg_trips_per_day = uber_data.Trips[uber_data.Date == date].mean()\n",
    "    date_dict[date] = avg_trips_per_day\n",
    "\n",
    "pprint(date_dict) #pretty prints the average number of trips per day"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> The average number of active vehicles per dispatching base per day </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{Timestamp('2015-01-01 00:00:00'): {'B02512': 190.0,\n",
      "                                    'B02598': 870.0,\n",
      "                                    'B02617': 1228.0,\n",
      "                                    'B02682': 945.0,\n",
      "                                    'B02764': 3427.0,\n",
      "                                    'B02765': 225.0},\n",
      " Timestamp('2015-01-02 00:00:00'): {'B02512': 175.0,\n",
      "                                    'B02598': 785.0,\n",
      "                                    'B02617': 1137.0,\n",
      "                                    'B02682': 890.0,\n",
      "                                    'B02764': 3147.0,\n",
      "                                    'B02765': 196.0},\n",
      " Timestamp('2015-01-03 00:00:00'): {'B02512': 173.0,\n",
      "                                    'B02598': 818.0,\n",
      "                                    'B02617': 1188.0,\n",
      "                                    'B02682': 915.0,\n",
      "                                    'B02764': 3215.0,\n",
      "                                    'B02765': 201.0},\n",
      " Timestamp('2015-01-04 00:00:00'): {'B02512': 147.0,\n",
      "                                    'B02598': 746.0,\n",
      "                                    'B02617': 1088.0,\n",
      "                                    'B02682': 812.0,\n",
      "                                    'B02764': 2862.0,\n",
      "                                    'B02765': 183.0},\n",
      " Timestamp('2015-01-05 00:00:00'): {'B02512': 194.0,\n",
      "                                    'B02598': 907.0,\n",
      "                                    'B02617': 1218.0,\n",
      "                                    'B02682': 951.0,\n",
      "                                    'B02764': 3387.0,\n",
      "                                    'B02765': 227.0},\n",
      " Timestamp('2015-01-06 00:00:00'): {'B02512': 218.0,\n",
      "                                    'B02598': 933.0,\n",
      "                                    'B02617': 1336.0,\n",
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      "                                    'B02765': 234.0},\n",
      " Timestamp('2015-01-07 00:00:00'): {'B02512': 217.0,\n",
      "                                    'B02598': 974.0,\n",
      "                                    'B02617': 1363.0,\n",
      "                                    'B02682': 1039.0,\n",
      "                                    'B02764': 3603.0,\n",
      "                                    'B02765': 248.0},\n",
      " Timestamp('2015-01-08 00:00:00'): {'B02512': 238.0,\n",
      "                                    'B02598': 1070.0,\n",
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      " Timestamp('2015-01-09 00:00:00'): {'B02512': 224.0,\n",
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      "                                    'B02765': 280.0},\n",
      " Timestamp('2015-01-10 00:00:00'): {'B02512': 206.0,\n",
      "                                    'B02598': 949.0,\n",
      "                                    'B02617': 1331.0,\n",
      "                                    'B02682': 1057.0,\n",
      "                                    'B02764': 3558.0,\n",
      "                                    'B02765': 245.0},\n",
      " Timestamp('2015-01-11 00:00:00'): {'B02512': 162.0,\n",
      "                                    'B02598': 832.0,\n",
      "                                    'B02617': 1228.0,\n",
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      "                                    'B02617': 1405.0,\n",
      "                                    'B02682': 1174.0,\n",
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      "                                    'B02765': 271.0},\n",
      " Timestamp('2015-01-15 00:00:00'): {'B02512': 237.0,\n",
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      "                                    'B02682': 1208.0,\n",
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      " Timestamp('2015-01-16 00:00:00'): {'B02512': 234.0,\n",
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      "                                    'B02617': 1445.0,\n",
      "                                    'B02682': 1250.0,\n",
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      " Timestamp('2015-01-18 00:00:00'): {'B02512': 177.0,\n",
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      " Timestamp('2015-01-21 00:00:00'): {'B02512': 242.0,\n",
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      " Timestamp('2015-01-23 00:00:00'): {'B02512': 246.0,\n",
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      "                                    'B02764': 4040.0,\n",
      "                                    'B02765': 299.0},\n",
      " Timestamp('2015-01-24 00:00:00'): {'B02512': 211.0,\n",
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      "                                    'B02617': 1367.0,\n",
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      " Timestamp('2015-01-25 00:00:00'): {'B02512': 183.0,\n",
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      "                                    'B02617': 1203.0,\n",
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      " Timestamp('2015-01-26 00:00:00'): {'B02512': 197.0,\n",
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      "                                    'B02617': 1150.0,\n",
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      " Timestamp('2015-01-27 00:00:00'): {'B02512': 112.0,\n",
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      " Timestamp('2015-01-28 00:00:00'): {'B02512': 235.0,\n",
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      " Timestamp('2015-02-12 00:00:00'): {'B02512': 269.0,\n",
      "                                    'B02598': 1181.0,\n",
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      " Timestamp('2015-02-13 00:00:00'): {'B02512': 281.0,\n",
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      " Timestamp('2015-02-14 00:00:00'): {'B02512': 236.0,\n",
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      "                                    'B02765': 583.0},\n",
      " Timestamp('2015-02-15 00:00:00'): {'B02512': 210.0,\n",
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      "                                    'B02764': 3651.0,\n",
      "                                    'B02765': 521.0},\n",
      " Timestamp('2015-02-16 00:00:00'): {'B02512': 207.0,\n",
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      "                                    'B02682': 1164.0,\n",
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      "                                    'B02765': 508.0},\n",
      " Timestamp('2015-02-17 00:00:00'): {'B02512': 241.0,\n",
      "                                    'B02598': 1066.0,\n",
      "                                    'B02617': 1378.0,\n",
      "                                    'B02682': 1314.0,\n",
      "                                    'B02764': 3826.0,\n",
      "                                    'B02765': 578.0},\n",
      " Timestamp('2015-02-18 00:00:00'): {'B02512': 228.0,\n",
      "                                    'B02598': 1078.0,\n",
      "                                    'B02617': 1394.0,\n",
      "                                    'B02682': 1314.0,\n",
      "                                    'B02764': 3842.0,\n",
      "                                    'B02765': 586.0},\n",
      " Timestamp('2015-02-19 00:00:00'): {'B02512': 250.0,\n",
      "                                    'B02598': 1127.0,\n",
      "                                    'B02617': 1452.0,\n",
      "                                    'B02682': 1428.0,\n",
      "                                    'B02764': 4110.0,\n",
      "                                    'B02765': 663.0},\n",
      " Timestamp('2015-02-20 00:00:00'): {'B02512': 272.0,\n",
      "                                    'B02598': 1186.0,\n",
      "                                    'B02617': 1574.0,\n",
      "                                    'B02682': 1497.0,\n",
      "                                    'B02764': 4384.0,\n",
      "                                    'B02765': 736.0},\n",
      " Timestamp('2015-02-21 00:00:00'): {'B02512': 238.0,\n",
      "                                    'B02598': 1044.0,\n",
      "                                    'B02617': 1443.0,\n",
      "                                    'B02682': 1374.0,\n",
      "                                    'B02764': 3981.0,\n",
      "                                    'B02765': 685.0},\n",
      " Timestamp('2015-02-22 00:00:00'): {'B02512': 199.0,\n",
      "                                    'B02598': 909.0,\n",
      "                                    'B02617': 1248.0,\n",
      "                                    'B02682': 1220.0,\n",
      "                                    'B02764': 3478.0,\n",
      "                                    'B02765': 566.0},\n",
      " Timestamp('2015-02-23 00:00:00'): {'B02512': 238.0,\n",
      "                                    'B02598': 966.0,\n",
      "                                    'B02617': 1332.0,\n",
      "                                    'B02682': 1262.0,\n",
      "                                    'B02764': 3734.0,\n",
      "                                    'B02765': 665.0},\n",
      " Timestamp('2015-02-24 00:00:00'): {'B02512': 247.0,\n",
      "                                    'B02598': 1061.0,\n",
      "                                    'B02617': 1456.0,\n",
      "                                    'B02682': 1346.0,\n",
      "                                    'B02764': 3965.0,\n",
      "                                    'B02765': 698.0},\n",
      " Timestamp('2015-02-25 00:00:00'): {'B02512': 246.0,\n",
      "                                    'B02598': 1076.0,\n",
      "                                    'B02617': 1473.0,\n",
      "                                    'B02682': 1395.0,\n",
      "                                    'B02764': 3934.0,\n",
      "                                    'B02765': 706.0},\n",
      " Timestamp('2015-02-26 00:00:00'): {'B02512': 243.0,\n",
      "                                    'B02598': 1134.0,\n",
      "                                    'B02617': 1539.0,\n",
      "                                    'B02682': 1465.0,\n",
      "                                    'B02764': 4101.0,\n",
      "                                    'B02765': 745.0},\n",
      " Timestamp('2015-02-27 00:00:00'): {'B02512': 272.0,\n",
      "                                    'B02598': 1114.0,\n",
      "                                    'B02617': 1551.0,\n",
      "                                    'B02682': 1510.0,\n",
      "                                    'B02764': 4253.0,\n",
      "                                    'B02765': 786.0},\n",
      " Timestamp('2015-02-28 00:00:00'): {'B02512': 230.0,\n",
      "                                    'B02598': 994.0,\n",
      "                                    'B02617': 1372.0,\n",
      "                                    'B02682': 1386.0,\n",
      "                                    'B02764': 3952.0,\n",
      "                                    'B02765': 747.0}}\n"
     ]
    }
   ],
   "source": [
    "dispatch_set = set() #empty set for unique dispatch bases\n",
    "date_set = set() #empty set for unique dates\n",
    "\n",
    "date_set = set(uber_data.Date) #coverts the date column into a set of unique dates\n",
    "\n",
    "dispatch_set = set(uber_data.Dispatch_Base_No) #converts the dispatch base column into a set of unqiue dispatch bases\n",
    "\n",
    "for date in date_set:\n",
    "    inner_dict[date] = {} #creates the empty inner dictionary {date: dispatch base no}\n",
    "    for base in dispatch_set:\n",
    "        avg_no_active_cars = uber_data.Active_Cars[(uber_data.Dispatch_Base_No == base) & (uber_data.Date == date)].mean() #creates the avg num of active cars per date per dispatch base\n",
    "        inner_dict[date][base] = avg_no_active_cars #fills up the embedded dictionary {date: {dispatch base no: avg number active cars}}\n",
    "\n",
    "pprint(inner_dict) #pretty prints the average number of active cars per dispatching base per day\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> The average number of trips per vehicle per day </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7444 1.39042629411\n",
      "8693 1.60518041336\n",
      "8681 1.69298851899\n",
      "7752 1.65355177159\n",
      "8937 1.60270038417\n",
      "8376 1.37285100287\n",
      "8515 1.4184771971\n",
      "8273 1.46017164269\n",
      "7849 1.3447360598\n",
      "9123 1.52058898754\n",
      "8765 1.8706978513\n",
      "9227 1.50948303891\n",
      "7559 1.40007496582\n",
      "3496 1.2034706331\n",
      "8833 1.52671798936\n",
      "8029 1.34441815087\n",
      "9030 1.63818752307\n",
      "7527 1.62444090164\n",
      "7939 1.87683167485\n",
      "7592 1.20240604145\n",
      "6571 1.44640592502\n",
      "7551 1.59135655322\n",
      "7840 1.49209183673\n",
      "6885 1.36618252239\n",
      "7643 1.75997644904\n",
      "8223 1.86989744213\n",
      "5838 1.16472536257\n",
      "6863 1.75999320025\n",
      "8973 1.86383223745\n",
      "8197 1.44802976699\n",
      "7948 1.24029105855\n",
      "7999 1.48795682794\n",
      "8080 1.37642326733\n",
      "9649 1.74309945763\n",
      "6330 1.03183254344\n",
      "8830 1.40979614949\n",
      "8119 1.66598924334\n",
      "6884 1.03505713732\n",
      "7815 1.28910215398\n",
      "5945 1.28273058593\n",
      "8267 1.3225676384\n",
      "8185 1.3609244553\n",
      "8442 1.4262615494\n",
      "7688 1.34313215401\n",
      "7364 1.3046804273\n",
      "6510 1.49639016897\n",
      "6533 1.10707178938\n",
      "8773 1.5030016338\n",
      "7216 1.21087398374\n",
      "7080 1.62382297552\n",
      "6787 1.42171307893\n",
      "8490 1.40987436199\n",
      "7346 1.78065160178\n",
      "7226 1.45308607805\n",
      "8403 1.44890713634\n",
      "7620 1.45319335083\n",
      "9604 1.70109676524\n",
      "9486 1.56029938857\n",
      "7989 1.46651646013\n",
      "{Timestamp('2015-01-01 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-02 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-03 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-04 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-05 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-06 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-07 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-08 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-09 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-10 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-11 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-12 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-13 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-14 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-15 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-16 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-17 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-18 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-19 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-20 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-21 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-22 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-23 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-24 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-25 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-26 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-27 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-28 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-29 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-30 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-01-31 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-01 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-02 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-03 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-04 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-05 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-06 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-07 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-08 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-09 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-10 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-11 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-12 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-13 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-14 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-15 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-16 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-17 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-18 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-19 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-20 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-21 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-22 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-23 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-24 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-25 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-26 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-27 00:00:00'): 8.799098760796095,\n",
      " Timestamp('2015-02-28 00:00:00'): 8.799098760796095}\n"
     ]
    }
   ],
   "source": [
    "date_set = set(uber_data.Date)\n",
    "avg_trips_per_car_per_date_dict = {}\n",
    "\n",
    "for date in date_set:\n",
    "    avg_num_trips = uber_data.Trips[uber_data.Date == date].mean() #creates the avg num of trips on a given date\n",
    "    total_vehicles = uber_data.Active_Cars[uber_data.Date == date].sum()\n",
    "    print total_vehicles, (avg_num_trips/total_vehicles)\n",
    "#     avg_num_cars = uber_data.Active_Cars[uber_data.Date == date].mean() #creates the avg num of cars on a given date\n",
    "#     avg_num_trips_per_car = avg_num_trips / avg_num_cars #gives the average number of trips per car for a given date\n",
    "    avg_trips_per_car_per_date_dict[date] = avg_num_trips_per_car\n",
    "\n",
    "pprint(avg_trips_per_car_per_date_dict) #pretty prints the average number of trips per car per day"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> The standard deviation in active vehicles per day </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{Timestamp('2015-01-01 00:00:00'): 1190.6658221348255,\n",
      " Timestamp('2015-01-02 00:00:00'): 1095.0428302125904,\n",
      " Timestamp('2015-01-03 00:00:00'): 1119.008310961094,\n",
      " Timestamp('2015-01-04 00:00:00'): 996.5311836565878,\n",
      " Timestamp('2015-01-05 00:00:00'): 1172.4559977528654,\n",
      " Timestamp('2015-01-06 00:00:00'): 1198.7856633554918,\n",
      " Timestamp('2015-01-07 00:00:00'): 1244.2383480132198,\n",
      " Timestamp('2015-01-08 00:00:00'): 1319.9502137075726,\n",
      " Timestamp('2015-01-09 00:00:00'): 1314.9256632981196,\n",
      " Timestamp('2015-01-10 00:00:00'): 1229.4131391304825,\n",
      " Timestamp('2015-01-11 00:00:00'): 1106.1968028640592,\n",
      " Timestamp('2015-01-12 00:00:00'): 1198.3486415341183,\n",
      " Timestamp('2015-01-13 00:00:00'): 1258.82936360202,\n",
      " Timestamp('2015-01-14 00:00:00'): 1283.0297606317113,\n",
      " Timestamp('2015-01-15 00:00:00'): 1320.3286964489814,\n",
      " Timestamp('2015-01-16 00:00:00'): 1367.2716506483512,\n",
      " Timestamp('2015-01-17 00:00:00'): 1263.4883062379326,\n",
      " Timestamp('2015-01-18 00:00:00'): 1134.269001016367,\n",
      " Timestamp('2015-01-19 00:00:00'): 1020.4231311895408,\n",
      " Timestamp('2015-01-20 00:00:00'): 1257.502869446693,\n",
      " Timestamp('2015-01-21 00:00:00'): 1269.8427724197459,\n",
      " Timestamp('2015-01-22 00:00:00'): 1331.8574122880673,\n",
      " Timestamp('2015-01-23 00:00:00'): 1386.9419598526824,\n",
      " Timestamp('2015-01-24 00:00:00'): 1261.9972134147788,\n",
      " Timestamp('2015-01-25 00:00:00'): 1142.4449950289365,\n",
      " Timestamp('2015-01-26 00:00:00'): 1028.3638299097584,\n",
      " Timestamp('2015-01-27 00:00:00'): 551.0897083657675,\n",
      " Timestamp('2015-01-28 00:00:00'): 1262.9275117757154,\n",
      " Timestamp('2015-01-29 00:00:00'): 1356.8762655452413,\n",
      " Timestamp('2015-01-30 00:00:00'): 1412.3442096977165,\n",
      " Timestamp('2015-01-31 00:00:00'): 1356.3406283083907,\n",
      " Timestamp('2015-02-01 00:00:00'): 1290.436205319736,\n",
      " Timestamp('2015-02-02 00:00:00'): 1109.5555867102828,\n",
      " Timestamp('2015-02-03 00:00:00'): 1250.9517443397513,\n",
      " Timestamp('2015-02-04 00:00:00'): 1316.5411374760254,\n",
      " Timestamp('2015-02-05 00:00:00'): 1390.5439822841515,\n",
      " Timestamp('2015-02-06 00:00:00'): 1415.3739788479934,\n",
      " Timestamp('2015-02-07 00:00:00'): 1315.8751333871564,\n",
      " Timestamp('2015-02-08 00:00:00'): 1171.02325624501,\n",
      " Timestamp('2015-02-09 00:00:00'): 1193.1879427259844,\n",
      " Timestamp('2015-02-10 00:00:00'): 1244.0683930824166,\n",
      " Timestamp('2015-02-11 00:00:00'): 1287.8402721869923,\n",
      " Timestamp('2015-02-12 00:00:00'): 1378.3840901577469,\n",
      " Timestamp('2015-02-13 00:00:00'): 1463.370720858753,\n",
      " Timestamp('2015-02-14 00:00:00'): 1378.8985096808249,\n",
      " Timestamp('2015-02-15 00:00:00'): 1217.2675000453542,\n",
      " Timestamp('2015-02-16 00:00:00'): 1176.2315673369765,\n",
      " Timestamp('2015-02-17 00:00:00'): 1266.7971818724575,\n",
      " Timestamp('2015-02-18 00:00:00'): 1273.6063756121825,\n",
      " Timestamp('2015-02-19 00:00:00'): 1358.060087035916,\n",
      " Timestamp('2015-02-20 00:00:00'): 1445.2001130178016,\n",
      " Timestamp('2015-02-21 00:00:00'): 1313.7798014380746,\n",
      " Timestamp('2015-02-22 00:00:00'): 1153.3625622500497,\n",
      " Timestamp('2015-02-23 00:00:00'): 1228.2655114700024,\n",
      " Timestamp('2015-02-24 00:00:00'): 1303.7808737156204,\n",
      " Timestamp('2015-02-25 00:00:00'): 1289.497679977233,\n",
      " Timestamp('2015-02-26 00:00:00'): 1344.8709107816508,\n",
      " Timestamp('2015-02-27 00:00:00'): 1393.4934517248369,\n",
      " Timestamp('2015-02-28 00:00:00'): 1300.8204206064213}\n"
     ]
    }
   ],
   "source": [
    "date_set = set(uber_data.Date)\n",
    "std_dev_active_cars_per_day_dict = {}\n",
    "\n",
    "for date in date_set:\n",
    "    std_dev_active_cars = uber_data.Active_Cars[uber_data.Date == date].std() #creates the std deviation of active cars on a given date\n",
    "    std_dev_active_cars_per_day_dict[date] = std_dev_active_cars\n",
    "\n",
    "pprint(std_dev_active_cars_per_day_dict) #pretty prints the standard deviation of active cars on a given day"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> For the month of January, which Dispatching Bases have active vehicles outside of one standard deviation from the mean? </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'B02512', 'B02598', 'B02617', 'B02682', 'B02764', 'B02765'}"
      ]
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# jan_only_dispatch = uber_data.Dispatch_Base_No[uber_data.Date.dt.month==1]\n",
    "jan_dispatch_set = set(uber_data.Dispatch_Base_No[uber_data.Date.dt.month==1])\n",
    "jan_dispatch_set"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> Which month showed more activity for Uber, January 2015 or February 2015? Prove it.</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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