Anls_TimeSeries_month_univar.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import statsmodels.formula.api as smf\n",
    "import numpy as np\n",
    "import pylab as pl\n",
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('subset_records_800m_hockey.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>tripduration</th>\n",
       "      <th>starttime</th>\n",
       "      <th>stoptime</th>\n",
       "      <th>start station id</th>\n",
       "      <th>start station name</th>\n",
       "      <th>start station latitude</th>\n",
       "      <th>start station longitude</th>\n",
       "      <th>end station id</th>\n",
       "      <th>end station name</th>\n",
       "      <th>...</th>\n",
       "      <th>usertype</th>\n",
       "      <th>birth year</th>\n",
       "      <th>gender</th>\n",
       "      <th>startdate</th>\n",
       "      <th>stopdate</th>\n",
       "      <th>Event_type</th>\n",
       "      <th>End_Time</th>\n",
       "      <th>E_Time</th>\n",
       "      <th>TripStartHM</th>\n",
       "      <th>EventEndHM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>397</td>\n",
       "      <td>21:51:17</td>\n",
       "      <td>21:57:54</td>\n",
       "      <td>83</td>\n",
       "      <td>Atlantic Ave &amp; Fort Greene Pl</td>\n",
       "      <td>40.683826</td>\n",
       "      <td>-73.976323</td>\n",
       "      <td>365</td>\n",
       "      <td>Fulton St &amp; Grand Ave</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1970.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-12-06 20:54:00</td>\n",
       "      <td>20:54:00</td>\n",
       "      <td>21.850000</td>\n",
       "      <td>20.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>705</td>\n",
       "      <td>20:58:36</td>\n",
       "      <td>21:10:21</td>\n",
       "      <td>274</td>\n",
       "      <td>Lafayette Ave &amp; Fort Greene Pl</td>\n",
       "      <td>40.686919</td>\n",
       "      <td>-73.976682</td>\n",
       "      <td>418</td>\n",
       "      <td>Front St &amp; Gold St</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-12-06 20:54:00</td>\n",
       "      <td>20:54:00</td>\n",
       "      <td>20.966667</td>\n",
       "      <td>20.9</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>687</td>\n",
       "      <td>20:58:58</td>\n",
       "      <td>21:10:25</td>\n",
       "      <td>274</td>\n",
       "      <td>Lafayette Ave &amp; Fort Greene Pl</td>\n",
       "      <td>40.686919</td>\n",
       "      <td>-73.976682</td>\n",
       "      <td>418</td>\n",
       "      <td>Front St &amp; Gold St</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-12-06 20:54:00</td>\n",
       "      <td>20:54:00</td>\n",
       "      <td>20.966667</td>\n",
       "      <td>20.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>292</td>\n",
       "      <td>21:19:57</td>\n",
       "      <td>21:24:49</td>\n",
       "      <td>397</td>\n",
       "      <td>Fulton St &amp; Clermont Ave</td>\n",
       "      <td>40.684157</td>\n",
       "      <td>-73.969223</td>\n",
       "      <td>421</td>\n",
       "      <td>Clermont Ave &amp; Park Ave</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-12-06 20:54:00</td>\n",
       "      <td>20:54:00</td>\n",
       "      <td>21.316667</td>\n",
       "      <td>20.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>690</td>\n",
       "      <td>21:12:22</td>\n",
       "      <td>21:23:52</td>\n",
       "      <td>467</td>\n",
       "      <td>Dean St &amp; 4 Ave</td>\n",
       "      <td>40.683125</td>\n",
       "      <td>-73.978951</td>\n",
       "      <td>120</td>\n",
       "      <td>Lexington Ave &amp; Classon Ave</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-12-06 20:54:00</td>\n",
       "      <td>20:54:00</td>\n",
       "      <td>21.200000</td>\n",
       "      <td>20.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  tripduration starttime  stoptime  start station id  \\\n",
       "0           0           397  21:51:17  21:57:54                83   \n",
       "1           3           705  20:58:36  21:10:21               274   \n",
       "2           4           687  20:58:58  21:10:25               274   \n",
       "3           5           292  21:19:57  21:24:49               397   \n",
       "4          10           690  21:12:22  21:23:52               467   \n",
       "\n",
       "               start station name  start station latitude  \\\n",
       "0   Atlantic Ave & Fort Greene Pl               40.683826   \n",
       "1  Lafayette Ave & Fort Greene Pl               40.686919   \n",
       "2  Lafayette Ave & Fort Greene Pl               40.686919   \n",
       "3        Fulton St & Clermont Ave               40.684157   \n",
       "4                 Dean St & 4 Ave               40.683125   \n",
       "\n",
       "   start station longitude  end station id             end station name  \\\n",
       "0               -73.976323             365        Fulton St & Grand Ave   \n",
       "1               -73.976682             418           Front St & Gold St   \n",
       "2               -73.976682             418           Front St & Gold St   \n",
       "3               -73.969223             421      Clermont Ave & Park Ave   \n",
       "4               -73.978951             120  Lexington Ave & Classon Ave   \n",
       "\n",
       "     ...        usertype  birth year  gender   startdate    stopdate  \\\n",
       "0    ...      Subscriber      1970.0       1  2016-01-01  2016-01-01   \n",
       "1    ...      Subscriber      1988.0       2  2016-01-03  2016-01-03   \n",
       "2    ...      Subscriber      1989.0       2  2016-01-03  2016-01-03   \n",
       "3    ...      Subscriber      1984.0       1  2016-01-03  2016-01-03   \n",
       "4    ...      Subscriber      1987.0       1  2016-01-05  2016-01-05   \n",
       "\n",
       "   Event_type             End_Time    E_Time TripStartHM EventEndHM  \n",
       "0         NaN  2017-12-06 20:54:00  20:54:00   21.850000       20.9  \n",
       "1         NaN  2017-12-06 20:54:00  20:54:00   20.966667       20.9  \n",
       "2         NaN  2017-12-06 20:54:00  20:54:00   20.966667       20.9  \n",
       "3         NaN  2017-12-06 20:54:00  20:54:00   21.316667       20.9  \n",
       "4         NaN  2017-12-06 20:54:00  20:54:00   21.200000       20.9  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Event_type\n",
       "hockey      20.908387\n",
       "no-event    20.900000\n",
       "Name: EventEndHM, dtype: float64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.replace(np.nan,'no-event',regex=True)\n",
    "df.groupby('Event_type')['EventEndHM'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>startdate</th>\n",
       "      <th>Type</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>no-event</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-01-03</td>\n",
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       "      <td>3</td>\n",
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       "      <th>2</th>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>no-event</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-07</td>\n",
       "      <td>no-event</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-01-09</td>\n",
       "      <td>no-event</td>\n",
       "      <td>4</td>\n",
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      ],
      "text/plain": [
       "    startdate      Type  Count\n",
       "0  2016-01-01  no-event      1\n",
       "1  2016-01-03  no-event      3\n",
       "2  2016-01-05  no-event      5\n",
       "3  2016-01-07  no-event     12\n",
       "4  2016-01-09  no-event      4"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.DataFrame(df.groupby(['startdate','Event_type']).size())\n",
    "data.reset_index(inplace=True)\n",
    "data.columns = ['startdate','Type','Count']\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>startdate</th>\n",
       "      <th>Type</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2016-03-08</td>\n",
       "      <td>hockey</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2016-03-21</td>\n",
       "      <td>hockey</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>2016-09-26</td>\n",
       "      <td>hockey</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>2016-10-03</td>\n",
       "      <td>hockey</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>2016-10-16</td>\n",
       "      <td>hockey</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>2016-10-18</td>\n",
       "      <td>hockey</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>2016-10-21</td>\n",
       "      <td>hockey</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>2016-10-23</td>\n",
       "      <td>hockey</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>2016-10-26</td>\n",
       "      <td>hockey</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>2016-10-30</td>\n",
       "      <td>hockey</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>2016-11-01</td>\n",
       "      <td>hockey</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>2016-11-03</td>\n",
       "      <td>hockey</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>2016-11-05</td>\n",
       "      <td>hockey</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>2016-11-07</td>\n",
       "      <td>hockey</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>2016-11-14</td>\n",
       "      <td>hockey</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>2016-11-18</td>\n",
       "      <td>hockey</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>2016-11-28</td>\n",
       "      <td>hockey</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>2016-11-30</td>\n",
       "      <td>hockey</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>2016-12-04</td>\n",
       "      <td>hockey</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>2016-12-06</td>\n",
       "      <td>hockey</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>2016-12-08</td>\n",
       "      <td>hockey</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>2016-12-13</td>\n",
       "      <td>hockey</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>2016-12-15</td>\n",
       "      <td>hockey</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>2016-12-18</td>\n",
       "      <td>hockey</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>2016-12-23</td>\n",
       "      <td>hockey</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>2016-12-27</td>\n",
       "      <td>hockey</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      startdate    Type  Count\n",
       "42   2016-03-08  hockey     16\n",
       "50   2016-03-21  hockey      9\n",
       "200  2016-09-26  hockey     31\n",
       "207  2016-10-03  hockey     48\n",
       "211  2016-10-16  hockey     33\n",
       "213  2016-10-18  hockey     45\n",
       "215  2016-10-21  hockey     31\n",
       "216  2016-10-23  hockey     38\n",
       "218  2016-10-26  hockey     56\n",
       "220  2016-10-30  hockey     22\n",
       "221  2016-11-01  hockey     43\n",
       "222  2016-11-03  hockey     44\n",
       "223  2016-11-05  hockey     23\n",
       "224  2016-11-07  hockey     56\n",
       "225  2016-11-14  hockey     44\n",
       "228  2016-11-18  hockey     39\n",
       "232  2016-11-28  hockey     38\n",
       "233  2016-11-30  hockey     15\n",
       "236  2016-12-04  hockey     27\n",
       "237  2016-12-06  hockey      5\n",
       "238  2016-12-08  hockey     23\n",
       "242  2016-12-13  hockey     26\n",
       "243  2016-12-15  hockey     16\n",
       "246  2016-12-18  hockey     19\n",
       "249  2016-12-23  hockey      9\n",
       "252  2016-12-27  hockey     19"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['Type'] <> 'no-event']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data['startdate'] = pd.to_datetime(data['startdate'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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B2cco/PLc/wCyLh2eD+fcZjPbCHws2NYBe51zmV82090ELAR+bmbzgVfxy2pfhi9LylXm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\nSZIkSZKkofw/z/oXAZiotwYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b972310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl.figure(figsize=(20,8))\n",
    "pl.plot(data[data['Type'] == 'no-event']['startdate'],data[data['Type'] == 'no-event']['Count'],'.-',label='NoEvent')\n",
    "pl.plot(data[data['Type'] <> 'no-event']['startdate'],data[data['Type'] <> 'no-event']['Count'],'o-',label='Hockey')\n",
    "#pl.annotate\n",
    "pl.legend(fontsize=15)\n",
    "pl.xlabel('Date',size=15)\n",
    "pl.ylabel('Number of trips',size=15)\n",
    "pl.title('Trip Count on Hockey Night and No Event Night',size=18)\n",
    "#pl.annotate(data[data['Type'] == 'no-event']['startdate'], xy=(data[data['Type'] <> 'no-event']['startdate'],data[data['Type'] <> 'no-event']['Count']), textcoords='offset points',\n",
    "#           rotation=0, fontsize=70, color='white')\n",
    "pl.savefig('hockey_compare.png',dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "lm = smf.ols(formula='Count ~ C(Type, Treatment(reference=\"no-event\"))', data=data).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>          <td>Count</td>      <th>  R-squared:         </th> <td>   0.146</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.142</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   43.28</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Wed, 06 Dec 2017</td> <th>  Prob (F-statistic):</th> <td>2.69e-10</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>21:05:56</td>     <th>  Log-Likelihood:    </th> <td> -976.91</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>   256</td>      <th>  AIC:               </th> <td>   1958.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>   254</td>      <th>  BIC:               </th> <td>   1965.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "                           <td></td>                             <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>                                          <td>   14.7870</td> <td>    0.728</td> <td>   20.323</td> <td> 0.000</td> <td>   13.354</td> <td>   16.220</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>C(Type, Treatment(reference=\"no-event\"))[T.hockey]</th> <td>   15.0207</td> <td>    2.283</td> <td>    6.579</td> <td> 0.000</td> <td>   10.524</td> <td>   19.517</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>49.689</td> <th>  Durbin-Watson:     </th> <td>   0.760</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.000</td> <th>  Jarque-Bera (JB):  </th> <td>  75.575</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 1.144</td> <th>  Prob(JB):          </th> <td>3.88e-17</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 4.359</td> <th>  Cond. No.          </th> <td>    3.35</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                  Count   R-squared:                       0.146\n",
       "Model:                            OLS   Adj. R-squared:                  0.142\n",
       "Method:                 Least Squares   F-statistic:                     43.28\n",
       "Date:                Wed, 06 Dec 2017   Prob (F-statistic):           2.69e-10\n",
       "Time:                        21:05:56   Log-Likelihood:                -976.91\n",
       "No. Observations:                 256   AIC:                             1958.\n",
       "Df Residuals:                     254   BIC:                             1965.\n",
       "Df Model:                           1                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "======================================================================================================================\n",
       "                                                         coef    std err          t      P>|t|      [0.025      0.975]\n",
       "----------------------------------------------------------------------------------------------------------------------\n",
       "Intercept                                             14.7870      0.728     20.323      0.000      13.354      16.220\n",
       "C(Type, Treatment(reference=\"no-event\"))[T.hockey]    15.0207      2.283      6.579      0.000      10.524      19.517\n",
       "==============================================================================\n",
       "Omnibus:                       49.689   Durbin-Watson:                   0.760\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):               75.575\n",
       "Skew:                           1.144   Prob(JB):                     3.88e-17\n",
       "Kurtosis:                       4.359   Cond. No.                         3.35\n",
       "==============================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lm.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "event = pd.read_csv('events_2016_subset.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   Unnamed: 0  Unnamed: 0.1           EventID  Event_type  \\\n",
       "0           1           168  1490000000000000  basketball   \n",
       "1           2           167   201000000000000  basketball   \n",
       "2           3           166  1080000000000000  basketball   \n",
       "3           4           165  1390000000000000  basketball   \n",
       "4           5           164  1230000000000000  basketball   \n",
       "\n",
       "                                  Name           Start_Time  Start_Hour  \\\n",
       "0                 Harlem Globetrotters  2016-01-02 19:00:00          19   \n",
       "1     Brooklyn Nets vs. Boston Celtics  2016-01-04 19:30:00          19   \n",
       "2    Brooklyn Nets vs. Toronto Raptors  2016-01-06 19:30:00          19   \n",
       "3      Brooklyn Nets vs. Orlando Magic  2016-01-08 19:30:00          19   \n",
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       "\n",
       "              End_Time  End_Hour  weekday        date  \n",
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     "execution_count": 39,
     "metadata": {},
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   ],
   "source": [
    "event.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "event['date'] = pd.to_datetime(event['Start_Time']).dt.date.astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
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       "    Unnamed: 0  Unnamed: 0.1           EventID Event_type  \\\n",
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