PandasTime Series.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2017, 4, 26, 8, 17, 8, 139190)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datetime.now()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2015, 7, 4, 0, 0)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datetime(year=2015, month=7, day=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Convert string into datetime object\n",
    "from dateutil import parser\n",
    "date = parser.parse(\"5th of November,2017\")\n",
    "date1 = parser.parse(\"5th of November,2017\")\n",
    "date2 = parser.parse(\"7th of November,2017\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.timedelta(2)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date\n",
    "date2 - date1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Sunday'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finding weekday information\n",
    "date.strftime('%A')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2017'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date.strftime('%Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'11'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date.strftime('%m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "date = np.array('2015-07-24',dtype=np.datetime64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(datetime.date(2015, 7, 24), dtype='datetime64[D]')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2015-07-24', '2015-07-25', '2015-07-26', '2015-07-27',\n",
       "       '2015-07-28', '2015-07-29', '2015-07-30', '2015-07-31',\n",
       "       '2015-08-01', '2015-08-02'], dtype='datetime64[D]')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = date + np.arange(10)\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "s = d[5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2015-07-29'"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Code\n",
    "Meaning\n",
    "Y\n",
    "Year\n",
    "\n",
    "M\n",
    "Month\n",
    "\n",
    "W\n",
    "Week\n",
    "\n",
    "D\n",
    "Day\n",
    "\n",
    "h\n",
    "Hour\n",
    "\n",
    "m\n",
    "Minute\n",
    "\n",
    "s\n",
    "Second\n",
    "\n",
    "ms\n",
    "Millisecond\n",
    "\n",
    "us\n",
    "Microsecond\n",
    "\n",
    "ns\n",
    "Nanosecond\n",
    "\n",
    "ps\n",
    "Picosecond\n",
    "\n",
    "fs\n",
    "Femtosecond\n",
    "\n",
    "as\n",
    "Attosecond"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas - Date & Times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Convert string into timestamp object\n",
    "date = pd.to_datetime(\"5th of July 2019\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2019-07-05 00:00:00')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2019-07-05 00:00:00', '2019-08-04 10:29:06',\n",
       "               '2019-09-03 20:58:12', '2019-10-04 07:27:18',\n",
       "               '2019-11-03 17:56:24', '2019-12-04 04:25:30',\n",
       "               '2020-01-03 14:54:36', '2020-02-03 01:23:42',\n",
       "               '2020-03-04 11:52:48', '2020-04-03 22:21:54',\n",
       "               '2020-05-04 08:51:00', '2020-06-03 19:20:06'],\n",
       "              dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date + pd.to_timedelta(np.arange(12),'M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TimedeltaIndex([  '0 days 00:00:00',  '30 days 10:29:06',  '60 days 20:58:12',\n",
       "                 '91 days 07:27:18', '121 days 17:56:24', '152 days 04:25:30',\n",
       "                '182 days 14:54:36', '213 days 01:23:42', '243 days 11:52:48',\n",
       "                '273 days 22:21:54', '304 days 08:51:00', '334 days 19:20:06'],\n",
       "               dtype='timedelta64[ns]', freq=None)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_timedelta(np.arange(12),'M')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas Time Series : Indexing by Time\n",
    "* The purpose here is to use datetime as index column and not a regular column\n",
    "* Before using datetime as index, convert date column as index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "index = pd.DatetimeIndex(['2017-07-04','2017-08-4','2017-09-04','2017-10-04'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(datetime.date(2015, 7, 24), dtype='datetime64[D]')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.Series([0,1,2,3], index=index)\n",
    "date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017-07-04    0\n",
       "2017-08-04    1\n",
       "2017-09-04    2\n",
       "2017-10-04    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017-07-04    0\n",
       "2017-08-04    1\n",
       "2017-09-04    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['2017-07-04 ':'2017-09-04']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "index = pd.DatetimeIndex(['2017-07-04','2018-08-4','2017-09-04','2018-10-04'])\n",
    "data = pd.Series([0,1,2,3], index=index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017-07-04    0\n",
       "2017-09-04    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['2017']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-02-26', '2017-02-27', '2017-02-28', '2017-03-01',\n",
       "               '2017-03-02'],\n",
       "              dtype='datetime64[ns]', freq='D')"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range('2017-02-26', '2017-03-02')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-12-31', '2018-12-31', '2019-12-31', '2020-12-31',\n",
       "               '2021-12-31', '2022-12-31', '2023-12-31', '2024-12-31',\n",
       "               '2025-12-31', '2026-12-31'],\n",
       "              dtype='datetime64[ns]', freq='A-DEC')"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range('2017',periods=10,freq='A')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PeriodIndex(['2018-05', '2018-06', '2018-07', '2018-08', '2018-09', '2018-10',\n",
       "             '2018-11', '2018-12'],\n",
       "            dtype='period[M]', freq='M')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.period_range('2018-05',periods=8, freq='M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TimedeltaIndex(['00:00:00', '01:00:00', '02:00:00', '03:00:00', '04:00:00',\n",
       "                '05:00:00', '06:00:00', '07:00:00', '08:00:00', '09:00:00'],\n",
       "               dtype='timedelta64[ns]', freq='H')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.timedelta_range(0, periods=10, freq='H')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "date = pd.to_datetime(\"5th of July 2019\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-12-31', '2022-12-31', '2027-12-31', '2032-12-31',\n",
       "               '2037-12-31', '2042-12-31', '2047-12-31', '2052-12-31',\n",
       "               '2057-12-31', '2062-12-31'],\n",
       "              dtype='datetime64[ns]', freq='5A-DEC')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range('2017-07-03',periods=10,freq='5A')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TimedeltaIndex(['00:00:00', '02:30:00', '05:00:00', '07:30:00', '10:00:00',\n",
       "                '12:30:00', '15:00:00', '17:30:00', '20:00:00'],\n",
       "               dtype='timedelta64[ns]', freq='150T')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.timedelta_range(0,periods=9, freq=\"2H30T\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Code\n",
    "Description\n",
    "Code\n",
    "Description\n",
    "D\n",
    "Calendar day\n",
    "B\n",
    "Business day\n",
    "W\n",
    "Weekly\n",
    "\n",
    "\n",
    "M\n",
    "Month end\n",
    "BM\n",
    "Business month end\n",
    "Q\n",
    "Quarter end\n",
    "BQ\n",
    "Business quarter end\n",
    "A\n",
    "Year end\n",
    "BA\n",
    "Business year end\n",
    "H\n",
    "Hours\n",
    "BH\n",
    "Business hours\n",
    "T\n",
    "Minutes\n",
    "\n",
    "\n",
    "S\n",
    "Seconds\n",
    "\n",
    "\n",
    "L\n",
    "Milliseonds\n",
    "\n",
    "\n",
    "U\n",
    "Microseconds\n",
    "\n",
    "\n",
    "N\n",
    "nanoseconds\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#It will not be present by default, needs seperate installation\n",
    "from pandas_datareader import data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Returns a pandas object\n",
    "goog = data.DataReader('GOOG', start='2004', end='2016',\n",
    "                       data_source='google')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2004-08-19</th>\n",
       "      <td>49.96</td>\n",
       "      <td>51.98</td>\n",
       "      <td>47.93</td>\n",
       "      <td>50.12</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-08-20</th>\n",
       "      <td>50.69</td>\n",
       "      <td>54.49</td>\n",
       "      <td>50.20</td>\n",
       "      <td>54.10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-08-23</th>\n",
       "      <td>55.32</td>\n",
       "      <td>56.68</td>\n",
       "      <td>54.47</td>\n",
       "      <td>54.65</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-08-24</th>\n",
       "      <td>55.56</td>\n",
       "      <td>55.74</td>\n",
       "      <td>51.73</td>\n",
       "      <td>52.38</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-08-25</th>\n",
       "      <td>52.43</td>\n",
       "      <td>53.95</td>\n",
       "      <td>51.89</td>\n",
       "      <td>52.95</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-08-26</th>\n",
       "      <td>52.42</td>\n",
       "      <td>53.92</td>\n",
       "      <td>52.28</td>\n",
       "      <td>53.90</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-08-27</th>\n",
       "      <td>54.00</td>\n",
       "      <td>54.26</td>\n",
       "      <td>52.79</td>\n",
       "      <td>53.02</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-08-30</th>\n",
       "      <td>52.69</td>\n",
       "      <td>52.69</td>\n",
       "      <td>50.95</td>\n",
       "      <td>50.95</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-08-31</th>\n",
       "      <td>51.11</td>\n",
       "      <td>51.80</td>\n",
       "      <td>51.03</td>\n",
       "      <td>51.13</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-01</th>\n",
       "      <td>51.30</td>\n",
       "      <td>51.43</td>\n",
       "      <td>49.79</td>\n",
       "      <td>50.07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-02</th>\n",
       "      <td>49.50</td>\n",
       "      <td>51.13</td>\n",
       "      <td>49.42</td>\n",
       "      <td>50.70</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-03</th>\n",
       "      <td>50.42</td>\n",
       "      <td>50.82</td>\n",
       "      <td>49.61</td>\n",
       "      <td>49.95</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-07</th>\n",
       "      <td>50.45</td>\n",
       "      <td>50.95</td>\n",
       "      <td>49.76</td>\n",
       "      <td>50.74</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-08</th>\n",
       "      <td>50.32</td>\n",
       "      <td>51.46</td>\n",
       "      <td>50.20</td>\n",
       "      <td>51.10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-09</th>\n",
       "      <td>51.20</td>\n",
       "      <td>51.30</td>\n",
       "      <td>50.45</td>\n",
       "      <td>51.10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-10</th>\n",
       "      <td>50.75</td>\n",
       "      <td>53.23</td>\n",
       "      <td>50.60</td>\n",
       "      <td>52.61</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-13</th>\n",
       "      <td>53.26</td>\n",
       "      <td>54.15</td>\n",
       "      <td>53.18</td>\n",
       "      <td>53.70</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-14</th>\n",
       "      <td>53.67</td>\n",
       "      <td>55.94</td>\n",
       "      <td>53.34</td>\n",
       "      <td>55.69</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-15</th>\n",
       "      <td>55.22</td>\n",
       "      <td>57.06</td>\n",
       "      <td>55.04</td>\n",
       "      <td>55.94</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-16</th>\n",
       "      <td>56.11</td>\n",
       "      <td>57.84</td>\n",
       "      <td>55.77</td>\n",
       "      <td>56.93</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-17</th>\n",
       "      <td>57.15</td>\n",
       "      <td>58.69</td>\n",
       "      <td>56.72</td>\n",
       "      <td>58.69</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-20</th>\n",
       "      <td>58.42</td>\n",
       "      <td>60.74</td>\n",
       "      <td>58.33</td>\n",
       "      <td>59.62</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-21</th>\n",
       "      <td>60.04</td>\n",
       "      <td>60.15</td>\n",
       "      <td>58.70</td>\n",
       "      <td>58.86</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-22</th>\n",
       "      <td>58.67</td>\n",
       "      <td>59.78</td>\n",
       "      <td>58.35</td>\n",
       "      <td>59.13</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-23</th>\n",
       "      <td>59.36</td>\n",
       "      <td>61.25</td>\n",
       "      <td>58.45</td>\n",
       "      <td>60.35</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-24</th>\n",
       "      <td>60.42</td>\n",
       "      <td>61.99</td>\n",
       "      <td>59.82</td>\n",
       "      <td>59.86</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-27</th>\n",
       "      <td>59.72</td>\n",
       "      <td>60.38</td>\n",
       "      <td>58.84</td>\n",
       "      <td>59.07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-28</th>\n",
       "      <td>60.51</td>\n",
       "      <td>63.64</td>\n",
       "      <td>60.04</td>\n",
       "      <td>63.37</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-29</th>\n",
       "      <td>63.20</td>\n",
       "      <td>67.44</td>\n",
       "      <td>63.05</td>\n",
       "      <td>65.47</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-30</th>\n",
       "      <td>64.88</td>\n",
       "      <td>66.08</td>\n",
       "      <td>64.44</td>\n",
       "      <td>64.74</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-18</th>\n",
       "      <td>727.58</td>\n",
       "      <td>741.41</td>\n",
       "      <td>727.00</td>\n",
       "      <td>740.00</td>\n",
       "      <td>1671588.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-19</th>\n",
       "      <td>738.74</td>\n",
       "      <td>742.00</td>\n",
       "      <td>737.43</td>\n",
       "      <td>738.41</td>\n",
       "      <td>1327109.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-20</th>\n",
       "      <td>746.53</td>\n",
       "      <td>757.92</td>\n",
       "      <td>743.00</td>\n",
       "      <td>756.60</td>\n",
       "      <td>2212302.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-23</th>\n",
       "      <td>757.45</td>\n",
       "      <td>762.71</td>\n",
       "      <td>751.82</td>\n",
       "      <td>755.98</td>\n",
       "      <td>1414487.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-24</th>\n",
       "      <td>752.00</td>\n",
       "      <td>755.28</td>\n",
       "      <td>737.63</td>\n",
       "      <td>748.28</td>\n",
       "      <td>2333130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-25</th>\n",
       "      <td>748.14</td>\n",
       "      <td>752.00</td>\n",
       "      <td>746.06</td>\n",
       "      <td>748.15</td>\n",
       "      <td>1122224.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-27</th>\n",
       "      <td>748.46</td>\n",
       "      <td>753.41</td>\n",
       "      <td>747.49</td>\n",
       "      <td>750.26</td>\n",
       "      <td>838518.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-30</th>\n",
       "      <td>748.81</td>\n",
       "      <td>754.93</td>\n",
       "      <td>741.27</td>\n",
       "      <td>742.60</td>\n",
       "      <td>2035261.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-01</th>\n",
       "      <td>747.11</td>\n",
       "      <td>768.95</td>\n",
       "      <td>746.70</td>\n",
       "      <td>767.04</td>\n",
       "      <td>2129940.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-02</th>\n",
       "      <td>768.90</td>\n",
       "      <td>775.96</td>\n",
       "      <td>758.96</td>\n",
       "      <td>762.38</td>\n",
       "      <td>2195686.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-03</th>\n",
       "      <td>766.01</td>\n",
       "      <td>769.00</td>\n",
       "      <td>745.63</td>\n",
       "      <td>752.54</td>\n",
       "      <td>2590641.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-04</th>\n",
       "      <td>753.10</td>\n",
       "      <td>768.49</td>\n",
       "      <td>750.00</td>\n",
       "      <td>766.81</td>\n",
       "      <td>2757283.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-07</th>\n",
       "      <td>767.77</td>\n",
       "      <td>768.73</td>\n",
       "      <td>755.09</td>\n",
       "      <td>763.25</td>\n",
       "      <td>1812314.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-08</th>\n",
       "      <td>757.89</td>\n",
       "      <td>764.80</td>\n",
       "      <td>754.20</td>\n",
       "      <td>762.37</td>\n",
       "      <td>1829475.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-09</th>\n",
       "      <td>759.17</td>\n",
       "      <td>764.23</td>\n",
       "      <td>737.00</td>\n",
       "      <td>751.61</td>\n",
       "      <td>2699990.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-10</th>\n",
       "      <td>752.85</td>\n",
       "      <td>755.85</td>\n",
       "      <td>743.83</td>\n",
       "      <td>749.46</td>\n",
       "      <td>1988380.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-11</th>\n",
       "      <td>741.16</td>\n",
       "      <td>745.71</td>\n",
       "      <td>736.75</td>\n",
       "      <td>738.87</td>\n",
       "      <td>2224410.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-14</th>\n",
       "      <td>741.79</td>\n",
       "      <td>748.73</td>\n",
       "      <td>724.17</td>\n",
       "      <td>747.77</td>\n",
       "      <td>2412497.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-15</th>\n",
       "      <td>753.00</td>\n",
       "      <td>758.08</td>\n",
       "      <td>743.01</td>\n",
       "      <td>743.40</td>\n",
       "      <td>2666229.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-16</th>\n",
       "      <td>750.00</td>\n",
       "      <td>760.59</td>\n",
       "      <td>739.44</td>\n",
       "      <td>758.09</td>\n",
       "      <td>1993251.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-17</th>\n",
       "      <td>762.42</td>\n",
       "      <td>762.68</td>\n",
       "      <td>749.00</td>\n",
       "      <td>749.43</td>\n",
       "      <td>1553418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-18</th>\n",
       "      <td>746.51</td>\n",
       "      <td>754.13</td>\n",
       "      <td>738.15</td>\n",
       "      <td>739.31</td>\n",
       "      <td>3148743.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-21</th>\n",
       "      <td>746.13</td>\n",
       "      <td>750.00</td>\n",
       "      <td>740.00</td>\n",
       "      <td>747.77</td>\n",
       "      <td>1525703.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-22</th>\n",
       "      <td>751.65</td>\n",
       "      <td>754.85</td>\n",
       "      <td>745.53</td>\n",
       "      <td>750.00</td>\n",
       "      <td>1365520.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-23</th>\n",
       "      <td>753.47</td>\n",
       "      <td>754.21</td>\n",
       "      <td>744.00</td>\n",
       "      <td>750.31</td>\n",
       "      <td>1566726.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-24</th>\n",
       "      <td>749.55</td>\n",
       "      <td>751.35</td>\n",
       "      <td>746.62</td>\n",
       "      <td>748.40</td>\n",
       "      <td>527223.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-28</th>\n",
       "      <td>752.92</td>\n",
       "      <td>762.99</td>\n",
       "      <td>749.52</td>\n",
       "      <td>762.51</td>\n",
       "      <td>1515716.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-29</th>\n",
       "      <td>766.69</td>\n",
       "      <td>779.98</td>\n",
       "      <td>766.43</td>\n",
       "      <td>776.60</td>\n",
       "      <td>1765012.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-30</th>\n",
       "      <td>776.60</td>\n",
       "      <td>777.60</td>\n",
       "      <td>766.90</td>\n",
       "      <td>771.00</td>\n",
       "      <td>1293521.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>769.50</td>\n",
       "      <td>769.50</td>\n",
       "      <td>758.34</td>\n",
       "      <td>758.88</td>\n",
       "      <td>1500923.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2862 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Open    High     Low   Close     Volume\n",
       "Date                                                 \n",
       "2004-08-19   49.96   51.98   47.93   50.12        NaN\n",
       "2004-08-20   50.69   54.49   50.20   54.10        NaN\n",
       "2004-08-23   55.32   56.68   54.47   54.65        NaN\n",
       "2004-08-24   55.56   55.74   51.73   52.38        NaN\n",
       "2004-08-25   52.43   53.95   51.89   52.95        NaN\n",
       "2004-08-26   52.42   53.92   52.28   53.90        NaN\n",
       "2004-08-27   54.00   54.26   52.79   53.02        NaN\n",
       "2004-08-30   52.69   52.69   50.95   50.95        NaN\n",
       "2004-08-31   51.11   51.80   51.03   51.13        NaN\n",
       "2004-09-01   51.30   51.43   49.79   50.07        NaN\n",
       "2004-09-02   49.50   51.13   49.42   50.70        NaN\n",
       "2004-09-03   50.42   50.82   49.61   49.95        NaN\n",
       "2004-09-07   50.45   50.95   49.76   50.74        NaN\n",
       "2004-09-08   50.32   51.46   50.20   51.10        NaN\n",
       "2004-09-09   51.20   51.30   50.45   51.10        NaN\n",
       "2004-09-10   50.75   53.23   50.60   52.61        NaN\n",
       "2004-09-13   53.26   54.15   53.18   53.70        NaN\n",
       "2004-09-14   53.67   55.94   53.34   55.69        NaN\n",
       "2004-09-15   55.22   57.06   55.04   55.94        NaN\n",
       "2004-09-16   56.11   57.84   55.77   56.93        NaN\n",
       "2004-09-17   57.15   58.69   56.72   58.69        NaN\n",
       "2004-09-20   58.42   60.74   58.33   59.62        NaN\n",
       "2004-09-21   60.04   60.15   58.70   58.86        NaN\n",
       "2004-09-22   58.67   59.78   58.35   59.13        NaN\n",
       "2004-09-23   59.36   61.25   58.45   60.35        NaN\n",
       "2004-09-24   60.42   61.99   59.82   59.86        NaN\n",
       "2004-09-27   59.72   60.38   58.84   59.07        NaN\n",
       "2004-09-28   60.51   63.64   60.04   63.37        NaN\n",
       "2004-09-29   63.20   67.44   63.05   65.47        NaN\n",
       "2004-09-30   64.88   66.08   64.44   64.74        NaN\n",
       "...            ...     ...     ...     ...        ...\n",
       "2015-11-18  727.58  741.41  727.00  740.00  1671588.0\n",
       "2015-11-19  738.74  742.00  737.43  738.41  1327109.0\n",
       "2015-11-20  746.53  757.92  743.00  756.60  2212302.0\n",
       "2015-11-23  757.45  762.71  751.82  755.98  1414487.0\n",
       "2015-11-24  752.00  755.28  737.63  748.28  2333130.0\n",
       "2015-11-25  748.14  752.00  746.06  748.15  1122224.0\n",
       "2015-11-27  748.46  753.41  747.49  750.26   838518.0\n",
       "2015-11-30  748.81  754.93  741.27  742.60  2035261.0\n",
       "2015-12-01  747.11  768.95  746.70  767.04  2129940.0\n",
       "2015-12-02  768.90  775.96  758.96  762.38  2195686.0\n",
       "2015-12-03  766.01  769.00  745.63  752.54  2590641.0\n",
       "2015-12-04  753.10  768.49  750.00  766.81  2757283.0\n",
       "2015-12-07  767.77  768.73  755.09  763.25  1812314.0\n",
       "2015-12-08  757.89  764.80  754.20  762.37  1829475.0\n",
       "2015-12-09  759.17  764.23  737.00  751.61  2699990.0\n",
       "2015-12-10  752.85  755.85  743.83  749.46  1988380.0\n",
       "2015-12-11  741.16  745.71  736.75  738.87  2224410.0\n",
       "2015-12-14  741.79  748.73  724.17  747.77  2412497.0\n",
       "2015-12-15  753.00  758.08  743.01  743.40  2666229.0\n",
       "2015-12-16  750.00  760.59  739.44  758.09  1993251.0\n",
       "2015-12-17  762.42  762.68  749.00  749.43  1553418.0\n",
       "2015-12-18  746.51  754.13  738.15  739.31  3148743.0\n",
       "2015-12-21  746.13  750.00  740.00  747.77  1525703.0\n",
       "2015-12-22  751.65  754.85  745.53  750.00  1365520.0\n",
       "2015-12-23  753.47  754.21  744.00  750.31  1566726.0\n",
       "2015-12-24  749.55  751.35  746.62  748.40   527223.0\n",
       "2015-12-28  752.92  762.99  749.52  762.51  1515716.0\n",
       "2015-12-29  766.69  779.98  766.43  776.60  1765012.0\n",
       "2015-12-30  776.60  777.60  766.90  771.00  1293521.0\n",
       "2015-12-31  769.50  769.50  758.34  758.88  1500923.0\n",
       "\n",
       "[2862 rows x 5 columns]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "goog\n",
    "# Date coming storage in the form of Index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
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       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-12-28</th>\n",
       "      <td>752.92</td>\n",
       "      <td>762.99</td>\n",
       "      <td>749.52</td>\n",
       "      <td>762.51</td>\n",
       "      <td>1515716.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-29</th>\n",
       "      <td>766.69</td>\n",
       "      <td>779.98</td>\n",
       "      <td>766.43</td>\n",
       "      <td>776.60</td>\n",
       "      <td>1765012.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-30</th>\n",
       "      <td>776.60</td>\n",
       "      <td>777.60</td>\n",
       "      <td>766.90</td>\n",
       "      <td>771.00</td>\n",
       "      <td>1293521.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>769.50</td>\n",
       "      <td>769.50</td>\n",
       "      <td>758.34</td>\n",
       "      <td>758.88</td>\n",
       "      <td>1500923.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Open    High     Low   Close     Volume\n",
       "Date                                                 \n",
       "2015-12-28  752.92  762.99  749.52  762.51  1515716.0\n",
       "2015-12-29  766.69  779.98  766.43  776.60  1765012.0\n",
       "2015-12-30  776.60  777.60  766.90  771.00  1293521.0\n",
       "2015-12-31  769.50  769.50  758.34  758.88  1500923.0"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "goog['2015-12-28':'2015-12-31']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
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       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2004-09-23</th>\n",
       "      <td>59.36</td>\n",
       "      <td>61.25</td>\n",
       "      <td>58.45</td>\n",
       "      <td>60.35</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-24</th>\n",
       "      <td>60.42</td>\n",
       "      <td>61.99</td>\n",
       "      <td>59.82</td>\n",
       "      <td>59.86</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-27</th>\n",
       "      <td>59.72</td>\n",
       "      <td>60.38</td>\n",
       "      <td>58.84</td>\n",
       "      <td>59.07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-28</th>\n",
       "      <td>60.51</td>\n",
       "      <td>63.64</td>\n",
       "      <td>60.04</td>\n",
       "      <td>63.37</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open   High    Low  Close  Volume\n",
       "Date                                          \n",
       "2004-09-23  59.36  61.25  58.45  60.35     NaN\n",
       "2004-09-24  60.42  61.99  59.82  59.86     NaN\n",
       "2004-09-27  59.72  60.38  58.84  59.07     NaN\n",
       "2004-09-28  60.51  63.64  60.04  63.37     NaN"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "goog['2004-09-23':'2004-09-28']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
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       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
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       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-03</th>\n",
       "      <td>98.60</td>\n",
       "      <td>101.72</td>\n",
       "      <td>97.63</td>\n",
       "      <td>101.25</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>100.56</td>\n",
       "      <td>101.36</td>\n",
       "      <td>96.64</td>\n",
       "      <td>97.15</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>96.63</td>\n",
       "      <td>98.35</td>\n",
       "      <td>96.02</td>\n",
       "      <td>96.66</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>97.53</td>\n",
       "      <td>97.85</td>\n",
       "      <td>93.77</td>\n",
       "      <td>94.18</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>95.22</td>\n",
       "      <td>97.03</td>\n",
       "      <td>94.30</td>\n",
       "      <td>96.83</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-10</th>\n",
       "      <td>97.15</td>\n",
       "      <td>98.95</td>\n",
       "      <td>95.82</td>\n",
       "      <td>97.43</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-11</th>\n",
       "      <td>97.71</td>\n",
       "      <td>98.76</td>\n",
       "      <td>96.49</td>\n",
       "      <td>96.67</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-12</th>\n",
       "      <td>97.07</td>\n",
       "      <td>97.87</td>\n",
       "      <td>95.15</td>\n",
       "      <td>97.59</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-13</th>\n",
       "      <td>97.59</td>\n",
       "      <td>98.60</td>\n",
       "      <td>96.93</td>\n",
       "      <td>97.57</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-14</th>\n",
       "      <td>97.90</td>\n",
       "      <td>99.90</td>\n",
       "      <td>96.97</td>\n",
       "      <td>99.89</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-18</th>\n",
       "      <td>100.34</td>\n",
       "      <td>102.41</td>\n",
       "      <td>99.23</td>\n",
       "      <td>101.85</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-19</th>\n",
       "      <td>102.22</td>\n",
       "      <td>102.55</td>\n",
       "      <td>98.26</td>\n",
       "      <td>98.55</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-20</th>\n",
       "      <td>96.19</td>\n",
       "      <td>98.03</td>\n",
       "      <td>95.90</td>\n",
       "      <td>96.86</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-21</th>\n",
       "      <td>97.12</td>\n",
       "      <td>97.58</td>\n",
       "      <td>93.97</td>\n",
       "      <td>94.05</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-24</th>\n",
       "      <td>94.25</td>\n",
       "      <td>94.57</td>\n",
       "      <td>90.07</td>\n",
       "      <td>90.27</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-25</th>\n",
       "      <td>91.01</td>\n",
       "      <td>91.03</td>\n",
       "      <td>88.06</td>\n",
       "      <td>88.47</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-26</th>\n",
       "      <td>89.55</td>\n",
       "      <td>94.61</td>\n",
       "      <td>89.49</td>\n",
       "      <td>94.53</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-27</th>\n",
       "      <td>94.29</td>\n",
       "      <td>94.34</td>\n",
       "      <td>92.51</td>\n",
       "      <td>93.95</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-28</th>\n",
       "      <td>94.91</td>\n",
       "      <td>97.25</td>\n",
       "      <td>93.08</td>\n",
       "      <td>95.07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-31</th>\n",
       "      <td>96.75</td>\n",
       "      <td>98.08</td>\n",
       "      <td>95.76</td>\n",
       "      <td>97.71</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-01</th>\n",
       "      <td>97.09</td>\n",
       "      <td>101.77</td>\n",
       "      <td>95.22</td>\n",
       "      <td>95.85</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-02</th>\n",
       "      <td>107.67</td>\n",
       "      <td>108.29</td>\n",
       "      <td>101.73</td>\n",
       "      <td>102.88</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-03</th>\n",
       "      <td>102.89</td>\n",
       "      <td>106.58</td>\n",
       "      <td>102.80</td>\n",
       "      <td>105.32</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-04</th>\n",
       "      <td>103.13</td>\n",
       "      <td>103.77</td>\n",
       "      <td>101.20</td>\n",
       "      <td>102.08</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-07</th>\n",
       "      <td>102.53</td>\n",
       "      <td>103.10</td>\n",
       "      <td>97.66</td>\n",
       "      <td>97.92</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-08</th>\n",
       "      <td>98.38</td>\n",
       "      <td>99.91</td>\n",
       "      <td>97.17</td>\n",
       "      <td>99.22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-09</th>\n",
       "      <td>100.28</td>\n",
       "      <td>100.70</td>\n",
       "      <td>94.64</td>\n",
       "      <td>95.69</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-10</th>\n",
       "      <td>95.89</td>\n",
       "      <td>96.01</td>\n",
       "      <td>92.53</td>\n",
       "      <td>93.90</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-11</th>\n",
       "      <td>93.24</td>\n",
       "      <td>96.06</td>\n",
       "      <td>92.94</td>\n",
       "      <td>93.61</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-14</th>\n",
       "      <td>91.33</td>\n",
       "      <td>96.44</td>\n",
       "      <td>90.41</td>\n",
       "      <td>96.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-11-17</th>\n",
       "      <td>200.70</td>\n",
       "      <td>201.70</td>\n",
       "      <td>199.57</td>\n",
       "      <td>201.52</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-11-18</th>\n",
       "      <td>201.54</td>\n",
       "      <td>202.05</td>\n",
       "      <td>199.73</td>\n",
       "      <td>199.90</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-11-21</th>\n",
       "      <td>199.39</td>\n",
       "      <td>204.79</td>\n",
       "      <td>196.55</td>\n",
       "      <td>204.48</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-11-22</th>\n",
       "      <td>204.12</td>\n",
       "      <td>208.45</td>\n",
       "      <td>202.91</td>\n",
       "      <td>208.03</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-11-23</th>\n",
       "      <td>208.31</td>\n",
       "      <td>212.15</td>\n",
       "      <td>207.68</td>\n",
       "      <td>211.22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-11-25</th>\n",
       "      <td>212.68</td>\n",
       "      <td>214.16</td>\n",
       "      <td>212.44</td>\n",
       "      <td>214.10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-11-28</th>\n",
       "      <td>214.70</td>\n",
       "      <td>215.40</td>\n",
       "      <td>211.01</td>\n",
       "      <td>211.53</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-11-29</th>\n",
       "      <td>212.02</td>\n",
       "      <td>212.99</td>\n",
       "      <td>200.87</td>\n",
       "      <td>201.57</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-11-30</th>\n",
       "      <td>201.93</td>\n",
       "      <td>204.02</td>\n",
       "      <td>197.58</td>\n",
       "      <td>202.25</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-01</th>\n",
       "      <td>204.40</td>\n",
       "      <td>207.51</td>\n",
       "      <td>203.94</td>\n",
       "      <td>206.84</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-02</th>\n",
       "      <td>208.26</td>\n",
       "      <td>209.56</td>\n",
       "      <td>206.72</td>\n",
       "      <td>208.64</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-05</th>\n",
       "      <td>208.29</td>\n",
       "      <td>208.54</td>\n",
       "      <td>201.94</td>\n",
       "      <td>202.72</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-06</th>\n",
       "      <td>204.15</td>\n",
       "      <td>208.00</td>\n",
       "      <td>200.65</td>\n",
       "      <td>202.07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-07</th>\n",
       "      <td>202.88</td>\n",
       "      <td>203.15</td>\n",
       "      <td>199.31</td>\n",
       "      <td>201.91</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-08</th>\n",
       "      <td>202.45</td>\n",
       "      <td>205.12</td>\n",
       "      <td>201.12</td>\n",
       "      <td>205.12</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-09</th>\n",
       "      <td>207.29</td>\n",
       "      <td>207.68</td>\n",
       "      <td>204.08</td>\n",
       "      <td>204.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-12</th>\n",
       "      <td>207.11</td>\n",
       "      <td>207.40</td>\n",
       "      <td>204.77</td>\n",
       "      <td>206.10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-13</th>\n",
       "      <td>206.04</td>\n",
       "      <td>208.79</td>\n",
       "      <td>205.61</td>\n",
       "      <td>208.54</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-14</th>\n",
       "      <td>208.31</td>\n",
       "      <td>209.66</td>\n",
       "      <td>207.54</td>\n",
       "      <td>209.27</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-15</th>\n",
       "      <td>209.35</td>\n",
       "      <td>211.36</td>\n",
       "      <td>208.04</td>\n",
       "      <td>211.05</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-16</th>\n",
       "      <td>212.46</td>\n",
       "      <td>216.03</td>\n",
       "      <td>211.16</td>\n",
       "      <td>214.86</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-19</th>\n",
       "      <td>215.88</td>\n",
       "      <td>222.88</td>\n",
       "      <td>209.84</td>\n",
       "      <td>212.09</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-20</th>\n",
       "      <td>213.72</td>\n",
       "      <td>215.88</td>\n",
       "      <td>212.12</td>\n",
       "      <td>214.66</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-21</th>\n",
       "      <td>216.56</td>\n",
       "      <td>218.21</td>\n",
       "      <td>210.14</td>\n",
       "      <td>212.95</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-22</th>\n",
       "      <td>215.67</td>\n",
       "      <td>216.21</td>\n",
       "      <td>212.75</td>\n",
       "      <td>215.80</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-23</th>\n",
       "      <td>215.86</td>\n",
       "      <td>216.03</td>\n",
       "      <td>214.18</td>\n",
       "      <td>215.25</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-27</th>\n",
       "      <td>215.71</td>\n",
       "      <td>215.71</td>\n",
       "      <td>211.17</td>\n",
       "      <td>212.11</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-28</th>\n",
       "      <td>211.96</td>\n",
       "      <td>213.68</td>\n",
       "      <td>210.42</td>\n",
       "      <td>213.13</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-29</th>\n",
       "      <td>213.78</td>\n",
       "      <td>214.15</td>\n",
       "      <td>209.38</td>\n",
       "      <td>209.86</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-30</th>\n",
       "      <td>208.43</td>\n",
       "      <td>208.90</td>\n",
       "      <td>206.66</td>\n",
       "      <td>207.22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Open    High     Low   Close  Volume\n",
       "Date                                              \n",
       "2005-01-03   98.60  101.72   97.63  101.25     NaN\n",
       "2005-01-04  100.56  101.36   96.64   97.15     NaN\n",
       "2005-01-05   96.63   98.35   96.02   96.66     NaN\n",
       "2005-01-06   97.53   97.85   93.77   94.18     NaN\n",
       "2005-01-07   95.22   97.03   94.30   96.83     NaN\n",
       "2005-01-10   97.15   98.95   95.82   97.43     NaN\n",
       "2005-01-11   97.71   98.76   96.49   96.67     NaN\n",
       "2005-01-12   97.07   97.87   95.15   97.59     NaN\n",
       "2005-01-13   97.59   98.60   96.93   97.57     NaN\n",
       "2005-01-14   97.90   99.90   96.97   99.89     NaN\n",
       "2005-01-18  100.34  102.41   99.23  101.85     NaN\n",
       "2005-01-19  102.22  102.55   98.26   98.55     NaN\n",
       "2005-01-20   96.19   98.03   95.90   96.86     NaN\n",
       "2005-01-21   97.12   97.58   93.97   94.05     NaN\n",
       "2005-01-24   94.25   94.57   90.07   90.27     NaN\n",
       "2005-01-25   91.01   91.03   88.06   88.47     NaN\n",
       "2005-01-26   89.55   94.61   89.49   94.53     NaN\n",
       "2005-01-27   94.29   94.34   92.51   93.95     NaN\n",
       "2005-01-28   94.91   97.25   93.08   95.07     NaN\n",
       "2005-01-31   96.75   98.08   95.76   97.71     NaN\n",
       "2005-02-01   97.09  101.77   95.22   95.85     NaN\n",
       "2005-02-02  107.67  108.29  101.73  102.88     NaN\n",
       "2005-02-03  102.89  106.58  102.80  105.32     NaN\n",
       "2005-02-04  103.13  103.77  101.20  102.08     NaN\n",
       "2005-02-07  102.53  103.10   97.66   97.92     NaN\n",
       "2005-02-08   98.38   99.91   97.17   99.22     NaN\n",
       "2005-02-09  100.28  100.70   94.64   95.69     NaN\n",
       "2005-02-10   95.89   96.01   92.53   93.90     NaN\n",
       "2005-02-11   93.24   96.06   92.94   93.61     NaN\n",
       "2005-02-14   91.33   96.44   90.41   96.40     NaN\n",
       "...            ...     ...     ...     ...     ...\n",
       "2005-11-17  200.70  201.70  199.57  201.52     NaN\n",
       "2005-11-18  201.54  202.05  199.73  199.90     NaN\n",
       "2005-11-21  199.39  204.79  196.55  204.48     NaN\n",
       "2005-11-22  204.12  208.45  202.91  208.03     NaN\n",
       "2005-11-23  208.31  212.15  207.68  211.22     NaN\n",
       "2005-11-25  212.68  214.16  212.44  214.10     NaN\n",
       "2005-11-28  214.70  215.40  211.01  211.53     NaN\n",
       "2005-11-29  212.02  212.99  200.87  201.57     NaN\n",
       "2005-11-30  201.93  204.02  197.58  202.25     NaN\n",
       "2005-12-01  204.40  207.51  203.94  206.84     NaN\n",
       "2005-12-02  208.26  209.56  206.72  208.64     NaN\n",
       "2005-12-05  208.29  208.54  201.94  202.72     NaN\n",
       "2005-12-06  204.15  208.00  200.65  202.07     NaN\n",
       "2005-12-07  202.88  203.15  199.31  201.91     NaN\n",
       "2005-12-08  202.45  205.12  201.12  205.12     NaN\n",
       "2005-12-09  207.29  207.68  204.08  204.40     NaN\n",
       "2005-12-12  207.11  207.40  204.77  206.10     NaN\n",
       "2005-12-13  206.04  208.79  205.61  208.54     NaN\n",
       "2005-12-14  208.31  209.66  207.54  209.27     NaN\n",
       "2005-12-15  209.35  211.36  208.04  211.05     NaN\n",
       "2005-12-16  212.46  216.03  211.16  214.86     NaN\n",
       "2005-12-19  215.88  222.88  209.84  212.09     NaN\n",
       "2005-12-20  213.72  215.88  212.12  214.66     NaN\n",
       "2005-12-21  216.56  218.21  210.14  212.95     NaN\n",
       "2005-12-22  215.67  216.21  212.75  215.80     NaN\n",
       "2005-12-23  215.86  216.03  214.18  215.25     NaN\n",
       "2005-12-27  215.71  215.71  211.17  212.11     NaN\n",
       "2005-12-28  211.96  213.68  210.42  213.13     NaN\n",
       "2005-12-29  213.78  214.15  209.38  209.86     NaN\n",
       "2005-12-30  208.43  208.90  206.66  207.22     NaN\n",
       "\n",
       "[252 rows x 5 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "goog['2005']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('https://data.seattle.gov/api/views/65db-xm6k/rows.csv?accessType=DOWNLOAD',index_col='Date',parse_dates=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Fremont Bridge West Sidewalk</th>\n",
       "      <th>Fremont Bridge East Sidewalk</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-10-03 00:00:00</th>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 01:00:00</th>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 02:00:00</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 03:00:00</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 04:00:00</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 05:00:00</th>\n",
       "      <td>21.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 06:00:00</th>\n",
       "      <td>105.0</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 07:00:00</th>\n",
       "      <td>257.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 08:00:00</th>\n",
       "      <td>291.0</td>\n",
       "      <td>146.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 09:00:00</th>\n",
       "      <td>172.0</td>\n",
       "      <td>104.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 10:00:00</th>\n",
       "      <td>72.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 11:00:00</th>\n",
       "      <td>10.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 12:00:00</th>\n",
       "      <td>35.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 13:00:00</th>\n",
       "      <td>42.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 14:00:00</th>\n",
       "      <td>77.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 15:00:00</th>\n",
       "      <td>72.0</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 16:00:00</th>\n",
       "      <td>133.0</td>\n",
       "      <td>182.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 17:00:00</th>\n",
       "      <td>192.0</td>\n",
       "      <td>391.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 18:00:00</th>\n",
       "      <td>122.0</td>\n",
       "      <td>258.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 19:00:00</th>\n",
       "      <td>59.0</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 20:00:00</th>\n",
       "      <td>29.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 21:00:00</th>\n",
       "      <td>25.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 22:00:00</th>\n",
       "      <td>24.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 23:00:00</th>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 00:00:00</th>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 01:00:00</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 02:00:00</th>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 03:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 04:00:00</th>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 05:00:00</th>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 18:00:00</th>\n",
       "      <td>104.0</td>\n",
       "      <td>213.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 19:00:00</th>\n",
       "      <td>50.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 20:00:00</th>\n",
       "      <td>25.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 21:00:00</th>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 22:00:00</th>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 23:00:00</th>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 00:00:00</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 01:00:00</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 02:00:00</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 03:00:00</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 04:00:00</th>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 05:00:00</th>\n",
       "      <td>23.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 06:00:00</th>\n",
       "      <td>57.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 07:00:00</th>\n",
       "      <td>163.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 08:00:00</th>\n",
       "      <td>250.0</td>\n",
       "      <td>162.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 09:00:00</th>\n",
       "      <td>90.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 10:00:00</th>\n",
       "      <td>52.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 11:00:00</th>\n",
       "      <td>39.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 12:00:00</th>\n",
       "      <td>37.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 13:00:00</th>\n",
       "      <td>52.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 14:00:00</th>\n",
       "      <td>45.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 15:00:00</th>\n",
       "      <td>74.0</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 16:00:00</th>\n",
       "      <td>83.0</td>\n",
       "      <td>223.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 17:00:00</th>\n",
       "      <td>145.0</td>\n",
       "      <td>333.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 18:00:00</th>\n",
       "      <td>117.0</td>\n",
       "      <td>206.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 19:00:00</th>\n",
       "      <td>50.0</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 20:00:00</th>\n",
       "      <td>26.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 21:00:00</th>\n",
       "      <td>16.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 22:00:00</th>\n",
       "      <td>12.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 23:00:00</th>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>39384 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Fremont Bridge West Sidewalk  \\\n",
       "Date                                                \n",
       "2012-10-03 00:00:00                           4.0   \n",
       "2012-10-03 01:00:00                           4.0   \n",
       "2012-10-03 02:00:00                           1.0   \n",
       "2012-10-03 03:00:00                           2.0   \n",
       "2012-10-03 04:00:00                           6.0   \n",
       "2012-10-03 05:00:00                          21.0   \n",
       "2012-10-03 06:00:00                         105.0   \n",
       "2012-10-03 07:00:00                         257.0   \n",
       "2012-10-03 08:00:00                         291.0   \n",
       "2012-10-03 09:00:00                         172.0   \n",
       "2012-10-03 10:00:00                          72.0   \n",
       "2012-10-03 11:00:00                          10.0   \n",
       "2012-10-03 12:00:00                          35.0   \n",
       "2012-10-03 13:00:00                          42.0   \n",
       "2012-10-03 14:00:00                          77.0   \n",
       "2012-10-03 15:00:00                          72.0   \n",
       "2012-10-03 16:00:00                         133.0   \n",
       "2012-10-03 17:00:00                         192.0   \n",
       "2012-10-03 18:00:00                         122.0   \n",
       "2012-10-03 19:00:00                          59.0   \n",
       "2012-10-03 20:00:00                          29.0   \n",
       "2012-10-03 21:00:00                          25.0   \n",
       "2012-10-03 22:00:00                          24.0   \n",
       "2012-10-03 23:00:00                           5.0   \n",
       "2012-10-04 00:00:00                           7.0   \n",
       "2012-10-04 01:00:00                           3.0   \n",
       "2012-10-04 02:00:00                           3.0   \n",
       "2012-10-04 03:00:00                           0.0   \n",
       "2012-10-04 04:00:00                           7.0   \n",
       "2012-10-04 05:00:00                          15.0   \n",
       "...                                           ...   \n",
       "2017-03-30 18:00:00                         104.0   \n",
       "2017-03-30 19:00:00                          50.0   \n",
       "2017-03-30 20:00:00                          25.0   \n",
       "2017-03-30 21:00:00                          15.0   \n",
       "2017-03-30 22:00:00                          10.0   \n",
       "2017-03-30 23:00:00                          11.0   \n",
       "2017-03-31 00:00:00                           2.0   \n",
       "2017-03-31 01:00:00                           2.0   \n",
       "2017-03-31 02:00:00                           1.0   \n",
       "2017-03-31 03:00:00                           1.0   \n",
       "2017-03-31 04:00:00                           3.0   \n",
       "2017-03-31 05:00:00                          23.0   \n",
       "2017-03-31 06:00:00                          57.0   \n",
       "2017-03-31 07:00:00                         163.0   \n",
       "2017-03-31 08:00:00                         250.0   \n",
       "2017-03-31 09:00:00                          90.0   \n",
       "2017-03-31 10:00:00                          52.0   \n",
       "2017-03-31 11:00:00                          39.0   \n",
       "2017-03-31 12:00:00                          37.0   \n",
       "2017-03-31 13:00:00                          52.0   \n",
       "2017-03-31 14:00:00                          45.0   \n",
       "2017-03-31 15:00:00                          74.0   \n",
       "2017-03-31 16:00:00                          83.0   \n",
       "2017-03-31 17:00:00                         145.0   \n",
       "2017-03-31 18:00:00                         117.0   \n",
       "2017-03-31 19:00:00                          50.0   \n",
       "2017-03-31 20:00:00                          26.0   \n",
       "2017-03-31 21:00:00                          16.0   \n",
       "2017-03-31 22:00:00                          12.0   \n",
       "2017-03-31 23:00:00                           5.0   \n",
       "\n",
       "                     Fremont Bridge East Sidewalk  \n",
       "Date                                               \n",
       "2012-10-03 00:00:00                           9.0  \n",
       "2012-10-03 01:00:00                           6.0  \n",
       "2012-10-03 02:00:00                           1.0  \n",
       "2012-10-03 03:00:00                           3.0  \n",
       "2012-10-03 04:00:00                           1.0  \n",
       "2012-10-03 05:00:00                          10.0  \n",
       "2012-10-03 06:00:00                          50.0  \n",
       "2012-10-03 07:00:00                          95.0  \n",
       "2012-10-03 08:00:00                         146.0  \n",
       "2012-10-03 09:00:00                         104.0  \n",
       "2012-10-03 10:00:00                          46.0  \n",
       "2012-10-03 11:00:00                          32.0  \n",
       "2012-10-03 12:00:00                          41.0  \n",
       "2012-10-03 13:00:00                          48.0  \n",
       "2012-10-03 14:00:00                          51.0  \n",
       "2012-10-03 15:00:00                          92.0  \n",
       "2012-10-03 16:00:00                         182.0  \n",
       "2012-10-03 17:00:00                         391.0  \n",
       "2012-10-03 18:00:00                         258.0  \n",
       "2012-10-03 19:00:00                          69.0  \n",
       "2012-10-03 20:00:00                          51.0  \n",
       "2012-10-03 21:00:00                          38.0  \n",
       "2012-10-03 22:00:00                          25.0  \n",
       "2012-10-03 23:00:00                          12.0  \n",
       "2012-10-04 00:00:00                          11.0  \n",
       "2012-10-04 01:00:00                           0.0  \n",
       "2012-10-04 02:00:00                           6.0  \n",
       "2012-10-04 03:00:00                           3.0  \n",
       "2012-10-04 04:00:00                           1.0  \n",
       "2012-10-04 05:00:00                          11.0  \n",
       "...                                           ...  \n",
       "2017-03-30 18:00:00                         213.0  \n",
       "2017-03-30 19:00:00                         125.0  \n",
       "2017-03-30 20:00:00                          58.0  \n",
       "2017-03-30 21:00:00                          21.0  \n",
       "2017-03-30 22:00:00                          20.0  \n",
       "2017-03-30 23:00:00                           5.0  \n",
       "2017-03-31 00:00:00                           4.0  \n",
       "2017-03-31 01:00:00                           0.0  \n",
       "2017-03-31 02:00:00                           0.0  \n",
       "2017-03-31 03:00:00                           0.0  \n",
       "2017-03-31 04:00:00                           3.0  \n",
       "2017-03-31 05:00:00                          14.0  \n",
       "2017-03-31 06:00:00                          49.0  \n",
       "2017-03-31 07:00:00                          99.0  \n",
       "2017-03-31 08:00:00                         162.0  \n",
       "2017-03-31 09:00:00                          70.0  \n",
       "2017-03-31 10:00:00                          38.0  \n",
       "2017-03-31 11:00:00                          31.0  \n",
       "2017-03-31 12:00:00                          37.0  \n",
       "2017-03-31 13:00:00                          34.0  \n",
       "2017-03-31 14:00:00                          55.0  \n",
       "2017-03-31 15:00:00                          87.0  \n",
       "2017-03-31 16:00:00                         223.0  \n",
       "2017-03-31 17:00:00                         333.0  \n",
       "2017-03-31 18:00:00                         206.0  \n",
       "2017-03-31 19:00:00                          84.0  \n",
       "2017-03-31 20:00:00                          36.0  \n",
       "2017-03-31 21:00:00                          40.0  \n",
       "2017-03-31 22:00:00                          22.0  \n",
       "2017-03-31 23:00:00                          15.0  \n",
       "\n",
       "[39384 rows x 2 columns]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data.columns = ['West','East']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>West</th>\n",
       "      <th>East</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-10-03 00:00:00</th>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 01:00:00</th>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 02:00:00</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 03:00:00</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 04:00:00</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 05:00:00</th>\n",
       "      <td>21.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 06:00:00</th>\n",
       "      <td>105.0</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 07:00:00</th>\n",
       "      <td>257.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 08:00:00</th>\n",
       "      <td>291.0</td>\n",
       "      <td>146.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 09:00:00</th>\n",
       "      <td>172.0</td>\n",
       "      <td>104.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 10:00:00</th>\n",
       "      <td>72.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 11:00:00</th>\n",
       "      <td>10.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 12:00:00</th>\n",
       "      <td>35.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 13:00:00</th>\n",
       "      <td>42.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 14:00:00</th>\n",
       "      <td>77.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 15:00:00</th>\n",
       "      <td>72.0</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 16:00:00</th>\n",
       "      <td>133.0</td>\n",
       "      <td>182.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 17:00:00</th>\n",
       "      <td>192.0</td>\n",
       "      <td>391.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 18:00:00</th>\n",
       "      <td>122.0</td>\n",
       "      <td>258.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 19:00:00</th>\n",
       "      <td>59.0</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 20:00:00</th>\n",
       "      <td>29.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 21:00:00</th>\n",
       "      <td>25.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 22:00:00</th>\n",
       "      <td>24.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 23:00:00</th>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 00:00:00</th>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 01:00:00</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 02:00:00</th>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 03:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 04:00:00</th>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 05:00:00</th>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 18:00:00</th>\n",
       "      <td>104.0</td>\n",
       "      <td>213.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 19:00:00</th>\n",
       "      <td>50.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 20:00:00</th>\n",
       "      <td>25.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 21:00:00</th>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 22:00:00</th>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 23:00:00</th>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 00:00:00</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 01:00:00</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 02:00:00</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 03:00:00</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 04:00:00</th>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 05:00:00</th>\n",
       "      <td>23.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 06:00:00</th>\n",
       "      <td>57.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 07:00:00</th>\n",
       "      <td>163.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 08:00:00</th>\n",
       "      <td>250.0</td>\n",
       "      <td>162.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 09:00:00</th>\n",
       "      <td>90.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 10:00:00</th>\n",
       "      <td>52.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 11:00:00</th>\n",
       "      <td>39.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 12:00:00</th>\n",
       "      <td>37.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 13:00:00</th>\n",
       "      <td>52.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 14:00:00</th>\n",
       "      <td>45.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 15:00:00</th>\n",
       "      <td>74.0</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 16:00:00</th>\n",
       "      <td>83.0</td>\n",
       "      <td>223.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 17:00:00</th>\n",
       "      <td>145.0</td>\n",
       "      <td>333.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 18:00:00</th>\n",
       "      <td>117.0</td>\n",
       "      <td>206.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 19:00:00</th>\n",
       "      <td>50.0</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 20:00:00</th>\n",
       "      <td>26.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 21:00:00</th>\n",
       "      <td>16.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 22:00:00</th>\n",
       "      <td>12.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 23:00:00</th>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>39384 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      West   East\n",
       "Date                             \n",
       "2012-10-03 00:00:00    4.0    9.0\n",
       "2012-10-03 01:00:00    4.0    6.0\n",
       "2012-10-03 02:00:00    1.0    1.0\n",
       "2012-10-03 03:00:00    2.0    3.0\n",
       "2012-10-03 04:00:00    6.0    1.0\n",
       "2012-10-03 05:00:00   21.0   10.0\n",
       "2012-10-03 06:00:00  105.0   50.0\n",
       "2012-10-03 07:00:00  257.0   95.0\n",
       "2012-10-03 08:00:00  291.0  146.0\n",
       "2012-10-03 09:00:00  172.0  104.0\n",
       "2012-10-03 10:00:00   72.0   46.0\n",
       "2012-10-03 11:00:00   10.0   32.0\n",
       "2012-10-03 12:00:00   35.0   41.0\n",
       "2012-10-03 13:00:00   42.0   48.0\n",
       "2012-10-03 14:00:00   77.0   51.0\n",
       "2012-10-03 15:00:00   72.0   92.0\n",
       "2012-10-03 16:00:00  133.0  182.0\n",
       "2012-10-03 17:00:00  192.0  391.0\n",
       "2012-10-03 18:00:00  122.0  258.0\n",
       "2012-10-03 19:00:00   59.0   69.0\n",
       "2012-10-03 20:00:00   29.0   51.0\n",
       "2012-10-03 21:00:00   25.0   38.0\n",
       "2012-10-03 22:00:00   24.0   25.0\n",
       "2012-10-03 23:00:00    5.0   12.0\n",
       "2012-10-04 00:00:00    7.0   11.0\n",
       "2012-10-04 01:00:00    3.0    0.0\n",
       "2012-10-04 02:00:00    3.0    6.0\n",
       "2012-10-04 03:00:00    0.0    3.0\n",
       "2012-10-04 04:00:00    7.0    1.0\n",
       "2012-10-04 05:00:00   15.0   11.0\n",
       "...                    ...    ...\n",
       "2017-03-30 18:00:00  104.0  213.0\n",
       "2017-03-30 19:00:00   50.0  125.0\n",
       "2017-03-30 20:00:00   25.0   58.0\n",
       "2017-03-30 21:00:00   15.0   21.0\n",
       "2017-03-30 22:00:00   10.0   20.0\n",
       "2017-03-30 23:00:00   11.0    5.0\n",
       "2017-03-31 00:00:00    2.0    4.0\n",
       "2017-03-31 01:00:00    2.0    0.0\n",
       "2017-03-31 02:00:00    1.0    0.0\n",
       "2017-03-31 03:00:00    1.0    0.0\n",
       "2017-03-31 04:00:00    3.0    3.0\n",
       "2017-03-31 05:00:00   23.0   14.0\n",
       "2017-03-31 06:00:00   57.0   49.0\n",
       "2017-03-31 07:00:00  163.0   99.0\n",
       "2017-03-31 08:00:00  250.0  162.0\n",
       "2017-03-31 09:00:00   90.0   70.0\n",
       "2017-03-31 10:00:00   52.0   38.0\n",
       "2017-03-31 11:00:00   39.0   31.0\n",
       "2017-03-31 12:00:00   37.0   37.0\n",
       "2017-03-31 13:00:00   52.0   34.0\n",
       "2017-03-31 14:00:00   45.0   55.0\n",
       "2017-03-31 15:00:00   74.0   87.0\n",
       "2017-03-31 16:00:00   83.0  223.0\n",
       "2017-03-31 17:00:00  145.0  333.0\n",
       "2017-03-31 18:00:00  117.0  206.0\n",
       "2017-03-31 19:00:00   50.0   84.0\n",
       "2017-03-31 20:00:00   26.0   36.0\n",
       "2017-03-31 21:00:00   16.0   40.0\n",
       "2017-03-31 22:00:00   12.0   22.0\n",
       "2017-03-31 23:00:00    5.0   15.0\n",
       "\n",
       "[39384 rows x 2 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data['total'] = data['West'] + data['East']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>West</th>\n",
       "      <th>East</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-10-03 00:00:00</th>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 01:00:00</th>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 02:00:00</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 03:00:00</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 04:00:00</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 05:00:00</th>\n",
       "      <td>21.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 06:00:00</th>\n",
       "      <td>105.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>155.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 07:00:00</th>\n",
       "      <td>257.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>352.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 08:00:00</th>\n",
       "      <td>291.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>437.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 09:00:00</th>\n",
       "      <td>172.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>276.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 10:00:00</th>\n",
       "      <td>72.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 11:00:00</th>\n",
       "      <td>10.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 12:00:00</th>\n",
       "      <td>35.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 13:00:00</th>\n",
       "      <td>42.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 14:00:00</th>\n",
       "      <td>77.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>128.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 15:00:00</th>\n",
       "      <td>72.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>164.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 16:00:00</th>\n",
       "      <td>133.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>315.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 17:00:00</th>\n",
       "      <td>192.0</td>\n",
       "      <td>391.0</td>\n",
       "      <td>583.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 18:00:00</th>\n",
       "      <td>122.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>380.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 19:00:00</th>\n",
       "      <td>59.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>128.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 20:00:00</th>\n",
       "      <td>29.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 21:00:00</th>\n",
       "      <td>25.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 22:00:00</th>\n",
       "      <td>24.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-03 23:00:00</th>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 00:00:00</th>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 01:00:00</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 02:00:00</th>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 03:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 04:00:00</th>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-04 05:00:00</th>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 18:00:00</th>\n",
       "      <td>104.0</td>\n",
       "      <td>213.0</td>\n",
       "      <td>317.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 19:00:00</th>\n",
       "      <td>50.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 20:00:00</th>\n",
       "      <td>25.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 21:00:00</th>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 22:00:00</th>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30 23:00:00</th>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 00:00:00</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 01:00:00</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 02:00:00</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 03:00:00</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 04:00:00</th>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 05:00:00</th>\n",
       "      <td>23.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 06:00:00</th>\n",
       "      <td>57.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>106.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 07:00:00</th>\n",
       "      <td>163.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>262.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 08:00:00</th>\n",
       "      <td>250.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>412.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 09:00:00</th>\n",
       "      <td>90.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 10:00:00</th>\n",
       "      <td>52.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 11:00:00</th>\n",
       "      <td>39.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 12:00:00</th>\n",
       "      <td>37.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 13:00:00</th>\n",
       "      <td>52.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 14:00:00</th>\n",
       "      <td>45.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 15:00:00</th>\n",
       "      <td>74.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>161.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 16:00:00</th>\n",
       "      <td>83.0</td>\n",
       "      <td>223.0</td>\n",
       "      <td>306.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 17:00:00</th>\n",
       "      <td>145.0</td>\n",
       "      <td>333.0</td>\n",
       "      <td>478.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 18:00:00</th>\n",
       "      <td>117.0</td>\n",
       "      <td>206.0</td>\n",
       "      <td>323.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 19:00:00</th>\n",
       "      <td>50.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>134.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 20:00:00</th>\n",
       "      <td>26.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 21:00:00</th>\n",
       "      <td>16.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 22:00:00</th>\n",
       "      <td>12.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31 23:00:00</th>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>39384 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      West   East  total\n",
       "Date                                    \n",
       "2012-10-03 00:00:00    4.0    9.0   13.0\n",
       "2012-10-03 01:00:00    4.0    6.0   10.0\n",
       "2012-10-03 02:00:00    1.0    1.0    2.0\n",
       "2012-10-03 03:00:00    2.0    3.0    5.0\n",
       "2012-10-03 04:00:00    6.0    1.0    7.0\n",
       "2012-10-03 05:00:00   21.0   10.0   31.0\n",
       "2012-10-03 06:00:00  105.0   50.0  155.0\n",
       "2012-10-03 07:00:00  257.0   95.0  352.0\n",
       "2012-10-03 08:00:00  291.0  146.0  437.0\n",
       "2012-10-03 09:00:00  172.0  104.0  276.0\n",
       "2012-10-03 10:00:00   72.0   46.0  118.0\n",
       "2012-10-03 11:00:00   10.0   32.0   42.0\n",
       "2012-10-03 12:00:00   35.0   41.0   76.0\n",
       "2012-10-03 13:00:00   42.0   48.0   90.0\n",
       "2012-10-03 14:00:00   77.0   51.0  128.0\n",
       "2012-10-03 15:00:00   72.0   92.0  164.0\n",
       "2012-10-03 16:00:00  133.0  182.0  315.0\n",
       "2012-10-03 17:00:00  192.0  391.0  583.0\n",
       "2012-10-03 18:00:00  122.0  258.0  380.0\n",
       "2012-10-03 19:00:00   59.0   69.0  128.0\n",
       "2012-10-03 20:00:00   29.0   51.0   80.0\n",
       "2012-10-03 21:00:00   25.0   38.0   63.0\n",
       "2012-10-03 22:00:00   24.0   25.0   49.0\n",
       "2012-10-03 23:00:00    5.0   12.0   17.0\n",
       "2012-10-04 00:00:00    7.0   11.0   18.0\n",
       "2012-10-04 01:00:00    3.0    0.0    3.0\n",
       "2012-10-04 02:00:00    3.0    6.0    9.0\n",
       "2012-10-04 03:00:00    0.0    3.0    3.0\n",
       "2012-10-04 04:00:00    7.0    1.0    8.0\n",
       "2012-10-04 05:00:00   15.0   11.0   26.0\n",
       "...                    ...    ...    ...\n",
       "2017-03-30 18:00:00  104.0  213.0  317.0\n",
       "2017-03-30 19:00:00   50.0  125.0  175.0\n",
       "2017-03-30 20:00:00   25.0   58.0   83.0\n",
       "2017-03-30 21:00:00   15.0   21.0   36.0\n",
       "2017-03-30 22:00:00   10.0   20.0   30.0\n",
       "2017-03-30 23:00:00   11.0    5.0   16.0\n",
       "2017-03-31 00:00:00    2.0    4.0    6.0\n",
       "2017-03-31 01:00:00    2.0    0.0    2.0\n",
       "2017-03-31 02:00:00    1.0    0.0    1.0\n",
       "2017-03-31 03:00:00    1.0    0.0    1.0\n",
       "2017-03-31 04:00:00    3.0    3.0    6.0\n",
       "2017-03-31 05:00:00   23.0   14.0   37.0\n",
       "2017-03-31 06:00:00   57.0   49.0  106.0\n",
       "2017-03-31 07:00:00  163.0   99.0  262.0\n",
       "2017-03-31 08:00:00  250.0  162.0  412.0\n",
       "2017-03-31 09:00:00   90.0   70.0  160.0\n",
       "2017-03-31 10:00:00   52.0   38.0   90.0\n",
       "2017-03-31 11:00:00   39.0   31.0   70.0\n",
       "2017-03-31 12:00:00   37.0   37.0   74.0\n",
       "2017-03-31 13:00:00   52.0   34.0   86.0\n",
       "2017-03-31 14:00:00   45.0   55.0  100.0\n",
       "2017-03-31 15:00:00   74.0   87.0  161.0\n",
       "2017-03-31 16:00:00   83.0  223.0  306.0\n",
       "2017-03-31 17:00:00  145.0  333.0  478.0\n",
       "2017-03-31 18:00:00  117.0  206.0  323.0\n",
       "2017-03-31 19:00:00   50.0   84.0  134.0\n",
       "2017-03-31 20:00:00   26.0   36.0   62.0\n",
       "2017-03-31 21:00:00   16.0   40.0   56.0\n",
       "2017-03-31 22:00:00   12.0   22.0   34.0\n",
       "2017-03-31 23:00:00    5.0   15.0   20.0\n",
       "\n",
       "[39384 rows x 3 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "No module named 'pygame'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m-----------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-78-ca8e7deb751e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mpytagcloud\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mcreate_tag_image\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmake_tags\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mpytagcloud\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlang\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcounter\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mget_tag_counts\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mYOUR_TEXT\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"A tag cloud is a visual representation for text data, typicallyused to depict keyword metadata on websites, or to visualize free form text.\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Users\\ZekeLabs\\Anaconda3\\lib\\site-packages\\pytagcloud\\__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mcopy\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mmath\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0msin\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcos\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mceil\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mpygame\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mtransform\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfont\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmask\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mSurface\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mRect\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mSRCALPHA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdraw\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mpygame\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msprite\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mGroup\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mSprite\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcollide_mask\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mrandom\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mrandint\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mchoice\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mImportError\u001b[0m: No module named 'pygame'"
     ]
    }
   ],
   "source": [
    "from pytagcloud import create_tag_image, make_tags\n",
    "from pytagcloud.lang.counter import get_tag_counts\n",
    "\n",
    "YOUR_TEXT = \"A tag cloud is a visual representation for text data, typically\\\n",
    "used to depict keyword metadata on websites, or to visualize free form text.\"\n",
    "\n",
    "tags = make_tags(get_tag_counts(YOUR_TEXT), maxsize=120)\n",
    "\n",
    "create_tag_image(tags, 'cloud_large.png', size=(900, 600), fontname='Lobster')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('https://data.seattle.gov/api/views/65db-xm6k/rows.csv?accessType=DOWNLOAD')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Fremont Bridge West Sidewalk</th>\n",
       "      <th>Fremont Bridge East Sidewalk</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10/03/2012 12:00:00 AM</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10/03/2012 01:00:00 AM</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10/03/2012 02:00:00 AM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10/03/2012 03:00:00 AM</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10/03/2012 04:00:00 AM</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Date  Fremont Bridge West Sidewalk  \\\n",
       "0  10/03/2012 12:00:00 AM                           4.0   \n",
       "1  10/03/2012 01:00:00 AM                           4.0   \n",
       "2  10/03/2012 02:00:00 AM                           1.0   \n",
       "3  10/03/2012 03:00:00 AM                           2.0   \n",
       "4  10/03/2012 04:00:00 AM                           6.0   \n",
       "\n",
       "   Fremont Bridge East Sidewalk  \n",
       "0                           9.0  \n",
       "1                           6.0  \n",
       "2                           1.0  \n",
       "3                           3.0  \n",
       "4                           1.0  "
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pd."
   ]
  }
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