22 Pandas Time Series Analysis 6.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### We live in a world with different timezones. If you are having morning coffee in new york at 9 AM it might be a time for dinner in Mumbai, India because it would be 6.30 PM there. Handling time zone could become necessity while doing time series analysis in Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](timezones_world_map.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Timezone Handling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
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    "</style>"
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  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date Time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-08-17 09:00:00</th>\n",
       "      <td>72.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 09:15:00</th>\n",
       "      <td>71.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 09:30:00</th>\n",
       "      <td>71.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 10:00:00</th>\n",
       "      <td>72.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 10:30:00</th>\n",
       "      <td>73.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 11:00:00</th>\n",
       "      <td>72.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Price\n",
       "Date Time                 \n",
       "2017-08-17 09:00:00  72.38\n",
       "2017-08-17 09:15:00  71.00\n",
       "2017-08-17 09:30:00  71.67\n",
       "2017-08-17 10:00:00  72.80\n",
       "2017-08-17 10:30:00  73.00\n",
       "2017-08-17 11:00:00  72.50"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"msft.csv\", header=1,index_col='Date Time',parse_dates=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-08-17 09:00:00', '2017-08-17 09:15:00',\n",
       "               '2017-08-17 09:30:00', '2017-08-17 10:00:00',\n",
       "               '2017-08-17 10:30:00', '2017-08-17 11:00:00'],\n",
       "              dtype='datetime64[ns]', name='Date Time', freq=None)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Two types of datetimes in python\n",
    "### 1.Naive (no timezone awareness)\n",
    "### 2.Timezone aware datetime"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Convert naive DatetimeIndex to timezone aware DatetimeIndex using tz_localize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date Time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-08-17 09:00:00-04:00</th>\n",
       "      <td>72.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 09:15:00-04:00</th>\n",
       "      <td>71.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 09:30:00-04:00</th>\n",
       "      <td>71.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 10:00:00-04:00</th>\n",
       "      <td>72.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 10:30:00-04:00</th>\n",
       "      <td>73.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 11:00:00-04:00</th>\n",
       "      <td>72.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Price\n",
       "Date Time                       \n",
       "2017-08-17 09:00:00-04:00  72.38\n",
       "2017-08-17 09:15:00-04:00  71.00\n",
       "2017-08-17 09:30:00-04:00  71.67\n",
       "2017-08-17 10:00:00-04:00  72.80\n",
       "2017-08-17 10:30:00-04:00  73.00\n",
       "2017-08-17 11:00:00-04:00  72.50"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.tz_localize(tz='US/Eastern')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-08-17 09:00:00-04:00', '2017-08-17 09:15:00-04:00',\n",
       "               '2017-08-17 09:30:00-04:00', '2017-08-17 10:00:00-04:00',\n",
       "               '2017-08-17 10:30:00-04:00', '2017-08-17 11:00:00-04:00'],\n",
       "              dtype='datetime64[ns, US/Eastern]', name='Date Time', freq=None)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date Time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-08-17 15:00:00+02:00</th>\n",
       "      <td>72.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 15:15:00+02:00</th>\n",
       "      <td>71.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 15:30:00+02:00</th>\n",
       "      <td>71.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 16:00:00+02:00</th>\n",
       "      <td>72.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 16:30:00+02:00</th>\n",
       "      <td>73.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 17:00:00+02:00</th>\n",
       "      <td>72.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Price\n",
       "Date Time                       \n",
       "2017-08-17 15:00:00+02:00  72.38\n",
       "2017-08-17 15:15:00+02:00  71.00\n",
       "2017-08-17 15:30:00+02:00  71.67\n",
       "2017-08-17 16:00:00+02:00  72.80\n",
       "2017-08-17 16:30:00+02:00  73.00\n",
       "2017-08-17 17:00:00+02:00  72.50"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.tz_convert(tz='Europe/Berlin')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-08-17 15:00:00+02:00', '2017-08-17 15:15:00+02:00',\n",
       "               '2017-08-17 15:30:00+02:00', '2017-08-17 16:00:00+02:00',\n",
       "               '2017-08-17 16:30:00+02:00', '2017-08-17 17:00:00+02:00'],\n",
       "              dtype='datetime64[ns, Europe/Berlin]', name='Date Time', freq=None)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Africa/Abidjan',\n",
       " 'Africa/Accra',\n",
       " 'Africa/Addis_Ababa',\n",
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       " 'Africa/Bissau',\n",
       " 'Africa/Blantyre',\n",
       " 'Africa/Brazzaville',\n",
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       " 'Africa/Douala',\n",
       " 'Africa/El_Aaiun',\n",
       " 'Africa/Freetown',\n",
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       " 'Africa/Harare',\n",
       " 'Africa/Johannesburg',\n",
       " 'Africa/Juba',\n",
       " 'Africa/Kampala',\n",
       " 'Africa/Khartoum',\n",
       " 'Africa/Kigali',\n",
       " 'Africa/Kinshasa',\n",
       " 'Africa/Lagos',\n",
       " 'Africa/Libreville',\n",
       " 'Africa/Lome',\n",
       " 'Africa/Luanda',\n",
       " 'Africa/Lubumbashi',\n",
       " 'Africa/Lusaka',\n",
       " 'Africa/Malabo',\n",
       " 'Africa/Maputo',\n",
       " 'Africa/Maseru',\n",
       " 'Africa/Mbabane',\n",
       " 'Africa/Mogadishu',\n",
       " 'Africa/Monrovia',\n",
       " 'Africa/Nairobi',\n",
       " 'Africa/Ndjamena',\n",
       " 'Africa/Niamey',\n",
       " 'Africa/Nouakchott',\n",
       " 'Africa/Ouagadougou',\n",
       " 'Africa/Porto-Novo',\n",
       " 'Africa/Sao_Tome',\n",
       " 'Africa/Timbuktu',\n",
       " 'Africa/Tripoli',\n",
       " 'Africa/Tunis',\n",
       " 'Africa/Windhoek',\n",
       " 'America/Adak',\n",
       " 'America/Anchorage',\n",
       " 'America/Anguilla',\n",
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       " 'America/Araguaina',\n",
       " 'America/Argentina/Buenos_Aires',\n",
       " 'America/Argentina/Catamarca',\n",
       " 'America/Argentina/ComodRivadavia',\n",
       " 'America/Argentina/Cordoba',\n",
       " 'America/Argentina/Jujuy',\n",
       " 'America/Argentina/La_Rioja',\n",
       " 'America/Argentina/Mendoza',\n",
       " 'America/Argentina/Rio_Gallegos',\n",
       " 'America/Argentina/Salta',\n",
       " 'America/Argentina/San_Juan',\n",
       " 'America/Argentina/San_Luis',\n",
       " 'America/Argentina/Tucuman',\n",
       " 'America/Argentina/Ushuaia',\n",
       " 'America/Aruba',\n",
       " 'America/Asuncion',\n",
       " 'America/Atikokan',\n",
       " 'America/Atka',\n",
       " 'America/Bahia',\n",
       " 'America/Bahia_Banderas',\n",
       " 'America/Barbados',\n",
       " 'America/Belem',\n",
       " 'America/Belize',\n",
       " 'America/Blanc-Sablon',\n",
       " 'America/Boa_Vista',\n",
       " 'America/Bogota',\n",
       " 'America/Boise',\n",
       " 'America/Buenos_Aires',\n",
       " 'America/Cambridge_Bay',\n",
       " 'America/Campo_Grande',\n",
       " 'America/Cancun',\n",
       " 'America/Caracas',\n",
       " 'America/Catamarca',\n",
       " 'America/Cayenne',\n",
       " 'America/Cayman',\n",
       " 'America/Chicago',\n",
       " 'America/Chihuahua',\n",
       " 'America/Coral_Harbour',\n",
       " 'America/Cordoba',\n",
       " 'America/Costa_Rica',\n",
       " 'America/Creston',\n",
       " 'America/Cuiaba',\n",
       " 'America/Curacao',\n",
       " 'America/Danmarkshavn',\n",
       " 'America/Dawson',\n",
       " 'America/Dawson_Creek',\n",
       " 'America/Denver',\n",
       " 'America/Detroit',\n",
       " 'America/Dominica',\n",
       " 'America/Edmonton',\n",
       " 'America/Eirunepe',\n",
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       " 'America/Ensenada',\n",
       " 'America/Fort_Nelson',\n",
       " 'America/Fort_Wayne',\n",
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       " 'America/Glace_Bay',\n",
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       " 'America/Goose_Bay',\n",
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       " 'America/Guayaquil',\n",
       " 'America/Guyana',\n",
       " 'America/Halifax',\n",
       " 'America/Havana',\n",
       " 'America/Hermosillo',\n",
       " 'America/Indiana/Indianapolis',\n",
       " 'America/Indiana/Knox',\n",
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       " 'America/Indiana/Petersburg',\n",
       " 'America/Indiana/Tell_City',\n",
       " 'America/Indiana/Vevay',\n",
       " 'America/Indiana/Vincennes',\n",
       " 'America/Indiana/Winamac',\n",
       " 'America/Indianapolis',\n",
       " 'America/Inuvik',\n",
       " 'America/Iqaluit',\n",
       " 'America/Jamaica',\n",
       " 'America/Jujuy',\n",
       " 'America/Juneau',\n",
       " 'America/Kentucky/Louisville',\n",
       " 'America/Kentucky/Monticello',\n",
       " 'America/Knox_IN',\n",
       " 'America/Kralendijk',\n",
       " 'America/La_Paz',\n",
       " 'America/Lima',\n",
       " 'America/Los_Angeles',\n",
       " 'America/Louisville',\n",
       " 'America/Lower_Princes',\n",
       " 'America/Maceio',\n",
       " 'America/Managua',\n",
       " 'America/Manaus',\n",
       " 'America/Marigot',\n",
       " 'America/Martinique',\n",
       " 'America/Matamoros',\n",
       " 'America/Mazatlan',\n",
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       " 'America/Menominee',\n",
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       " 'America/Metlakatla',\n",
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       " 'America/Miquelon',\n",
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       " 'America/Montevideo',\n",
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       " 'America/Montserrat',\n",
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       " 'America/New_York',\n",
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       " 'America/Nome',\n",
       " 'America/Noronha',\n",
       " 'America/North_Dakota/Beulah',\n",
       " 'America/North_Dakota/Center',\n",
       " 'America/North_Dakota/New_Salem',\n",
       " 'America/Nuuk',\n",
       " 'America/Ojinaga',\n",
       " 'America/Panama',\n",
       " 'America/Pangnirtung',\n",
       " 'America/Paramaribo',\n",
       " 'America/Phoenix',\n",
       " 'America/Port-au-Prince',\n",
       " 'America/Port_of_Spain',\n",
       " 'America/Porto_Acre',\n",
       " 'America/Porto_Velho',\n",
       " 'America/Puerto_Rico',\n",
       " 'America/Punta_Arenas',\n",
       " 'America/Rainy_River',\n",
       " 'America/Rankin_Inlet',\n",
       " 'America/Recife',\n",
       " 'America/Regina',\n",
       " 'America/Resolute',\n",
       " 'America/Rio_Branco',\n",
       " 'America/Rosario',\n",
       " 'America/Santa_Isabel',\n",
       " 'America/Santarem',\n",
       " 'America/Santiago',\n",
       " 'America/Santo_Domingo',\n",
       " 'America/Sao_Paulo',\n",
       " 'America/Scoresbysund',\n",
       " 'America/Shiprock',\n",
       " 'America/Sitka',\n",
       " 'America/St_Barthelemy',\n",
       " 'America/St_Johns',\n",
       " 'America/St_Kitts',\n",
       " 'America/St_Lucia',\n",
       " 'America/St_Thomas',\n",
       " 'America/St_Vincent',\n",
       " 'America/Swift_Current',\n",
       " 'America/Tegucigalpa',\n",
       " 'America/Thule',\n",
       " 'America/Thunder_Bay',\n",
       " 'America/Tijuana',\n",
       " 'America/Toronto',\n",
       " 'America/Tortola',\n",
       " 'America/Vancouver',\n",
       " 'America/Virgin',\n",
       " 'America/Whitehorse',\n",
       " 'America/Winnipeg',\n",
       " 'America/Yakutat',\n",
       " 'America/Yellowknife',\n",
       " 'Antarctica/Casey',\n",
       " 'Antarctica/Davis',\n",
       " 'Antarctica/DumontDUrville',\n",
       " 'Antarctica/Macquarie',\n",
       " 'Antarctica/Mawson',\n",
       " 'Antarctica/McMurdo',\n",
       " 'Antarctica/Palmer',\n",
       " 'Antarctica/Rothera',\n",
       " 'Antarctica/South_Pole',\n",
       " 'Antarctica/Syowa',\n",
       " 'Antarctica/Troll',\n",
       " 'Antarctica/Vostok',\n",
       " 'Arctic/Longyearbyen',\n",
       " 'Asia/Aden',\n",
       " 'Asia/Almaty',\n",
       " 'Asia/Amman',\n",
       " 'Asia/Anadyr',\n",
       " 'Asia/Aqtau',\n",
       " 'Asia/Aqtobe',\n",
       " 'Asia/Ashgabat',\n",
       " 'Asia/Ashkhabad',\n",
       " 'Asia/Atyrau',\n",
       " 'Asia/Baghdad',\n",
       " 'Asia/Bahrain',\n",
       " 'Asia/Baku',\n",
       " 'Asia/Bangkok',\n",
       " 'Asia/Barnaul',\n",
       " 'Asia/Beirut',\n",
       " 'Asia/Bishkek',\n",
       " 'Asia/Brunei',\n",
       " 'Asia/Calcutta',\n",
       " 'Asia/Chita',\n",
       " 'Asia/Choibalsan',\n",
       " 'Asia/Chongqing',\n",
       " 'Asia/Chungking',\n",
       " 'Asia/Colombo',\n",
       " 'Asia/Dacca',\n",
       " 'Asia/Damascus',\n",
       " 'Asia/Dhaka',\n",
       " 'Asia/Dili',\n",
       " 'Asia/Dubai',\n",
       " 'Asia/Dushanbe',\n",
       " 'Asia/Famagusta',\n",
       " 'Asia/Gaza',\n",
       " 'Asia/Harbin',\n",
       " 'Asia/Hebron',\n",
       " 'Asia/Ho_Chi_Minh',\n",
       " 'Asia/Hong_Kong',\n",
       " 'Asia/Hovd',\n",
       " 'Asia/Irkutsk',\n",
       " 'Asia/Istanbul',\n",
       " 'Asia/Jakarta',\n",
       " 'Asia/Jayapura',\n",
       " 'Asia/Jerusalem',\n",
       " 'Asia/Kabul',\n",
       " 'Asia/Kamchatka',\n",
       " 'Asia/Karachi',\n",
       " 'Asia/Kashgar',\n",
       " 'Asia/Kathmandu',\n",
       " 'Asia/Katmandu',\n",
       " 'Asia/Khandyga',\n",
       " 'Asia/Kolkata',\n",
       " 'Asia/Krasnoyarsk',\n",
       " 'Asia/Kuala_Lumpur',\n",
       " 'Asia/Kuching',\n",
       " 'Asia/Kuwait',\n",
       " 'Asia/Macao',\n",
       " 'Asia/Macau',\n",
       " 'Asia/Magadan',\n",
       " 'Asia/Makassar',\n",
       " 'Asia/Manila',\n",
       " 'Asia/Muscat',\n",
       " 'Asia/Nicosia',\n",
       " 'Asia/Novokuznetsk',\n",
       " 'Asia/Novosibirsk',\n",
       " 'Asia/Omsk',\n",
       " 'Asia/Oral',\n",
       " 'Asia/Phnom_Penh',\n",
       " 'Asia/Pontianak',\n",
       " 'Asia/Pyongyang',\n",
       " 'Asia/Qatar',\n",
       " 'Asia/Qostanay',\n",
       " 'Asia/Qyzylorda',\n",
       " 'Asia/Rangoon',\n",
       " 'Asia/Riyadh',\n",
       " 'Asia/Saigon',\n",
       " 'Asia/Sakhalin',\n",
       " 'Asia/Samarkand',\n",
       " 'Asia/Seoul',\n",
       " 'Asia/Shanghai',\n",
       " 'Asia/Singapore',\n",
       " 'Asia/Srednekolymsk',\n",
       " 'Asia/Taipei',\n",
       " 'Asia/Tashkent',\n",
       " 'Asia/Tbilisi',\n",
       " 'Asia/Tehran',\n",
       " 'Asia/Tel_Aviv',\n",
       " 'Asia/Thimbu',\n",
       " 'Asia/Thimphu',\n",
       " 'Asia/Tokyo',\n",
       " 'Asia/Tomsk',\n",
       " 'Asia/Ujung_Pandang',\n",
       " 'Asia/Ulaanbaatar',\n",
       " 'Asia/Ulan_Bator',\n",
       " 'Asia/Urumqi',\n",
       " 'Asia/Ust-Nera',\n",
       " 'Asia/Vientiane',\n",
       " 'Asia/Vladivostok',\n",
       " 'Asia/Yakutsk',\n",
       " 'Asia/Yangon',\n",
       " 'Asia/Yekaterinburg',\n",
       " 'Asia/Yerevan',\n",
       " 'Atlantic/Azores',\n",
       " 'Atlantic/Bermuda',\n",
       " 'Atlantic/Canary',\n",
       " 'Atlantic/Cape_Verde',\n",
       " 'Atlantic/Faeroe',\n",
       " 'Atlantic/Faroe',\n",
       " 'Atlantic/Jan_Mayen',\n",
       " 'Atlantic/Madeira',\n",
       " 'Atlantic/Reykjavik',\n",
       " 'Atlantic/South_Georgia',\n",
       " 'Atlantic/St_Helena',\n",
       " 'Atlantic/Stanley',\n",
       " 'Australia/ACT',\n",
       " 'Australia/Adelaide',\n",
       " 'Australia/Brisbane',\n",
       " 'Australia/Broken_Hill',\n",
       " 'Australia/Canberra',\n",
       " 'Australia/Currie',\n",
       " 'Australia/Darwin',\n",
       " 'Australia/Eucla',\n",
       " 'Australia/Hobart',\n",
       " 'Australia/LHI',\n",
       " 'Australia/Lindeman',\n",
       " 'Australia/Lord_Howe',\n",
       " 'Australia/Melbourne',\n",
       " 'Australia/NSW',\n",
       " 'Australia/North',\n",
       " 'Australia/Perth',\n",
       " 'Australia/Queensland',\n",
       " 'Australia/South',\n",
       " 'Australia/Sydney',\n",
       " 'Australia/Tasmania',\n",
       " 'Australia/Victoria',\n",
       " 'Australia/West',\n",
       " 'Australia/Yancowinna',\n",
       " 'Brazil/Acre',\n",
       " 'Brazil/DeNoronha',\n",
       " 'Brazil/East',\n",
       " 'Brazil/West',\n",
       " 'CET',\n",
       " 'CST6CDT',\n",
       " 'Canada/Atlantic',\n",
       " 'Canada/Central',\n",
       " 'Canada/Eastern',\n",
       " 'Canada/Mountain',\n",
       " 'Canada/Newfoundland',\n",
       " 'Canada/Pacific',\n",
       " 'Canada/Saskatchewan',\n",
       " 'Canada/Yukon',\n",
       " 'Chile/Continental',\n",
       " 'Chile/EasterIsland',\n",
       " 'Cuba',\n",
       " 'EET',\n",
       " 'EST',\n",
       " 'EST5EDT',\n",
       " 'Egypt',\n",
       " 'Eire',\n",
       " 'Etc/GMT',\n",
       " 'Etc/GMT+0',\n",
       " 'Etc/GMT+1',\n",
       " 'Etc/GMT+10',\n",
       " 'Etc/GMT+11',\n",
       " 'Etc/GMT+12',\n",
       " 'Etc/GMT+2',\n",
       " 'Etc/GMT+3',\n",
       " 'Etc/GMT+4',\n",
       " 'Etc/GMT+5',\n",
       " 'Etc/GMT+6',\n",
       " 'Etc/GMT+7',\n",
       " 'Etc/GMT+8',\n",
       " 'Etc/GMT+9',\n",
       " 'Etc/GMT-0',\n",
       " 'Etc/GMT-1',\n",
       " 'Etc/GMT-10',\n",
       " 'Etc/GMT-11',\n",
       " 'Etc/GMT-12',\n",
       " 'Etc/GMT-13',\n",
       " 'Etc/GMT-14',\n",
       " 'Etc/GMT-2',\n",
       " 'Etc/GMT-3',\n",
       " 'Etc/GMT-4',\n",
       " 'Etc/GMT-5',\n",
       " 'Etc/GMT-6',\n",
       " 'Etc/GMT-7',\n",
       " 'Etc/GMT-8',\n",
       " 'Etc/GMT-9',\n",
       " 'Etc/GMT0',\n",
       " 'Etc/Greenwich',\n",
       " 'Etc/UCT',\n",
       " 'Etc/UTC',\n",
       " 'Etc/Universal',\n",
       " 'Etc/Zulu',\n",
       " 'Europe/Amsterdam',\n",
       " 'Europe/Andorra',\n",
       " 'Europe/Astrakhan',\n",
       " 'Europe/Athens',\n",
       " 'Europe/Belfast',\n",
       " 'Europe/Belgrade',\n",
       " 'Europe/Berlin',\n",
       " 'Europe/Bratislava',\n",
       " 'Europe/Brussels',\n",
       " 'Europe/Bucharest',\n",
       " 'Europe/Budapest',\n",
       " 'Europe/Busingen',\n",
       " 'Europe/Chisinau',\n",
       " 'Europe/Copenhagen',\n",
       " 'Europe/Dublin',\n",
       " 'Europe/Gibraltar',\n",
       " 'Europe/Guernsey',\n",
       " 'Europe/Helsinki',\n",
       " 'Europe/Isle_of_Man',\n",
       " 'Europe/Istanbul',\n",
       " 'Europe/Jersey',\n",
       " 'Europe/Kaliningrad',\n",
       " 'Europe/Kiev',\n",
       " 'Europe/Kirov',\n",
       " 'Europe/Lisbon',\n",
       " 'Europe/Ljubljana',\n",
       " 'Europe/London',\n",
       " 'Europe/Luxembourg',\n",
       " 'Europe/Madrid',\n",
       " 'Europe/Malta',\n",
       " 'Europe/Mariehamn',\n",
       " 'Europe/Minsk',\n",
       " 'Europe/Monaco',\n",
       " 'Europe/Moscow',\n",
       " 'Europe/Nicosia',\n",
       " 'Europe/Oslo',\n",
       " 'Europe/Paris',\n",
       " 'Europe/Podgorica',\n",
       " 'Europe/Prague',\n",
       " 'Europe/Riga',\n",
       " 'Europe/Rome',\n",
       " 'Europe/Samara',\n",
       " 'Europe/San_Marino',\n",
       " 'Europe/Sarajevo',\n",
       " 'Europe/Saratov',\n",
       " 'Europe/Simferopol',\n",
       " 'Europe/Skopje',\n",
       " 'Europe/Sofia',\n",
       " 'Europe/Stockholm',\n",
       " 'Europe/Tallinn',\n",
       " 'Europe/Tirane',\n",
       " 'Europe/Tiraspol',\n",
       " 'Europe/Ulyanovsk',\n",
       " 'Europe/Uzhgorod',\n",
       " 'Europe/Vaduz',\n",
       " 'Europe/Vatican',\n",
       " 'Europe/Vienna',\n",
       " 'Europe/Vilnius',\n",
       " 'Europe/Volgograd',\n",
       " 'Europe/Warsaw',\n",
       " 'Europe/Zagreb',\n",
       " 'Europe/Zaporozhye',\n",
       " 'Europe/Zurich',\n",
       " 'GB',\n",
       " 'GB-Eire',\n",
       " 'GMT',\n",
       " 'GMT+0',\n",
       " 'GMT-0',\n",
       " 'GMT0',\n",
       " 'Greenwich',\n",
       " 'HST',\n",
       " 'Hongkong',\n",
       " 'Iceland',\n",
       " 'Indian/Antananarivo',\n",
       " 'Indian/Chagos',\n",
       " 'Indian/Christmas',\n",
       " 'Indian/Cocos',\n",
       " 'Indian/Comoro',\n",
       " 'Indian/Kerguelen',\n",
       " 'Indian/Mahe',\n",
       " 'Indian/Maldives',\n",
       " 'Indian/Mauritius',\n",
       " 'Indian/Mayotte',\n",
       " 'Indian/Reunion',\n",
       " 'Iran',\n",
       " 'Israel',\n",
       " 'Jamaica',\n",
       " 'Japan',\n",
       " 'Kwajalein',\n",
       " 'Libya',\n",
       " 'MET',\n",
       " 'MST',\n",
       " 'MST7MDT',\n",
       " 'Mexico/BajaNorte',\n",
       " 'Mexico/BajaSur',\n",
       " 'Mexico/General',\n",
       " 'NZ',\n",
       " 'NZ-CHAT',\n",
       " 'Navajo',\n",
       " 'PRC',\n",
       " 'PST8PDT',\n",
       " 'Pacific/Apia',\n",
       " 'Pacific/Auckland',\n",
       " 'Pacific/Bougainville',\n",
       " 'Pacific/Chatham',\n",
       " 'Pacific/Chuuk',\n",
       " 'Pacific/Easter',\n",
       " 'Pacific/Efate',\n",
       " 'Pacific/Enderbury',\n",
       " 'Pacific/Fakaofo',\n",
       " 'Pacific/Fiji',\n",
       " 'Pacific/Funafuti',\n",
       " 'Pacific/Galapagos',\n",
       " 'Pacific/Gambier',\n",
       " 'Pacific/Guadalcanal',\n",
       " 'Pacific/Guam',\n",
       " 'Pacific/Honolulu',\n",
       " 'Pacific/Johnston',\n",
       " 'Pacific/Kiritimati',\n",
       " 'Pacific/Kosrae',\n",
       " 'Pacific/Kwajalein',\n",
       " 'Pacific/Majuro',\n",
       " 'Pacific/Marquesas',\n",
       " 'Pacific/Midway',\n",
       " 'Pacific/Nauru',\n",
       " 'Pacific/Niue',\n",
       " 'Pacific/Norfolk',\n",
       " 'Pacific/Noumea',\n",
       " 'Pacific/Pago_Pago',\n",
       " 'Pacific/Palau',\n",
       " 'Pacific/Pitcairn',\n",
       " 'Pacific/Pohnpei',\n",
       " 'Pacific/Ponape',\n",
       " 'Pacific/Port_Moresby',\n",
       " 'Pacific/Rarotonga',\n",
       " 'Pacific/Saipan',\n",
       " 'Pacific/Samoa',\n",
       " 'Pacific/Tahiti',\n",
       " 'Pacific/Tarawa',\n",
       " 'Pacific/Tongatapu',\n",
       " 'Pacific/Truk',\n",
       " 'Pacific/Wake',\n",
       " 'Pacific/Wallis',\n",
       " 'Pacific/Yap',\n",
       " 'Poland',\n",
       " 'Portugal',\n",
       " 'ROC',\n",
       " 'ROK',\n",
       " 'Singapore',\n",
       " 'Turkey',\n",
       " 'UCT',\n",
       " 'US/Alaska',\n",
       " 'US/Aleutian',\n",
       " 'US/Arizona',\n",
       " 'US/Central',\n",
       " 'US/East-Indiana',\n",
       " 'US/Eastern',\n",
       " 'US/Hawaii',\n",
       " 'US/Indiana-Starke',\n",
       " 'US/Michigan',\n",
       " 'US/Mountain',\n",
       " 'US/Pacific',\n",
       " 'US/Samoa',\n",
       " 'UTC',\n",
       " 'Universal',\n",
       " 'W-SU',\n",
       " 'WET',\n",
       " 'Zulu']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pytz import all_timezones\n",
    "all_timezones\n",
    "\n",
    "## All the timezones that are avaiable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date Time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-08-17 18:30:00+05:30</th>\n",
       "      <td>72.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 18:45:00+05:30</th>\n",
       "      <td>71.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 19:00:00+05:30</th>\n",
       "      <td>71.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 19:30:00+05:30</th>\n",
       "      <td>72.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 20:00:00+05:30</th>\n",
       "      <td>73.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 20:30:00+05:30</th>\n",
       "      <td>72.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Price\n",
       "Date Time                       \n",
       "2017-08-17 18:30:00+05:30  72.38\n",
       "2017-08-17 18:45:00+05:30  71.00\n",
       "2017-08-17 19:00:00+05:30  71.67\n",
       "2017-08-17 19:30:00+05:30  72.80\n",
       "2017-08-17 20:00:00+05:30  73.00\n",
       "2017-08-17 20:30:00+05:30  72.50"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index = df.index.tz_convert('Asia/Calcutta')\n",
    "# tz database doesn't have any Mumbai timezone but calcutta and mumbai are both in same timezone so we will use that\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date Time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-08-17 18:30:00+05:30</th>\n",
       "      <td>72.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 18:45:00+05:30</th>\n",
       "      <td>71.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 19:00:00+05:30</th>\n",
       "      <td>71.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 19:30:00+05:30</th>\n",
       "      <td>72.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 20:00:00+05:30</th>\n",
       "      <td>73.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17 20:30:00+05:30</th>\n",
       "      <td>72.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Price\n",
       "Date Time                       \n",
       "2017-08-17 18:30:00+05:30  72.38\n",
       "2017-08-17 18:45:00+05:30  71.00\n",
       "2017-08-17 19:00:00+05:30  71.67\n",
       "2017-08-17 19:30:00+05:30  72.80\n",
       "2017-08-17 20:00:00+05:30  73.00\n",
       "2017-08-17 20:30:00+05:30  72.50"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.tz_convert('Asia/Calcutta')\n",
    "df\n",
    "## same effect as before"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using timezones in date_range"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Timezone anware range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2012-03-06 00:09:00', '2012-03-06 01:09:00',\n",
       "               '2012-03-06 02:09:00', '2012-03-06 03:09:00',\n",
       "               '2012-03-06 04:09:00', '2012-03-06 05:09:00',\n",
       "               '2012-03-06 06:09:00', '2012-03-06 07:09:00',\n",
       "               '2012-03-06 08:09:00', '2012-03-06 09:09:00'],\n",
       "              dtype='datetime64[ns]', freq='H')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rng = pd.date_range('3/6/2012 00:09:00', periods=10, freq='H')\n",
    "rng"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (1) timezone using pytz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2012-03-06 00:09:00+00:00', '2012-03-06 01:09:00+00:00',\n",
       "               '2012-03-06 02:09:00+00:00', '2012-03-06 03:09:00+00:00',\n",
       "               '2012-03-06 04:09:00+00:00', '2012-03-06 05:09:00+00:00',\n",
       "               '2012-03-06 06:09:00+00:00', '2012-03-06 07:09:00+00:00',\n",
       "               '2012-03-06 08:09:00+00:00', '2012-03-06 09:09:00+00:00'],\n",
       "              dtype='datetime64[ns, Europe/London]', freq='H')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "london = pd.date_range('3/6/2012 00:09:00', periods=10, freq='H',tz='Europe/London')\n",
    "london\n",
    "## it is timezpne aware"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (2) timezone using dateutil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2012-03-06 00:00:00+00:00', '2012-03-06 01:00:00+00:00',\n",
       "               '2012-03-06 02:00:00+00:00', '2012-03-06 03:00:00+00:00',\n",
       "               '2012-03-06 04:00:00+00:00', '2012-03-06 05:00:00+00:00',\n",
       "               '2012-03-06 06:00:00+00:00', '2012-03-06 07:00:00+00:00',\n",
       "               '2012-03-06 08:00:00+00:00', '2012-03-06 09:00:00+00:00'],\n",
       "              dtype='datetime64[ns, tzfile('GB-Eire')]', freq='H')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "td = pd.date_range('3/6/2012 00:00', periods=10, freq='H',tz='dateutil/Europe/London')\n",
    "td"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pandas documentation indicates that difference between pytz timezone and dateutil timezones is\n",
    "### 1.In pytz you can find a list of common (and less common) time zones using from pytz import common_timezones, all_timezones\n",
    "### 2.dateutil uses the OS timezones so there isn’t a fixed list available. For common zones, the names are the same as pytz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Airthmetic between different timezones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017-08-22 09:00:00    0\n",
       "2017-08-22 09:30:00    1\n",
       "2017-08-22 10:00:00    2\n",
       "2017-08-22 10:30:00    3\n",
       "2017-08-22 11:00:00    4\n",
       "2017-08-22 11:30:00    5\n",
       "2017-08-22 12:00:00    6\n",
       "2017-08-22 12:30:00    7\n",
       "2017-08-22 13:00:00    8\n",
       "2017-08-22 13:30:00    9\n",
       "Freq: 30T, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rng = pd.date_range(start=\"2017-08-22 09:00:00\",periods=10, freq='30min')\n",
    "s = pd.Series(range(10),index=rng)\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017-08-22 09:00:00+02:00    0\n",
       "2017-08-22 09:30:00+02:00    1\n",
       "2017-08-22 10:00:00+02:00    2\n",
       "2017-08-22 10:30:00+02:00    3\n",
       "2017-08-22 11:00:00+02:00    4\n",
       "2017-08-22 11:30:00+02:00    5\n",
       "2017-08-22 12:00:00+02:00    6\n",
       "2017-08-22 12:30:00+02:00    7\n",
       "2017-08-22 13:00:00+02:00    8\n",
       "2017-08-22 13:30:00+02:00    9\n",
       "Freq: 30T, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = s.tz_localize(tz=\"Europe/Berlin\")\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-08-22 09:00:00+02:00', '2017-08-22 09:30:00+02:00',\n",
       "               '2017-08-22 10:00:00+02:00', '2017-08-22 10:30:00+02:00',\n",
       "               '2017-08-22 11:00:00+02:00', '2017-08-22 11:30:00+02:00',\n",
       "               '2017-08-22 12:00:00+02:00', '2017-08-22 12:30:00+02:00',\n",
       "               '2017-08-22 13:00:00+02:00', '2017-08-22 13:30:00+02:00'],\n",
       "              dtype='datetime64[ns, Europe/Berlin]', freq='30T')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-08-22 09:00:00+05:30', '2017-08-22 09:30:00+05:30',\n",
       "               '2017-08-22 10:00:00+05:30', '2017-08-22 10:30:00+05:30',\n",
       "               '2017-08-22 11:00:00+05:30', '2017-08-22 11:30:00+05:30',\n",
       "               '2017-08-22 12:00:00+05:30', '2017-08-22 12:30:00+05:30',\n",
       "               '2017-08-22 13:00:00+05:30', '2017-08-22 13:30:00+05:30'],\n",
       "              dtype='datetime64[ns, Asia/Calcutta]', freq='30T')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = s.tz_localize(tz=\"Asia/Calcutta\")\n",
    "m.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017-08-22 09:00:00+05:30    0\n",
       "2017-08-22 09:30:00+05:30    1\n",
       "2017-08-22 10:00:00+05:30    2\n",
       "2017-08-22 10:30:00+05:30    3\n",
       "2017-08-22 11:00:00+05:30    4\n",
       "2017-08-22 11:30:00+05:30    5\n",
       "2017-08-22 12:00:00+05:30    6\n",
       "2017-08-22 12:30:00+05:30    7\n",
       "2017-08-22 13:00:00+05:30    8\n",
       "2017-08-22 13:30:00+05:30    9\n",
       "Freq: 30T, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017-08-22 03:30:00+00:00     NaN\n",
       "2017-08-22 04:00:00+00:00     NaN\n",
       "2017-08-22 04:30:00+00:00     NaN\n",
       "2017-08-22 05:00:00+00:00     NaN\n",
       "2017-08-22 05:30:00+00:00     NaN\n",
       "2017-08-22 06:00:00+00:00     NaN\n",
       "2017-08-22 06:30:00+00:00     NaN\n",
       "2017-08-22 07:00:00+00:00     7.0\n",
       "2017-08-22 07:30:00+00:00     9.0\n",
       "2017-08-22 08:00:00+00:00    11.0\n",
       "2017-08-22 08:30:00+00:00     NaN\n",
       "2017-08-22 09:00:00+00:00     NaN\n",
       "2017-08-22 09:30:00+00:00     NaN\n",
       "2017-08-22 10:00:00+00:00     NaN\n",
       "2017-08-22 10:30:00+00:00     NaN\n",
       "2017-08-22 11:00:00+00:00     NaN\n",
       "2017-08-22 11:30:00+00:00     NaN\n",
       "Freq: 30T, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b+m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](alignment.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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