day34.working-with-dates-and-time.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "date = pd.read_csv('orders.csv')\n",
    "time = pd.read_csv('messages.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>product_id</th>\n",
       "      <th>city_id</th>\n",
       "      <th>orders</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-10</td>\n",
       "      <td>5628</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>3646</td>\n",
       "      <td>14</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>1859</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>7292</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>4344</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  product_id  city_id  orders\n",
       "0  2019-12-10        5628       25       3\n",
       "1  2018-08-15        3646       14     157\n",
       "2  2018-10-23        1859       25       1\n",
       "3  2019-08-17        7292       25       1\n",
       "4  2019-01-06        4344       25       3"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>date</th>\n",
       "      <th>msg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-12-15 00:50:00</td>\n",
       "      <td>ищу на сегодня мужика 37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-04-29 23:40:00</td>\n",
       "      <td>ПАРЕНЬ БИ ИЩЕТ ДРУГА СЕЙЧАС!! СМС ММС 0955532826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-12-30 00:21:00</td>\n",
       "      <td>Днепр.м 43 позн.с д/ж *.о  067.16.34.576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-11-28 00:31:00</td>\n",
       "      <td>КИЕВ ИЩУ Д/Ж ДО 45 МНЕ СЕЙЧАС СКУЧНО 093 629 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-10-26 23:11:00</td>\n",
       "      <td>Зая я тебя никогда не обижу  люблю тебя!)  Даше</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  date                                                msg\n",
       "0  2013-12-15 00:50:00                           ищу на сегодня мужика 37\n",
       "1  2014-04-29 23:40:00   ПАРЕНЬ БИ ИЩЕТ ДРУГА СЕЙЧАС!! СМС ММС 0955532826\n",
       "2  2012-12-30 00:21:00           Днепр.м 43 позн.с д/ж *.о  067.16.34.576\n",
       "3  2014-11-28 00:31:00  КИЕВ ИЩУ Д/Ж ДО 45 МНЕ СЕЙЧАС СКУЧНО 093 629 9...\n",
       "4  2013-10-26 23:11:00    Зая я тебя никогда не обижу  люблю тебя!)  Даше"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 4 columns):\n",
      " #   Column      Non-Null Count  Dtype \n",
      "---  ------      --------------  ----- \n",
      " 0   date        1000 non-null   object\n",
      " 1   product_id  1000 non-null   int64 \n",
      " 2   city_id     1000 non-null   int64 \n",
      " 3   orders      1000 non-null   int64 \n",
      "dtypes: int64(3), object(1)\n",
      "memory usage: 31.4+ KB\n"
     ]
    }
   ],
   "source": [
    "date.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   date    1000 non-null   object\n",
      " 1   msg     1000 non-null   object\n",
      "dtypes: object(2)\n",
      "memory usage: 15.8+ KB\n"
     ]
    }
   ],
   "source": [
    "time.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Working with Dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting to datetime datatype\n",
    "date['date'] = pd.to_datetime(date['date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 4 columns):\n",
      " #   Column      Non-Null Count  Dtype         \n",
      "---  ------      --------------  -----         \n",
      " 0   date        1000 non-null   datetime64[ns]\n",
      " 1   product_id  1000 non-null   int64         \n",
      " 2   city_id     1000 non-null   int64         \n",
      " 3   orders      1000 non-null   int64         \n",
      "dtypes: datetime64[ns](1), int64(3)\n",
      "memory usage: 31.4 KB\n"
     ]
    }
   ],
   "source": [
    "date.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1. Extract year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>date</th>\n",
       "      <th>product_id</th>\n",
       "      <th>city_id</th>\n",
       "      <th>orders</th>\n",
       "      <th>date_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>2018-11-21</td>\n",
       "      <td>192</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>2019-10-15</td>\n",
       "      <td>6371</td>\n",
       "      <td>7</td>\n",
       "      <td>22</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>871</th>\n",
       "      <td>2018-12-26</td>\n",
       "      <td>7378</td>\n",
       "      <td>21</td>\n",
       "      <td>8</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>841</th>\n",
       "      <td>2019-11-17</td>\n",
       "      <td>5250</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>2018-10-05</td>\n",
       "      <td>1288</td>\n",
       "      <td>20</td>\n",
       "      <td>22</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date  product_id  city_id  orders  date_year\n",
       "202 2018-11-21         192       23       1       2018\n",
       "999 2019-10-15        6371        7      22       2019\n",
       "871 2018-12-26        7378       21       8       2018\n",
       "841 2019-11-17        5250        3      13       2019\n",
       "235 2018-10-05        1288       20      22       2018"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date['date_year'] = date['date'].dt.year\n",
    "\n",
    "date.sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2. Extract Month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>product_id</th>\n",
       "      <th>city_id</th>\n",
       "      <th>orders</th>\n",
       "      <th>date_year</th>\n",
       "      <th>date_month_no</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-10</td>\n",
       "      <td>5628</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>3646</td>\n",
       "      <td>14</td>\n",
       "      <td>157</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>1859</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>7292</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2019</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>4344</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  product_id  city_id  orders  date_year  date_month_no\n",
       "0 2019-12-10        5628       25       3       2019             12\n",
       "1 2018-08-15        3646       14     157       2018              8\n",
       "2 2018-10-23        1859       25       1       2018             10\n",
       "3 2019-08-17        7292       25       1       2019              8\n",
       "4 2019-01-06        4344       25       3       2019              1"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date['date_month_no'] = date['date'].dt.month\n",
    "\n",
    "date.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>product_id</th>\n",
       "      <th>city_id</th>\n",
       "      <th>orders</th>\n",
       "      <th>date_year</th>\n",
       "      <th>date_month_no</th>\n",
       "      <th>date_month_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-10</td>\n",
       "      <td>5628</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>December</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>3646</td>\n",
       "      <td>14</td>\n",
       "      <td>157</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>1859</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>October</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>7292</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2019</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>4344</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>January</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  product_id  city_id  orders  date_year  date_month_no  \\\n",
       "0 2019-12-10        5628       25       3       2019             12   \n",
       "1 2018-08-15        3646       14     157       2018              8   \n",
       "2 2018-10-23        1859       25       1       2018             10   \n",
       "3 2019-08-17        7292       25       1       2019              8   \n",
       "4 2019-01-06        4344       25       3       2019              1   \n",
       "\n",
       "  date_month_name  \n",
       "0        December  \n",
       "1          August  \n",
       "2         October  \n",
       "3          August  \n",
       "4         January  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date['date_month_name'] = date['date'].dt.month_name()\n",
    "\n",
    "date.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Extract Days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>product_id</th>\n",
       "      <th>city_id</th>\n",
       "      <th>orders</th>\n",
       "      <th>date_year</th>\n",
       "      <th>date_month_no</th>\n",
       "      <th>date_month_name</th>\n",
       "      <th>date_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-10</td>\n",
       "      <td>5628</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>December</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>3646</td>\n",
       "      <td>14</td>\n",
       "      <td>157</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>1859</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>October</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>7292</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2019</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>4344</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>January</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  product_id  city_id  orders  date_year  date_month_no  \\\n",
       "0 2019-12-10        5628       25       3       2019             12   \n",
       "1 2018-08-15        3646       14     157       2018              8   \n",
       "2 2018-10-23        1859       25       1       2018             10   \n",
       "3 2019-08-17        7292       25       1       2019              8   \n",
       "4 2019-01-06        4344       25       3       2019              1   \n",
       "\n",
       "  date_month_name  date_day  \n",
       "0        December        10  \n",
       "1          August        15  \n",
       "2         October        23  \n",
       "3          August        17  \n",
       "4         January         6  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date['date_day'] = date['date'].dt.day\n",
    "\n",
    "date.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>product_id</th>\n",
       "      <th>city_id</th>\n",
       "      <th>orders</th>\n",
       "      <th>date_year</th>\n",
       "      <th>date_month_no</th>\n",
       "      <th>date_month_name</th>\n",
       "      <th>date_day</th>\n",
       "      <th>date_dow</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-10</td>\n",
       "      <td>5628</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>December</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>3646</td>\n",
       "      <td>14</td>\n",
       "      <td>157</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>1859</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>October</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>7292</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2019</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>4344</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>January</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  product_id  city_id  orders  date_year  date_month_no  \\\n",
       "0 2019-12-10        5628       25       3       2019             12   \n",
       "1 2018-08-15        3646       14     157       2018              8   \n",
       "2 2018-10-23        1859       25       1       2018             10   \n",
       "3 2019-08-17        7292       25       1       2019              8   \n",
       "4 2019-01-06        4344       25       3       2019              1   \n",
       "\n",
       "  date_month_name  date_day  date_dow  \n",
       "0        December        10         1  \n",
       "1          August        15         2  \n",
       "2         October        23         1  \n",
       "3          August        17         5  \n",
       "4         January         6         6  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# day of week\n",
    "date['date_dow'] = date['date'].dt.dayofweek\n",
    "\n",
    "date.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>date_month_name</th>\n",
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       "      <td>2019-12-10</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>December</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>October</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>2019</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>January</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  date_year  date_month_no date_month_name  date_day  date_dow  \\\n",
       "0 2019-12-10       2019             12        December        10         1   \n",
       "1 2018-08-15       2018              8          August        15         2   \n",
       "2 2018-10-23       2018             10         October        23         1   \n",
       "3 2019-08-17       2019              8          August        17         5   \n",
       "4 2019-01-06       2019              1         January         6         6   \n",
       "\n",
       "  date_dow_name  \n",
       "0       Tuesday  \n",
       "1     Wednesday  \n",
       "2       Tuesday  \n",
       "3      Saturday  \n",
       "4        Sunday  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# day of week - name\n",
    "\n",
    "date['date_dow_name'] = date['date'].dt.day_name()\n",
    "\n",
    "date.drop(columns=['product_id','city_id','orders']).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>date_year</th>\n",
       "      <th>date_month_no</th>\n",
       "      <th>date_month_name</th>\n",
       "      <th>date_day</th>\n",
       "      <th>date_dow</th>\n",
       "      <th>date_dow_name</th>\n",
       "      <th>date_is_weekend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-10</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>December</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>October</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>2019</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>January</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  date_year  date_month_no date_month_name  date_day  date_dow  \\\n",
       "0 2019-12-10       2019             12        December        10         1   \n",
       "1 2018-08-15       2018              8          August        15         2   \n",
       "2 2018-10-23       2018             10         October        23         1   \n",
       "3 2019-08-17       2019              8          August        17         5   \n",
       "4 2019-01-06       2019              1         January         6         6   \n",
       "\n",
       "  date_dow_name  date_is_weekend  \n",
       "0       Tuesday                0  \n",
       "1     Wednesday                0  \n",
       "2       Tuesday                0  \n",
       "3      Saturday                1  \n",
       "4        Sunday                1  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# is weekend?\n",
    "\n",
    "date['date_is_weekend'] = np.where(date['date_dow_name'].isin(['Sunday', 'Saturday']), 1,0)\n",
    "\n",
    "date.drop(columns=['product_id','city_id','orders']).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Extract week of the year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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>date</th>\n",
       "      <th>date_year</th>\n",
       "      <th>date_month_no</th>\n",
       "      <th>date_month_name</th>\n",
       "      <th>date_day</th>\n",
       "      <th>date_dow</th>\n",
       "      <th>date_dow_name</th>\n",
       "      <th>date_is_weekend</th>\n",
       "      <th>date_week</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-10</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>December</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>October</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>2019</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>January</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  date_year  date_month_no date_month_name  date_day  date_dow  \\\n",
       "0 2019-12-10       2019             12        December        10         1   \n",
       "1 2018-08-15       2018              8          August        15         2   \n",
       "2 2018-10-23       2018             10         October        23         1   \n",
       "3 2019-08-17       2019              8          August        17         5   \n",
       "4 2019-01-06       2019              1         January         6         6   \n",
       "\n",
       "  date_dow_name  date_is_weekend  date_week  \n",
       "0       Tuesday                0         50  \n",
       "1     Wednesday                0         33  \n",
       "2       Tuesday                0         43  \n",
       "3      Saturday                1         33  \n",
       "4        Sunday                1          1  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date['date_week'] = date['date'].dt.week\n",
    "\n",
    "date.drop(columns=['product_id','city_id','orders']).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Extract Quarter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>date_dow_name</th>\n",
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       "      <th>date_week</th>\n",
       "      <th>quarter</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-10</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>December</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>October</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>2019</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>January</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  date_year  date_month_no date_month_name  date_day  date_dow  \\\n",
       "0 2019-12-10       2019             12        December        10         1   \n",
       "1 2018-08-15       2018              8          August        15         2   \n",
       "2 2018-10-23       2018             10         October        23         1   \n",
       "3 2019-08-17       2019              8          August        17         5   \n",
       "4 2019-01-06       2019              1         January         6         6   \n",
       "\n",
       "  date_dow_name  date_is_weekend  date_week  quarter  \n",
       "0       Tuesday                0         50        4  \n",
       "1     Wednesday                0         33        3  \n",
       "2       Tuesday                0         43        4  \n",
       "3      Saturday                1         33        3  \n",
       "4        Sunday                1          1        1  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date['quarter'] = date['date'].dt.quarter\n",
    "\n",
    "date.drop(columns=['product_id','city_id','orders']).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Extract Semester"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "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>date</th>\n",
       "      <th>date_year</th>\n",
       "      <th>date_month_no</th>\n",
       "      <th>date_month_name</th>\n",
       "      <th>date_day</th>\n",
       "      <th>date_dow</th>\n",
       "      <th>date_dow_name</th>\n",
       "      <th>date_is_weekend</th>\n",
       "      <th>date_week</th>\n",
       "      <th>quarter</th>\n",
       "      <th>semester</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-10</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>December</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-15</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-23</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>October</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-17</td>\n",
       "      <td>2019</td>\n",
       "      <td>8</td>\n",
       "      <td>August</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>January</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  date_year  date_month_no date_month_name  date_day  date_dow  \\\n",
       "0 2019-12-10       2019             12        December        10         1   \n",
       "1 2018-08-15       2018              8          August        15         2   \n",
       "2 2018-10-23       2018             10         October        23         1   \n",
       "3 2019-08-17       2019              8          August        17         5   \n",
       "4 2019-01-06       2019              1         January         6         6   \n",
       "\n",
       "  date_dow_name  date_is_weekend  date_week  quarter  semester  \n",
       "0       Tuesday                0         50        4         2  \n",
       "1     Wednesday                0         33        3         2  \n",
       "2       Tuesday                0         43        4         2  \n",
       "3      Saturday                1         33        3         2  \n",
       "4        Sunday                1          1        1         1  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date['semester'] = np.where(date['quarter'].isin([1,2]), 1, 2)\n",
    "\n",
    "date.drop(columns=['product_id','city_id','orders']).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Extract Time elapsed between dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2021, 4, 21, 16, 2, 16, 791379)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import datetime\n",
    "\n",
    "today = datetime.datetime.today()\n",
    "\n",
    "today"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     498 days 16:02:16.791379\n",
       "1     980 days 16:02:16.791379\n",
       "2     911 days 16:02:16.791379\n",
       "3     613 days 16:02:16.791379\n",
       "4     836 days 16:02:16.791379\n",
       "                ...           \n",
       "995   926 days 16:02:16.791379\n",
       "996   867 days 16:02:16.791379\n",
       "997   715 days 16:02:16.791379\n",
       "998   780 days 16:02:16.791379\n",
       "999   554 days 16:02:16.791379\n",
       "Name: date, Length: 1000, dtype: timedelta64[ns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "today - date['date']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      498\n",
       "1      980\n",
       "2      911\n",
       "3      613\n",
       "4      836\n",
       "      ... \n",
       "995    926\n",
       "996    867\n",
       "997    715\n",
       "998    780\n",
       "999    554\n",
       "Name: date, Length: 1000, dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(today - date['date']).dt.days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      16.0\n",
       "1      32.0\n",
       "2      30.0\n",
       "3      20.0\n",
       "4      27.0\n",
       "       ... \n",
       "995    30.0\n",
       "996    29.0\n",
       "997    24.0\n",
       "998    26.0\n",
       "999    18.0\n",
       "Name: date, Length: 1000, dtype: float64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Months passed\n",
    "\n",
    "np.round((today -date['date']) / np.timedelta64(1, 'M'),0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   date    1000 non-null   object\n",
      " 1   msg     1000 non-null   object\n",
      "dtypes: object(2)\n",
      "memory usage: 15.8+ KB\n"
     ]
    }
   ],
   "source": [
    "time.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting to datetime datatype\n",
    "time['date'] = pd.to_datetime(time['date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype         \n",
      "---  ------  --------------  -----         \n",
      " 0   date    1000 non-null   datetime64[ns]\n",
      " 1   msg     1000 non-null   object        \n",
      "dtypes: datetime64[ns](1), object(1)\n",
      "memory usage: 15.8+ KB\n"
     ]
    }
   ],
   "source": [
    "time.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>msg</th>\n",
       "      <th>hour</th>\n",
       "      <th>min</th>\n",
       "      <th>sec</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-12-15 00:50:00</td>\n",
       "      <td>ищу на сегодня мужика 37</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-04-29 23:40:00</td>\n",
       "      <td>ПАРЕНЬ БИ ИЩЕТ ДРУГА СЕЙЧАС!! СМС ММС 0955532826</td>\n",
       "      <td>23</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-12-30 00:21:00</td>\n",
       "      <td>Днепр.м 43 позн.с д/ж *.о  067.16.34.576</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-11-28 00:31:00</td>\n",
       "      <td>КИЕВ ИЩУ Д/Ж ДО 45 МНЕ СЕЙЧАС СКУЧНО 093 629 9...</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-10-26 23:11:00</td>\n",
       "      <td>Зая я тебя никогда не обижу  люблю тебя!)  Даше</td>\n",
       "      <td>23</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 date                                                msg  \\\n",
       "0 2013-12-15 00:50:00                           ищу на сегодня мужика 37   \n",
       "1 2014-04-29 23:40:00   ПАРЕНЬ БИ ИЩЕТ ДРУГА СЕЙЧАС!! СМС ММС 0955532826   \n",
       "2 2012-12-30 00:21:00           Днепр.м 43 позн.с д/ж *.о  067.16.34.576   \n",
       "3 2014-11-28 00:31:00  КИЕВ ИЩУ Д/Ж ДО 45 МНЕ СЕЙЧАС СКУЧНО 093 629 9...   \n",
       "4 2013-10-26 23:11:00    Зая я тебя никогда не обижу  люблю тебя!)  Даше   \n",
       "\n",
       "   hour  min  sec  \n",
       "0     0   50    0  \n",
       "1    23   40    0  \n",
       "2     0   21    0  \n",
       "3     0   31    0  \n",
       "4    23   11    0  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time['hour'] = time['date'].dt.hour\n",
    "time['min'] = time['date'].dt.minute\n",
    "time['sec'] = time['date'].dt.second\n",
    "\n",
    "time.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Extract Time part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "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>date</th>\n",
       "      <th>msg</th>\n",
       "      <th>hour</th>\n",
       "      <th>min</th>\n",
       "      <th>sec</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-12-15 00:50:00</td>\n",
       "      <td>ищу на сегодня мужика 37</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>00:50:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-04-29 23:40:00</td>\n",
       "      <td>ПАРЕНЬ БИ ИЩЕТ ДРУГА СЕЙЧАС!! СМС ММС 0955532826</td>\n",
       "      <td>23</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>23:40:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-12-30 00:21:00</td>\n",
       "      <td>Днепр.м 43 позн.с д/ж *.о  067.16.34.576</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>00:21:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-11-28 00:31:00</td>\n",
       "      <td>КИЕВ ИЩУ Д/Ж ДО 45 МНЕ СЕЙЧАС СКУЧНО 093 629 9...</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>00:31:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-10-26 23:11:00</td>\n",
       "      <td>Зая я тебя никогда не обижу  люблю тебя!)  Даше</td>\n",
       "      <td>23</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>23:11:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 date                                                msg  \\\n",
       "0 2013-12-15 00:50:00                           ищу на сегодня мужика 37   \n",
       "1 2014-04-29 23:40:00   ПАРЕНЬ БИ ИЩЕТ ДРУГА СЕЙЧАС!! СМС ММС 0955532826   \n",
       "2 2012-12-30 00:21:00           Днепр.м 43 позн.с д/ж *.о  067.16.34.576   \n",
       "3 2014-11-28 00:31:00  КИЕВ ИЩУ Д/Ж ДО 45 МНЕ СЕЙЧАС СКУЧНО 093 629 9...   \n",
       "4 2013-10-26 23:11:00    Зая я тебя никогда не обижу  люблю тебя!)  Даше   \n",
       "\n",
       "   hour  min  sec      time  \n",
       "0     0   50    0  00:50:00  \n",
       "1    23   40    0  23:40:00  \n",
       "2     0   21    0  00:21:00  \n",
       "3     0   31    0  00:31:00  \n",
       "4    23   11    0  23:11:00  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time['time'] = time['date'].dt.time\n",
    "\n",
    "time.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Time difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     2684 days 15:12:16.791379\n",
       "1     2548 days 16:22:16.791379\n",
       "2     3034 days 15:41:16.791379\n",
       "3     2336 days 15:31:16.791379\n",
       "4     2733 days 16:51:16.791379\n",
       "                 ...           \n",
       "995   3323 days 15:12:16.791379\n",
       "996   2644 days 16:48:16.791379\n",
       "997   3109 days 16:25:16.791379\n",
       "998   3225 days 16:28:16.791379\n",
       "999   2497 days 16:37:16.791379\n",
       "Name: date, Length: 1000, dtype: timedelta64[ns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "today - time['date']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      2.319523e+08\n",
       "1      2.202061e+08\n",
       "2      2.621941e+08\n",
       "3      2.018863e+08\n",
       "4      2.361919e+08\n",
       "           ...     \n",
       "995    2.871619e+08\n",
       "996    2.285021e+08\n",
       "997    2.686767e+08\n",
       "998    2.786993e+08\n",
       "999    2.158006e+08\n",
       "Name: date, Length: 1000, dtype: float64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# in seconds\n",
    "\n",
    "(today - time['date'])/np.timedelta64(1,'s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      3.865872e+06\n",
       "1      3.670102e+06\n",
       "2      4.369901e+06\n",
       "3      3.364771e+06\n",
       "4      3.936531e+06\n",
       "           ...     \n",
       "995    4.786032e+06\n",
       "996    3.808368e+06\n",
       "997    4.477945e+06\n",
       "998    4.644988e+06\n",
       "999    3.596677e+06\n",
       "Name: date, Length: 1000, dtype: float64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# in minutes\n",
    "\n",
    "(today - time['date'])/np.timedelta64(1,'m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      64431.204664\n",
       "1      61168.371331\n",
       "2      72831.687998\n",
       "3      56079.521331\n",
       "4      65608.854664\n",
       "           ...     \n",
       "995    79767.204664\n",
       "996    63472.804664\n",
       "997    74632.421331\n",
       "998    77416.471331\n",
       "999    59944.621331\n",
       "Name: date, Length: 1000, dtype: float64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# in hours\n",
    "\n",
    "(today - time['date'])/np.timedelta64(1,'h')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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