{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T05:20:26.267026Z",
     "start_time": "2021-06-29T05:20:26.259203Z"
    }
   },
   "outputs": [],
   "source": [
    "from datetime import datetime, date\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T05:10:11.339694Z",
     "start_time": "2021-06-29T05:10:11.315592Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.3.2'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## inline date elements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T05:20:52.097514Z",
     "start_time": "2021-06-29T05:20:52.067371Z"
    }
   },
   "outputs": [],
   "source": [
    "from datetime import date\n",
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame({\n",
    "    \"name\":          [\"alice\",        \"bob\",            \"charlie\"],\n",
    "    \"date_of_birth\": [date(1999,4,1), date(2001,12,15), date(1985,4,24)] \n",
    "})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## pandas timestamp now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T05:10:12.191183Z",
     "start_time": "2021-06-29T05:10:12.118037Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>alice</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>bob</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>charlie</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>david</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name  age\n",
       "0    alice   12\n",
       "1      bob   43\n",
       "2  charlie   22\n",
       "3    david   34"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({\n",
    "    \"name\":[\"alice\",\"bob\",\"charlie\", \"david\"],\n",
    "    \"age\":[12,43,22,34]\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T05:10:31.467561Z",
     "start_time": "2021-06-29T05:10:31.445164Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>alice</td>\n",
       "      <td>12</td>\n",
       "      <td>2022-05-05 00:46:43.273572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>bob</td>\n",
       "      <td>43</td>\n",
       "      <td>2022-05-05 00:46:43.273572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>charlie</td>\n",
       "      <td>22</td>\n",
       "      <td>2022-05-05 00:46:43.273572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>david</td>\n",
       "      <td>34</td>\n",
       "      <td>2022-05-05 00:46:43.273572</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name  age                       time\n",
       "0    alice   12 2022-05-05 00:46:43.273572\n",
       "1      bob   43 2022-05-05 00:46:43.273572\n",
       "2  charlie   22 2022-05-05 00:46:43.273572\n",
       "3    david   34 2022-05-05 00:46:43.273572"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"time\"] = pd.Timestamp(datetime.now())\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## timestamp to string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T05:14:12.468050Z",
     "start_time": "2021-06-29T05:14:12.439949Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>timestamp_col</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>alice</td>\n",
       "      <td>12</td>\n",
       "      <td>2022-05-05 00:46:43.285148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>bob</td>\n",
       "      <td>43</td>\n",
       "      <td>2022-05-05 00:46:43.285148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>charlie</td>\n",
       "      <td>22</td>\n",
       "      <td>2022-05-05 00:46:43.285148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>david</td>\n",
       "      <td>34</td>\n",
       "      <td>2022-05-05 00:46:43.285148</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name  age              timestamp_col\n",
       "0    alice   12 2022-05-05 00:46:43.285148\n",
       "1      bob   43 2022-05-05 00:46:43.285148\n",
       "2  charlie   22 2022-05-05 00:46:43.285148\n",
       "3    david   34 2022-05-05 00:46:43.285148"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({\n",
    "    \"name\":[\"alice\",\"bob\",\"charlie\", \"david\"],\n",
    "    \"age\":[12,43,22,34]\n",
    "})\n",
    "\n",
    "df[\"timestamp_col\"] = pd.Timestamp(datetime.now())\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T05:14:12.704240Z",
     "start_time": "2021-06-29T05:14:12.583792Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>name</th>\n",
       "      <th>age</th>\n",
       "      <th>timestamp_col</th>\n",
       "      <th>formatted_col</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>alice</td>\n",
       "      <td>12</td>\n",
       "      <td>2022-05-05 00:46:43.285148</td>\n",
       "      <td>05-05-2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>bob</td>\n",
       "      <td>43</td>\n",
       "      <td>2022-05-05 00:46:43.285148</td>\n",
       "      <td>05-05-2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>charlie</td>\n",
       "      <td>22</td>\n",
       "      <td>2022-05-05 00:46:43.285148</td>\n",
       "      <td>05-05-2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>david</td>\n",
       "      <td>34</td>\n",
       "      <td>2022-05-05 00:46:43.285148</td>\n",
       "      <td>05-05-2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name  age              timestamp_col formatted_col\n",
       "0    alice   12 2022-05-05 00:46:43.285148    05-05-2022\n",
       "1      bob   43 2022-05-05 00:46:43.285148    05-05-2022\n",
       "2  charlie   22 2022-05-05 00:46:43.285148    05-05-2022\n",
       "3    david   34 2022-05-05 00:46:43.285148    05-05-2022"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"formatted_col\"] = df[\"timestamp_col\"].map(lambda ts: ts.strftime(\"%d-%m-%Y\"))\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## group by year\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\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>year_of_birth</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1998</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1999</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2001</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  year_of_birth  count\n",
       "0          1998      1\n",
       "1          1999      2\n",
       "2          2001      1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame({\n",
    "    'name': ['alice','bob','charlie', 'david'],\n",
    "    'date_of_birth': ['2001-05-27','1999-02-16','1998-09-25', '1999-01-01']\n",
    "})\n",
    "\n",
    "df['date_of_birth'] = pd.to_datetime(df['date_of_birth'])\n",
    "\n",
    "# step 1: create a 'year' column\n",
    "df['year_of_birth'] = df['date_of_birth'].map(lambda dt: dt.strftime('%Y'))\n",
    "\n",
    "# step 2: group by the created columns\n",
    "grouped_df = df.groupby('year_of_birth').size()\n",
    "\n",
    "grouped_df.to_frame('count').reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## group by start of week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\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>purchase_start_of_week</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2001-01-15</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2001-01-22</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2001-01-29</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  purchase_start_of_week  count\n",
       "0             2001-01-15      3\n",
       "1             2001-01-22      2\n",
       "2             2001-01-29      1"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datetime import timedelta\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame({\n",
    "    'item':          ['a',          'b',         'c',         'd',          'e',          'f'],\n",
    "    'purchase_date': ['2001-01-15', '2001-01-18','2001-01-21','2001-01-24', '2001-01-27', '2001-01-30']\n",
    "})\n",
    "\n",
    "# convert values to datetime type\n",
    "df['purchase_date'] = pd.to_datetime(df['purchase_date'])\n",
    "\n",
    "\n",
    "df['purchase_start_of_week'] = df['purchase_date'].map(lambda dt: dt - timedelta(days=dt.weekday()))\n",
    "\n",
    "grouped_df = df.groupby('purchase_start_of_week').size()\n",
    "\n",
    "grouped_df.to_frame('count').reset_index()"
   ]
  }
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