Working with Dates and Times.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "db677d18",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7355ad54",
   "metadata": {},
   "source": [
    "# review of Python's datetime module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c2e80e8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(1984, 12, 21)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.date(1984, 12, 21)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "483842fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1984-12-21'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str(dt.date(1984, 12, 21))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e28d7abc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "birthday = dt.date(1984, 12, 21)\n",
    "birthday.day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "98877184",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "birthday.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a6a1d01d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1984"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "birthday.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "efe4b34e",
   "metadata": {},
   "outputs": [],
   "source": [
    "someday = dt.datetime(1984, 12, 21, 23, 49, 32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3bf373e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "someday.day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6aefb88d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "someday.hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6dbb54e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "someday.second"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "373b24e3",
   "metadata": {},
   "source": [
    "# pandas Timestamp Object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "99c37265",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2015-09-12 00:00:00')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Timestamp(\"2015-09-12\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0c3322d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2015-09-12 00:00:00')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Timestamp(\"09/12/15\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4c1aae3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2015-02-12 12:34:00')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Timestamp(\"2/12/2015 12:34\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5bb1d309",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('1984-12-21 23:49:32')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Timestamp(dt.datetime(1984, 12, 21, 23, 49, 32))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3be953a2",
   "metadata": {},
   "source": [
    "# pandas DateTimeIndex "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "352857a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2016-01-01', '2016-01-02', '2016-01-03'], dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates = [\"2016/01/01\", \"2016/01/02\", \"2016/01/03\"]\n",
    "pd.DatetimeIndex(dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7026e34c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2016-01-01    100\n",
       "2016-01-02    200\n",
       "2016-01-03    300\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates = pd.DatetimeIndex(dates)\n",
    "series_value = [100, 200, 300]\n",
    "pd.Series(index = dates, data = series_value)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8569bf19",
   "metadata": {},
   "source": [
    "# pd.to_datetime()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7911dbde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2016-01-01', '2016-01-02', '2016-01-03'], dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_datetime(dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "be04b9bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2016-01-01\n",
       "1   2016-01-02\n",
       "2   2016-01-03\n",
       "dtype: datetime64[ns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4e7e74b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2016-01-01\n",
       "1   2016-01-02\n",
       "2   2016-01-03\n",
       "dtype: datetime64[ns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_datetime(pd.Series(dates))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "36a5a60b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2016-01-01', '2016-01-02', '2016-01-03'], dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "30de22cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "mixedData = [\"2016/01/01\", \"Hero\", \"2016/01/03\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "10b4449f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2016-01-01', 'NaT', '2016-01-03'], dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_datetime(mixedData, errors = \"coerce\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0640bae2",
   "metadata": {},
   "source": [
    "# pd.date_range()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "971e30af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2016-01-01', '2016-01-03', '2016-01-05', '2016-01-07',\n",
       "               '2016-01-09'],\n",
       "              dtype='datetime64[ns]', freq='2D')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range(\"2016-01-01\", \"2016-01-10\", freq = \"2D\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d7dc3362",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2016-01-01', '2016-01-03', '2016-01-05', '2016-01-07',\n",
       "               '2016-01-09', '2016-01-11', '2016-01-13', '2016-01-15',\n",
       "               '2016-01-17', '2016-01-19', '2016-01-21', '2016-01-23',\n",
       "               '2016-01-25', '2016-01-27', '2016-01-29', '2016-01-31',\n",
       "               '2016-02-02', '2016-02-04', '2016-02-06', '2016-02-08'],\n",
       "              dtype='datetime64[ns]', freq='2D')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range(start = \"2016-01-01\", periods = 20, freq = \"2D\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "28810b67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2015-11-24', '2015-11-26', '2015-11-28', '2015-11-30',\n",
       "               '2015-12-02', '2015-12-04', '2015-12-06', '2015-12-08',\n",
       "               '2015-12-10', '2015-12-12', '2015-12-14', '2015-12-16',\n",
       "               '2015-12-18', '2015-12-20', '2015-12-22', '2015-12-24',\n",
       "               '2015-12-26', '2015-12-28', '2015-12-30', '2016-01-01'],\n",
       "              dtype='datetime64[ns]', freq='2D')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range(end = \"2016-01-01\", periods = 20, freq = \"2D\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a29d8c8",
   "metadata": {},
   "source": [
    "# dt accessor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e3834e5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2016-01-01', '2016-01-25', '2016-02-18', '2016-03-13',\n",
       "               '2016-04-06', '2016-04-30', '2016-05-24', '2016-06-17',\n",
       "               '2016-07-11', '2016-08-04',\n",
       "               ...\n",
       "               '2025-05-25', '2025-06-18', '2025-07-12', '2025-08-05',\n",
       "               '2025-08-29', '2025-09-22', '2025-10-16', '2025-11-09',\n",
       "               '2025-12-03', '2025-12-27'],\n",
       "              dtype='datetime64[ns]', length=153, freq='24D')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range(start = \"2016-01-01\", end = \"2026-01-10\", freq = \"24D\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4a94791f",
   "metadata": {},
   "outputs": [],
   "source": [
    "bunch_of_dates = pd.date_range(start = \"2016-01-01\", end = \"2026-01-10\", freq = \"24D\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "46294a8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "s = pd.Series(bunch_of_dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "43e5f96c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2016-01-01\n",
       "1   2016-01-25\n",
       "2   2016-02-18\n",
       "dtype: datetime64[ns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d0846812",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1       1\n",
       "2       2\n",
       "3       3\n",
       "4       4\n",
       "       ..\n",
       "148     9\n",
       "149    10\n",
       "150    11\n",
       "151    12\n",
       "152    12\n",
       "Length: 153, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.dt.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "11bb9dd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      4\n",
       "1      0\n",
       "2      3\n",
       "3      6\n",
       "4      2\n",
       "      ..\n",
       "148    0\n",
       "149    3\n",
       "150    6\n",
       "151    2\n",
       "152    5\n",
       "Length: 153, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.dt.weekday"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4337c848",
   "metadata": {},
   "source": [
    "# pandas_datareader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "015f79c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas_datareader import data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "229af6a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
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       "    <tr>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>31.100000</td>\n",
       "      <td>30.590000</td>\n",
       "      <td>30.620001</td>\n",
       "      <td>30.950001</td>\n",
       "      <td>38409100.0</td>\n",
       "      <td>23.683075</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>31.100000</td>\n",
       "      <td>30.639999</td>\n",
       "      <td>30.850000</td>\n",
       "      <td>30.959999</td>\n",
       "      <td>49749600.0</td>\n",
       "      <td>23.690722</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>31.080000</td>\n",
       "      <td>30.520000</td>\n",
       "      <td>30.879999</td>\n",
       "      <td>30.770000</td>\n",
       "      <td>58182400.0</td>\n",
       "      <td>23.545328</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>30.700001</td>\n",
       "      <td>30.190001</td>\n",
       "      <td>30.629999</td>\n",
       "      <td>30.450001</td>\n",
       "      <td>50559700.0</td>\n",
       "      <td>23.300468</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>30.879999</td>\n",
       "      <td>30.240000</td>\n",
       "      <td>30.280001</td>\n",
       "      <td>30.660000</td>\n",
       "      <td>51197400.0</td>\n",
       "      <td>23.461159</td>\n",
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       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <th>2020-12-24</th>\n",
       "      <td>223.610001</td>\n",
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       "      <td>221.419998</td>\n",
       "      <td>222.750000</td>\n",
       "      <td>10550600.0</td>\n",
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       "    <tr>\n",
       "      <th>2020-12-28</th>\n",
       "      <td>226.029999</td>\n",
       "      <td>223.020004</td>\n",
       "      <td>224.449997</td>\n",
       "      <td>224.960007</td>\n",
       "      <td>17933500.0</td>\n",
       "      <td>221.019012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-29</th>\n",
       "      <td>227.179993</td>\n",
       "      <td>223.580002</td>\n",
       "      <td>226.309998</td>\n",
       "      <td>224.149994</td>\n",
       "      <td>17403200.0</td>\n",
       "      <td>220.223206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>225.630005</td>\n",
       "      <td>221.470001</td>\n",
       "      <td>225.229996</td>\n",
       "      <td>221.679993</td>\n",
       "      <td>20272300.0</td>\n",
       "      <td>217.796448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>223.000000</td>\n",
       "      <td>219.679993</td>\n",
       "      <td>221.699997</td>\n",
       "      <td>222.419998</td>\n",
       "      <td>20942100.0</td>\n",
       "      <td>218.523499</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2769 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  High         Low        Open       Close      Volume  \\\n",
       "Date                                                                     \n",
       "2010-01-04   31.100000   30.590000   30.620001   30.950001  38409100.0   \n",
       "2010-01-05   31.100000   30.639999   30.850000   30.959999  49749600.0   \n",
       "2010-01-06   31.080000   30.520000   30.879999   30.770000  58182400.0   \n",
       "2010-01-07   30.700001   30.190001   30.629999   30.450001  50559700.0   \n",
       "2010-01-08   30.879999   30.240000   30.280001   30.660000  51197400.0   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2020-12-24  223.610001  221.199997  221.419998  222.750000  10550600.0   \n",
       "2020-12-28  226.029999  223.020004  224.449997  224.960007  17933500.0   \n",
       "2020-12-29  227.179993  223.580002  226.309998  224.149994  17403200.0   \n",
       "2020-12-30  225.630005  221.470001  225.229996  221.679993  20272300.0   \n",
       "2020-12-31  223.000000  219.679993  221.699997  222.419998  20942100.0   \n",
       "\n",
       "             Adj Close  \n",
       "Date                    \n",
       "2010-01-04   23.683075  \n",
       "2010-01-05   23.690722  \n",
       "2010-01-06   23.545328  \n",
       "2010-01-07   23.300468  \n",
       "2010-01-08   23.461159  \n",
       "...                ...  \n",
       "2020-12-24  218.847702  \n",
       "2020-12-28  221.019012  \n",
       "2020-12-29  220.223206  \n",
       "2020-12-30  217.796448  \n",
       "2020-12-31  218.523499  \n",
       "\n",
       "[2769 rows x 6 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.DataReader(name = \"MSFT\", data_source = \"yahoo\", start = \"2010-01-01\", end = \"2020-12-31\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "90965484",
   "metadata": {},
   "outputs": [],
   "source": [
    "stock = data.DataReader(name = \"MSFT\", data_source = \"yahoo\", start = \"2010-01-01\", end = \"2020-12-31\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8fd46f46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3.11000004e+01, 3.05900002e+01, 3.06200008e+01, 3.09500008e+01,\n",
       "        3.84091000e+07, 2.36830750e+01],\n",
       "       [3.11000004e+01, 3.06399994e+01, 3.08500004e+01, 3.09599991e+01,\n",
       "        4.97496000e+07, 2.36907234e+01],\n",
       "       [3.10799999e+01, 3.05200005e+01, 3.08799992e+01, 3.07700005e+01,\n",
       "        5.81824000e+07, 2.35453339e+01],\n",
       "       ...,\n",
       "       [2.27179993e+02, 2.23580002e+02, 2.26309998e+02, 2.24149994e+02,\n",
       "        1.74032000e+07, 2.20223206e+02],\n",
       "       [2.25630005e+02, 2.21470001e+02, 2.25229996e+02, 2.21679993e+02,\n",
       "        2.02723000e+07, 2.17796463e+02],\n",
       "       [2.23000000e+02, 2.19679993e+02, 2.21699997e+02, 2.22419998e+02,\n",
       "        2.09421000e+07, 2.18523514e+02]])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "4972cb06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-04', '2010-01-05', '2010-01-06', '2010-01-07',\n",
       "               '2010-01-08', '2010-01-11', '2010-01-12', '2010-01-13',\n",
       "               '2010-01-14', '2010-01-15',\n",
       "               ...\n",
       "               '2020-12-17', '2020-12-18', '2020-12-21', '2020-12-22',\n",
       "               '2020-12-23', '2020-12-24', '2020-12-28', '2020-12-29',\n",
       "               '2020-12-30', '2020-12-31'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2769, freq=None)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "960f43fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['High', 'Low', 'Open', 'Close', 'Volume', 'Adj Close'], dtype='object')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "dcdbd8fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[DatetimeIndex(['2010-01-04', '2010-01-05', '2010-01-06', '2010-01-07',\n",
       "                '2010-01-08', '2010-01-11', '2010-01-12', '2010-01-13',\n",
       "                '2010-01-14', '2010-01-15',\n",
       "                ...\n",
       "                '2020-12-17', '2020-12-18', '2020-12-21', '2020-12-22',\n",
       "                '2020-12-23', '2020-12-24', '2020-12-28', '2020-12-29',\n",
       "                '2020-12-30', '2020-12-31'],\n",
       "               dtype='datetime64[ns]', name='Date', length=2769, freq=None),\n",
       " Index(['High', 'Low', 'Open', 'Close', 'Volume', 'Adj Close'], dtype='object')]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "f95a8473",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "High         float64\n",
       "Low          float64\n",
       "Open         float64\n",
       "Close        float64\n",
       "Volume       float64\n",
       "Adj Close    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "3bfd93ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(stock)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "fd999650",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "High         3.110000e+01\n",
       "Low          3.059000e+01\n",
       "Open         3.062000e+01\n",
       "Close        3.095000e+01\n",
       "Volume       3.840910e+07\n",
       "Adj Close    2.368307e+01\n",
       "Name: 2010-01-04 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.loc[\"2010-01-04\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "db7576c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "High         3.110000e+01\n",
       "Low          3.059000e+01\n",
       "Open         3.062000e+01\n",
       "Close        3.095000e+01\n",
       "Volume       3.840910e+07\n",
       "Adj Close    2.368307e+01\n",
       "Name: 2010-01-04 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.loc[pd.to_datetime(\"2010-01-04\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "a00cd169",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "High         3.110000e+01\n",
       "Low          3.059000e+01\n",
       "Open         3.062000e+01\n",
       "Close        3.095000e+01\n",
       "Volume       3.840910e+07\n",
       "Adj Close    2.368307e+01\n",
       "Name: 2010-01-04 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.loc[pd.Timestamp(\"2010-01-04\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c61e71af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-04', '2010-01-05', '2010-01-06', '2010-01-07',\n",
       "               '2010-01-08', '2010-01-11', '2010-01-12', '2010-01-13',\n",
       "               '2010-01-14', '2010-01-15',\n",
       "               ...\n",
       "               '2020-12-17', '2020-12-18', '2020-12-21', '2020-12-22',\n",
       "               '2020-12-23', '2020-12-24', '2020-12-28', '2020-12-29',\n",
       "               '2020-12-30', '2020-12-31'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2769, freq=None)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "71d36571",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-09', '2010-01-10', '2010-01-11', '2010-01-12',\n",
       "               '2010-01-13', '2010-01-16', '2010-01-17', '2010-01-18',\n",
       "               '2010-01-19', '2010-01-20',\n",
       "               ...\n",
       "               '2020-12-22', '2020-12-23', '2020-12-26', '2020-12-27',\n",
       "               '2020-12-28', '2020-12-29', '2021-01-02', '2021-01-03',\n",
       "               '2021-01-04', '2021-01-05'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2769, freq=None)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.index + pd.DateOffset(days = 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4364baa4",
   "metadata": {},
   "source": [
    "# Timeseries Offsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "8e4014c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-31', '2010-01-31', '2010-01-31', '2010-01-31',\n",
       "               '2010-01-31', '2010-01-31', '2010-01-31', '2010-01-31',\n",
       "               '2010-01-31', '2010-01-31',\n",
       "               ...\n",
       "               '2020-12-31', '2020-12-31', '2020-12-31', '2020-12-31',\n",
       "               '2020-12-31', '2020-12-31', '2020-12-31', '2020-12-31',\n",
       "               '2020-12-31', '2021-01-31'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2769, freq=None)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.index + pd.tseries.offsets.MonthEnd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "4d0dea16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2009-12-31', '2009-12-31', '2009-12-31', '2009-12-31',\n",
       "               '2009-12-31', '2009-12-31', '2009-12-31', '2009-12-31',\n",
       "               '2009-12-31', '2009-12-31',\n",
       "               ...\n",
       "               '2020-11-30', '2020-11-30', '2020-11-30', '2020-11-30',\n",
       "               '2020-11-30', '2020-11-30', '2020-11-30', '2020-11-30',\n",
       "               '2020-11-30', '2020-11-30'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2769, freq=None)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.index - pd.tseries.offsets.MonthEnd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "1da8fb2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.tseries import offsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "c2b35ef0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-01', '2010-01-01', '2010-01-01', '2010-01-01',\n",
       "               '2010-01-01', '2010-01-01', '2010-01-01', '2010-01-01',\n",
       "               '2010-01-01', '2010-01-01',\n",
       "               ...\n",
       "               '2020-12-01', '2020-12-01', '2020-12-01', '2020-12-01',\n",
       "               '2020-12-01', '2020-12-01', '2020-12-01', '2020-12-01',\n",
       "               '2020-12-01', '2020-12-01'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2769, freq=None)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.index - offsets.MonthBegin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6c1a6e31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-01', '2010-01-01', '2010-01-01', '2010-01-01',\n",
       "               '2010-01-01', '2010-01-01', '2010-01-01', '2010-01-01',\n",
       "               '2010-01-01', '2010-01-01',\n",
       "               ...\n",
       "               '2020-12-01', '2020-12-01', '2020-12-01', '2020-12-01',\n",
       "               '2020-12-01', '2020-12-01', '2020-12-01', '2020-12-01',\n",
       "               '2020-12-01', '2020-12-01'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2769, freq=None)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.index - offsets.BMonthBegin()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58f5b44b",
   "metadata": {},
   "source": [
    "# TimeDelta Object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "357be6cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('1 days 00:00:00')"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_a = pd.Timestamp(\"2010-01-01\")\n",
    "time_b = pd.Timestamp(\"2010-01-02\")\n",
    "time_b - time_a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "e0ec150a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('-1 days +00:00:00')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_a - time_b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "fc35620b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('2 days 02:02:00')"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Timedelta(days = 2, hours = 2, minutes = 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46f44dbf",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
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