02_SimpleStockDate.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Simple Stock Date"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## This tutorial is about date and how to manipulate date in dataframe."
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "# fix_yahoo_finance is used to fetch data \n",
        "import fix_yahoo_finance as yf\n",
        "yf.pdr_override()"
      ],
      "outputs": [],
      "execution_count": 1,
      "metadata": {
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        "outputHidden": false,
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    {
      "cell_type": "code",
      "source": [
        "# input\n",
        "symbol = 'AAPL'\n",
        "start = '2015-01-01'\n",
        "end = '2019-01-01'\n",
        "\n",
        "# Read data \n",
        "dataset = yf.download(symbol,start,end)\n",
        "\n",
        "# View Columns\n",
        "dataset.head()"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*********************100%***********************]  1 of 1 downloaded\n"
          ]
        },
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              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-01-02  111.389999  111.440002  107.349998  109.330002  100.755898   \n",
              "2015-01-05  108.290001  108.650002  105.410004  106.250000   97.917427   \n",
              "2015-01-06  106.540001  107.430000  104.629997  106.260002   97.926666   \n",
              "2015-01-07  107.199997  108.199997  106.699997  107.750000   99.299805   \n",
              "2015-01-08  109.230003  112.150002  108.699997  111.889999  103.115128   \n",
              "\n",
              "              Volume  \n",
              "Date                  \n",
              "2015-01-02  53204600  \n",
              "2015-01-05  64285500  \n",
              "2015-01-06  65797100  \n",
              "2015-01-07  40105900  \n",
              "2015-01-08  59364500  "
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              "      <th>Close</th>\n",
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              "      <th>2015-01-02</th>\n",
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              "      <td>107.349998</td>\n",
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              "      <td>100.755898</td>\n",
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              "      <th>2015-01-05</th>\n",
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              "      <td>104.629997</td>\n",
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              "      <td>97.926666</td>\n",
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              "      <th>2015-01-08</th>\n",
              "      <td>109.230003</td>\n",
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              "      <td>108.699997</td>\n",
              "      <td>111.889999</td>\n",
              "      <td>103.115128</td>\n",
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      "source": [
        "# Date becomes a columns\n",
        "df = dataset.copy() # Copy the original data\n",
        "dfn = df.reset_index()\n",
        "dfn.head()"
      ],
      "outputs": [
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              "        Date        Open        High         Low       Close   Adj Close  \\\n",
              "0 2015-01-02  111.389999  111.440002  107.349998  109.330002  100.755898   \n",
              "1 2015-01-05  108.290001  108.650002  105.410004  106.250000   97.917427   \n",
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              "4 2015-01-08  109.230003  112.150002  108.699997  111.889999  103.115128   \n",
              "\n",
              "     Volume  \n",
              "0  53204600  \n",
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              "      <td>2015-01-05</td>\n",
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              "      <td>105.410004</td>\n",
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              "      <td>106.540001</td>\n",
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              "      <td>104.629997</td>\n",
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              "      <th>4</th>\n",
              "      <td>2015-01-08</td>\n",
              "      <td>109.230003</td>\n",
              "      <td>112.150002</td>\n",
              "      <td>108.699997</td>\n",
              "      <td>111.889999</td>\n",
              "      <td>103.115128</td>\n",
              "      <td>59364500</td>\n",
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        "df = dataset.copy()"
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        "df.head()"
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              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-01-02  111.389999  111.440002  107.349998  109.330002  100.755898   \n",
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              "2015-01-08  109.230003  112.150002  108.699997  111.889999  103.115128   \n",
              "\n",
              "              Volume  \n",
              "Date                  \n",
              "2015-01-02  53204600  \n",
              "2015-01-05  64285500  \n",
              "2015-01-06  65797100  \n",
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              "      <th>2015-01-08</th>\n",
              "      <td>109.230003</td>\n",
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              "      <td>111.889999</td>\n",
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      "source": [
        "# Add Year, Month, Day\n",
        "df['Year'] = df.index.year\n",
        "df['Month'] = df.index.month\n",
        "df['Day'] = df.index.day"
      ],
      "outputs": [],
      "execution_count": 6,
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          "execution_count": 7,
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              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-01-02  111.389999  111.440002  107.349998  109.330002  100.755898   \n",
              "2015-01-05  108.290001  108.650002  105.410004  106.250000   97.917427   \n",
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              "2015-01-07  107.199997  108.199997  106.699997  107.750000   99.299805   \n",
              "2015-01-08  109.230003  112.150002  108.699997  111.889999  103.115128   \n",
              "\n",
              "              Volume  Year  Month  Day  \n",
              "Date                                    \n",
              "2015-01-02  53204600  2015      1    2  \n",
              "2015-01-05  64285500  2015      1    5  \n",
              "2015-01-06  65797100  2015      1    6  \n",
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              "      <td>107.199997</td>\n",
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              "      <td>40105900</td>\n",
              "      <td>2015</td>\n",
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              "      <td>7</td>\n",
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              "      <th>2015-01-08</th>\n",
              "      <td>109.230003</td>\n",
              "      <td>112.150002</td>\n",
              "      <td>108.699997</td>\n",
              "      <td>111.889999</td>\n",
              "      <td>103.115128</td>\n",
              "      <td>59364500</td>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
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    },
    {
      "cell_type": "code",
      "source": [
        "# Convert Daily to Weekly\n",
        "weekly = dataset.copy()\n",
        "weekly = weekly.resample('W').last()\n",
        "weekly.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 8,
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-01-04  111.389999  111.440002  107.349998  109.330002  100.755898   \n",
              "2015-01-11  112.669998  113.250000  110.209999  112.010002  103.225708   \n",
              "2015-01-18  107.029999  107.580002  105.199997  105.989998   97.677811   \n",
              "2015-01-25  112.300003  113.750000  111.529999  112.980003  104.119629   \n",
              "2015-02-01  118.400002  120.000000  116.849998  117.160004  107.971832   \n",
              "\n",
              "              Volume  \n",
              "Date                  \n",
              "2015-01-04  53204600  \n",
              "2015-01-11  53699500  \n",
              "2015-01-18  78513300  \n",
              "2015-01-25  46464800  \n",
              "2015-02-01  83745500  "
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              "      <th>2015-01-04</th>\n",
              "      <td>111.389999</td>\n",
              "      <td>111.440002</td>\n",
              "      <td>107.349998</td>\n",
              "      <td>109.330002</td>\n",
              "      <td>100.755898</td>\n",
              "      <td>53204600</td>\n",
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              "      <th>2015-01-11</th>\n",
              "      <td>112.669998</td>\n",
              "      <td>113.250000</td>\n",
              "      <td>110.209999</td>\n",
              "      <td>112.010002</td>\n",
              "      <td>103.225708</td>\n",
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              "      <th>2015-01-18</th>\n",
              "      <td>107.029999</td>\n",
              "      <td>107.580002</td>\n",
              "      <td>105.199997</td>\n",
              "      <td>105.989998</td>\n",
              "      <td>97.677811</td>\n",
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              "      <th>2015-01-25</th>\n",
              "      <td>112.300003</td>\n",
              "      <td>113.750000</td>\n",
              "      <td>111.529999</td>\n",
              "      <td>112.980003</td>\n",
              "      <td>104.119629</td>\n",
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              "      <th>2015-02-01</th>\n",
              "      <td>118.400002</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>116.849998</td>\n",
              "      <td>117.160004</td>\n",
              "      <td>107.971832</td>\n",
              "      <td>83745500</td>\n",
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    {
      "cell_type": "code",
      "source": [
        "# Convert Daily to Yearly\n",
        "yearly = dataset.copy()\n",
        "yearly = yearly.asfreq('BY') # Use Business Year - 'BY'\n",
        "yearly.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 9,
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-12-31  107.010002  107.029999  104.820000  105.260002   98.657883   \n",
              "2016-12-30  116.650002  117.199997  115.430000  115.820000  110.970810   \n",
              "2017-12-29  170.520004  170.589996  169.220001  169.229996  164.752060   \n",
              "2018-12-31  158.529999  159.360001  156.479996  157.740005  155.871613   \n",
              "\n",
              "              Volume  \n",
              "Date                  \n",
              "2015-12-31  40912300  \n",
              "2016-12-30  30586300  \n",
              "2017-12-29  25999900  \n",
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              "      <td>107.010002</td>\n",
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              "      <td>104.820000</td>\n",
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              "      <th>2016-12-30</th>\n",
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              "      <th>2017-12-29</th>\n",
              "      <td>170.520004</td>\n",
              "      <td>170.589996</td>\n",
              "      <td>169.220001</td>\n",
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              "      <td>164.752060</td>\n",
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              "      <th>2018-12-31</th>\n",
              "      <td>158.529999</td>\n",
              "      <td>159.360001</td>\n",
              "      <td>156.479996</td>\n",
              "      <td>157.740005</td>\n",
              "      <td>155.871613</td>\n",
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    },
    {
      "cell_type": "code",
      "source": [
        "# Choose Particular Year to analyze\n",
        "monthly = dataset.copy()\n",
        "monthly = monthly.reset_index()\n",
        "y2017 = monthly[monthly['Date'].dt.year==2017]\n",
        "y2017"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 10,
          "data": {
            "text/plain": [
              "          Date        Open        High         Low       Close   Adj Close  \\\n",
              "504 2017-01-03  115.800003  116.330002  114.760002  116.150002  111.286987   \n",
              "505 2017-01-04  115.849998  116.510002  115.750000  116.019997  111.162437   \n",
              "506 2017-01-05  115.919998  116.860001  115.809998  116.610001  111.727715   \n",
              "507 2017-01-06  116.779999  118.160004  116.470001  117.910004  112.973305   \n",
              "508 2017-01-09  117.949997  119.430000  117.940002  118.989998  114.008080   \n",
              "509 2017-01-10  118.769997  119.379997  118.300003  119.110001  114.123047   \n",
              "510 2017-01-11  118.739998  119.930000  118.599998  119.750000  114.736275   \n",
              "511 2017-01-12  118.900002  119.300003  118.209999  119.250000  114.257195   \n",
              "512 2017-01-13  119.110001  119.620003  118.809998  119.040001  114.055984   \n",
              "513 2017-01-17  118.339996  120.239998  118.220001  120.000000  114.975792   \n",
              "514 2017-01-18  120.000000  120.500000  119.709999  119.989998  114.966225   \n",
              "515 2017-01-19  119.400002  120.089996  119.370003  119.779999  114.765007   \n",
              "516 2017-01-20  120.449997  120.449997  119.730003  120.000000  114.975792   \n",
              "517 2017-01-23  120.000000  120.809998  119.769997  120.080002  115.052444   \n",
              "518 2017-01-24  119.550003  120.099998  119.500000  119.970001  114.947060   \n",
              "519 2017-01-25  120.419998  122.099998  120.279999  121.879997  116.777084   \n",
              "520 2017-01-26  121.669998  122.440002  121.599998  121.940002  116.834564   \n",
              "521 2017-01-27  122.139999  122.349998  121.599998  121.949997  116.844154   \n",
              "522 2017-01-30  120.930000  121.629997  120.660004  121.629997  116.537560   \n",
              "523 2017-01-31  121.150002  121.389999  120.620003  121.349998  116.269257   \n",
              "524 2017-02-01  127.029999  130.490005  127.010002  128.750000  123.359444   \n",
              "525 2017-02-02  127.980003  129.389999  127.779999  128.529999  123.148666   \n",
              "526 2017-02-03  128.309998  129.190002  128.160004  129.080002  123.675636   \n",
              "527 2017-02-06  129.130005  130.500000  128.899994  130.289993  124.834976   \n",
              "528 2017-02-07  130.539993  132.089996  130.449997  131.529999  126.023041   \n",
              "529 2017-02-08  131.350006  132.220001  131.220001  132.039993  126.511688   \n",
              "530 2017-02-09  131.649994  132.449997  131.119995  132.419998  127.425858   \n",
              "531 2017-02-10  132.460007  132.940002  132.050003  132.119995  127.137177   \n",
              "532 2017-02-13  133.080002  133.820007  132.750000  133.289993  128.263062   \n",
              "533 2017-02-14  133.470001  135.089996  133.250000  135.020004  129.927811   \n",
              "..         ...         ...         ...         ...         ...         ...   \n",
              "725 2017-11-16  171.179993  171.869995  170.300003  171.100006  166.572571   \n",
              "726 2017-11-17  171.039993  171.389999  169.639999  170.149994  165.647690   \n",
              "727 2017-11-20  170.289993  170.559998  169.559998  169.979996  165.482208   \n",
              "728 2017-11-21  170.779999  173.699997  170.779999  173.139999  168.558578   \n",
              "729 2017-11-22  173.360001  175.000000  173.050003  174.960007  170.330444   \n",
              "730 2017-11-24  175.100006  175.500000  174.649994  174.970001  170.340179   \n",
              "731 2017-11-27  175.050003  175.080002  173.339996  174.089996  169.483444   \n",
              "732 2017-11-28  174.300003  174.869995  171.860001  173.070007  168.490463   \n",
              "733 2017-11-29  172.630005  172.919998  167.160004  169.479996  164.995453   \n",
              "734 2017-11-30  170.429993  172.139999  168.440002  171.850006  167.302734   \n",
              "735 2017-12-01  169.949997  171.669998  168.500000  171.050003  166.523895   \n",
              "736 2017-12-04  172.479996  172.619995  169.630005  169.800003  165.306976   \n",
              "737 2017-12-05  169.059998  171.520004  168.399994  169.639999  165.151184   \n",
              "738 2017-12-06  167.500000  170.199997  166.460007  169.009995  164.537888   \n",
              "739 2017-12-07  169.029999  170.440002  168.910004  169.320007  164.839676   \n",
              "740 2017-12-08  170.490005  171.000000  168.820007  169.369995  164.888367   \n",
              "741 2017-12-11  169.199997  172.889999  168.789993  172.669998  168.101028   \n",
              "742 2017-12-12  172.149994  172.389999  171.460007  171.699997  167.156677   \n",
              "743 2017-12-13  172.500000  173.539993  172.000000  172.270004  167.711624   \n",
              "744 2017-12-14  172.399994  173.130005  171.649994  172.220001  167.662949   \n",
              "745 2017-12-15  173.630005  174.169998  172.460007  173.970001  169.366638   \n",
              "746 2017-12-18  174.880005  177.199997  174.860001  176.419998  171.751816   \n",
              "747 2017-12-19  175.029999  175.389999  174.089996  174.539993  169.921539   \n",
              "748 2017-12-20  174.869995  175.419998  173.250000  174.350006  169.736588   \n",
              "749 2017-12-21  174.169998  176.020004  174.100006  175.009995  170.379120   \n",
              "750 2017-12-22  174.679993  175.419998  174.500000  175.009995  170.379120   \n",
              "751 2017-12-26  170.800003  171.470001  169.679993  170.570007  166.056595   \n",
              "752 2017-12-27  170.100006  170.779999  169.710007  170.600006  166.085815   \n",
              "753 2017-12-28  171.000000  171.850006  170.479996  171.080002  166.553101   \n",
              "754 2017-12-29  170.520004  170.589996  169.220001  169.229996  164.752060   \n",
              "\n",
              "        Volume  \n",
              "504   28781900  \n",
              "505   21118100  \n",
              "506   22193600  \n",
              "507   31751900  \n",
              "508   33561900  \n",
              "509   24462100  \n",
              "510   27588600  \n",
              "511   27086200  \n",
              "512   26111900  \n",
              "513   34439800  \n",
              "514   23713000  \n",
              "515   25597300  \n",
              "516   32597900  \n",
              "517   22050200  \n",
              "518   23211000  \n",
              "519   32377600  \n",
              "520   26337600  \n",
              "521   20562900  \n",
              "522   30377500  \n",
              "523   49201000  \n",
              "524  111985000  \n",
              "525   33710400  \n",
              "526   24507300  \n",
              "527   26845900  \n",
              "528   38183800  \n",
              "529   23004100  \n",
              "530   28349900  \n",
              "531   20065500  \n",
              "532   23035400  \n",
              "533   33226200  \n",
              "..         ...  \n",
              "725   23637500  \n",
              "726   21899500  \n",
              "727   16262400  \n",
              "728   25131300  \n",
              "729   25588900  \n",
              "730   14026700  \n",
              "731   20716800  \n",
              "732   26428800  \n",
              "733   41666400  \n",
              "734   41527200  \n",
              "735   39759300  \n",
              "736   32542400  \n",
              "737   27350200  \n",
              "738   28560000  \n",
              "739   25673300  \n",
              "740   23355200  \n",
              "741   35273800  \n",
              "742   19409200  \n",
              "743   23818400  \n",
              "744   20476500  \n",
              "745   40169300  \n",
              "746   29421100  \n",
              "747   27436400  \n",
              "748   23475600  \n",
              "749   20949900  \n",
              "750   16349400  \n",
              "751   33185500  \n",
              "752   21498200  \n",
              "753   16480200  \n",
              "754   25999900  \n",
              "\n",
              "[251 rows x 7 columns]"
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              "      <th>504</th>\n",
              "      <td>2017-01-03</td>\n",
              "      <td>115.800003</td>\n",
              "      <td>116.330002</td>\n",
              "      <td>114.760002</td>\n",
              "      <td>116.150002</td>\n",
              "      <td>111.286987</td>\n",
              "      <td>28781900</td>\n",
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              "      <th>505</th>\n",
              "      <td>2017-01-04</td>\n",
              "      <td>115.849998</td>\n",
              "      <td>116.510002</td>\n",
              "      <td>115.750000</td>\n",
              "      <td>116.019997</td>\n",
              "      <td>111.162437</td>\n",
              "      <td>21118100</td>\n",
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              "    <tr>\n",
              "      <th>506</th>\n",
              "      <td>2017-01-05</td>\n",
              "      <td>115.919998</td>\n",
              "      <td>116.860001</td>\n",
              "      <td>115.809998</td>\n",
              "      <td>116.610001</td>\n",
              "      <td>111.727715</td>\n",
              "      <td>22193600</td>\n",
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              "    <tr>\n",
              "      <th>507</th>\n",
              "      <td>2017-01-06</td>\n",
              "      <td>116.779999</td>\n",
              "      <td>118.160004</td>\n",
              "      <td>116.470001</td>\n",
              "      <td>117.910004</td>\n",
              "      <td>112.973305</td>\n",
              "      <td>31751900</td>\n",
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              "    <tr>\n",
              "      <th>508</th>\n",
              "      <td>2017-01-09</td>\n",
              "      <td>117.949997</td>\n",
              "      <td>119.430000</td>\n",
              "      <td>117.940002</td>\n",
              "      <td>118.989998</td>\n",
              "      <td>114.008080</td>\n",
              "      <td>33561900</td>\n",
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              "    <tr>\n",
              "      <th>509</th>\n",
              "      <td>2017-01-10</td>\n",
              "      <td>118.769997</td>\n",
              "      <td>119.379997</td>\n",
              "      <td>118.300003</td>\n",
              "      <td>119.110001</td>\n",
              "      <td>114.123047</td>\n",
              "      <td>24462100</td>\n",
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              "      <th>510</th>\n",
              "      <td>2017-01-11</td>\n",
              "      <td>118.739998</td>\n",
              "      <td>119.930000</td>\n",
              "      <td>118.599998</td>\n",
              "      <td>119.750000</td>\n",
              "      <td>114.736275</td>\n",
              "      <td>27588600</td>\n",
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              "    <tr>\n",
              "      <th>511</th>\n",
              "      <td>2017-01-12</td>\n",
              "      <td>118.900002</td>\n",
              "      <td>119.300003</td>\n",
              "      <td>118.209999</td>\n",
              "      <td>119.250000</td>\n",
              "      <td>114.257195</td>\n",
              "      <td>27086200</td>\n",
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              "    <tr>\n",
              "      <th>512</th>\n",
              "      <td>2017-01-13</td>\n",
              "      <td>119.110001</td>\n",
              "      <td>119.620003</td>\n",
              "      <td>118.809998</td>\n",
              "      <td>119.040001</td>\n",
              "      <td>114.055984</td>\n",
              "      <td>26111900</td>\n",
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              "    <tr>\n",
              "      <th>513</th>\n",
              "      <td>2017-01-17</td>\n",
              "      <td>118.339996</td>\n",
              "      <td>120.239998</td>\n",
              "      <td>118.220001</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>114.975792</td>\n",
              "      <td>34439800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>514</th>\n",
              "      <td>2017-01-18</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>120.500000</td>\n",
              "      <td>119.709999</td>\n",
              "      <td>119.989998</td>\n",
              "      <td>114.966225</td>\n",
              "      <td>23713000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>515</th>\n",
              "      <td>2017-01-19</td>\n",
              "      <td>119.400002</td>\n",
              "      <td>120.089996</td>\n",
              "      <td>119.370003</td>\n",
              "      <td>119.779999</td>\n",
              "      <td>114.765007</td>\n",
              "      <td>25597300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>516</th>\n",
              "      <td>2017-01-20</td>\n",
              "      <td>120.449997</td>\n",
              "      <td>120.449997</td>\n",
              "      <td>119.730003</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>114.975792</td>\n",
              "      <td>32597900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>517</th>\n",
              "      <td>2017-01-23</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>120.809998</td>\n",
              "      <td>119.769997</td>\n",
              "      <td>120.080002</td>\n",
              "      <td>115.052444</td>\n",
              "      <td>22050200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>518</th>\n",
              "      <td>2017-01-24</td>\n",
              "      <td>119.550003</td>\n",
              "      <td>120.099998</td>\n",
              "      <td>119.500000</td>\n",
              "      <td>119.970001</td>\n",
              "      <td>114.947060</td>\n",
              "      <td>23211000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>519</th>\n",
              "      <td>2017-01-25</td>\n",
              "      <td>120.419998</td>\n",
              "      <td>122.099998</td>\n",
              "      <td>120.279999</td>\n",
              "      <td>121.879997</td>\n",
              "      <td>116.777084</td>\n",
              "      <td>32377600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>520</th>\n",
              "      <td>2017-01-26</td>\n",
              "      <td>121.669998</td>\n",
              "      <td>122.440002</td>\n",
              "      <td>121.599998</td>\n",
              "      <td>121.940002</td>\n",
              "      <td>116.834564</td>\n",
              "      <td>26337600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>521</th>\n",
              "      <td>2017-01-27</td>\n",
              "      <td>122.139999</td>\n",
              "      <td>122.349998</td>\n",
              "      <td>121.599998</td>\n",
              "      <td>121.949997</td>\n",
              "      <td>116.844154</td>\n",
              "      <td>20562900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>522</th>\n",
              "      <td>2017-01-30</td>\n",
              "      <td>120.930000</td>\n",
              "      <td>121.629997</td>\n",
              "      <td>120.660004</td>\n",
              "      <td>121.629997</td>\n",
              "      <td>116.537560</td>\n",
              "      <td>30377500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>523</th>\n",
              "      <td>2017-01-31</td>\n",
              "      <td>121.150002</td>\n",
              "      <td>121.389999</td>\n",
              "      <td>120.620003</td>\n",
              "      <td>121.349998</td>\n",
              "      <td>116.269257</td>\n",
              "      <td>49201000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>524</th>\n",
              "      <td>2017-02-01</td>\n",
              "      <td>127.029999</td>\n",
              "      <td>130.490005</td>\n",
              "      <td>127.010002</td>\n",
              "      <td>128.750000</td>\n",
              "      <td>123.359444</td>\n",
              "      <td>111985000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>525</th>\n",
              "      <td>2017-02-02</td>\n",
              "      <td>127.980003</td>\n",
              "      <td>129.389999</td>\n",
              "      <td>127.779999</td>\n",
              "      <td>128.529999</td>\n",
              "      <td>123.148666</td>\n",
              "      <td>33710400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>526</th>\n",
              "      <td>2017-02-03</td>\n",
              "      <td>128.309998</td>\n",
              "      <td>129.190002</td>\n",
              "      <td>128.160004</td>\n",
              "      <td>129.080002</td>\n",
              "      <td>123.675636</td>\n",
              "      <td>24507300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>527</th>\n",
              "      <td>2017-02-06</td>\n",
              "      <td>129.130005</td>\n",
              "      <td>130.500000</td>\n",
              "      <td>128.899994</td>\n",
              "      <td>130.289993</td>\n",
              "      <td>124.834976</td>\n",
              "      <td>26845900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>528</th>\n",
              "      <td>2017-02-07</td>\n",
              "      <td>130.539993</td>\n",
              "      <td>132.089996</td>\n",
              "      <td>130.449997</td>\n",
              "      <td>131.529999</td>\n",
              "      <td>126.023041</td>\n",
              "      <td>38183800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>529</th>\n",
              "      <td>2017-02-08</td>\n",
              "      <td>131.350006</td>\n",
              "      <td>132.220001</td>\n",
              "      <td>131.220001</td>\n",
              "      <td>132.039993</td>\n",
              "      <td>126.511688</td>\n",
              "      <td>23004100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>530</th>\n",
              "      <td>2017-02-09</td>\n",
              "      <td>131.649994</td>\n",
              "      <td>132.449997</td>\n",
              "      <td>131.119995</td>\n",
              "      <td>132.419998</td>\n",
              "      <td>127.425858</td>\n",
              "      <td>28349900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>531</th>\n",
              "      <td>2017-02-10</td>\n",
              "      <td>132.460007</td>\n",
              "      <td>132.940002</td>\n",
              "      <td>132.050003</td>\n",
              "      <td>132.119995</td>\n",
              "      <td>127.137177</td>\n",
              "      <td>20065500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>532</th>\n",
              "      <td>2017-02-13</td>\n",
              "      <td>133.080002</td>\n",
              "      <td>133.820007</td>\n",
              "      <td>132.750000</td>\n",
              "      <td>133.289993</td>\n",
              "      <td>128.263062</td>\n",
              "      <td>23035400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>533</th>\n",
              "      <td>2017-02-14</td>\n",
              "      <td>133.470001</td>\n",
              "      <td>135.089996</td>\n",
              "      <td>133.250000</td>\n",
              "      <td>135.020004</td>\n",
              "      <td>129.927811</td>\n",
              "      <td>33226200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>725</th>\n",
              "      <td>2017-11-16</td>\n",
              "      <td>171.179993</td>\n",
              "      <td>171.869995</td>\n",
              "      <td>170.300003</td>\n",
              "      <td>171.100006</td>\n",
              "      <td>166.572571</td>\n",
              "      <td>23637500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>726</th>\n",
              "      <td>2017-11-17</td>\n",
              "      <td>171.039993</td>\n",
              "      <td>171.389999</td>\n",
              "      <td>169.639999</td>\n",
              "      <td>170.149994</td>\n",
              "      <td>165.647690</td>\n",
              "      <td>21899500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>727</th>\n",
              "      <td>2017-11-20</td>\n",
              "      <td>170.289993</td>\n",
              "      <td>170.559998</td>\n",
              "      <td>169.559998</td>\n",
              "      <td>169.979996</td>\n",
              "      <td>165.482208</td>\n",
              "      <td>16262400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>728</th>\n",
              "      <td>2017-11-21</td>\n",
              "      <td>170.779999</td>\n",
              "      <td>173.699997</td>\n",
              "      <td>170.779999</td>\n",
              "      <td>173.139999</td>\n",
              "      <td>168.558578</td>\n",
              "      <td>25131300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>729</th>\n",
              "      <td>2017-11-22</td>\n",
              "      <td>173.360001</td>\n",
              "      <td>175.000000</td>\n",
              "      <td>173.050003</td>\n",
              "      <td>174.960007</td>\n",
              "      <td>170.330444</td>\n",
              "      <td>25588900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>730</th>\n",
              "      <td>2017-11-24</td>\n",
              "      <td>175.100006</td>\n",
              "      <td>175.500000</td>\n",
              "      <td>174.649994</td>\n",
              "      <td>174.970001</td>\n",
              "      <td>170.340179</td>\n",
              "      <td>14026700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>731</th>\n",
              "      <td>2017-11-27</td>\n",
              "      <td>175.050003</td>\n",
              "      <td>175.080002</td>\n",
              "      <td>173.339996</td>\n",
              "      <td>174.089996</td>\n",
              "      <td>169.483444</td>\n",
              "      <td>20716800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>732</th>\n",
              "      <td>2017-11-28</td>\n",
              "      <td>174.300003</td>\n",
              "      <td>174.869995</td>\n",
              "      <td>171.860001</td>\n",
              "      <td>173.070007</td>\n",
              "      <td>168.490463</td>\n",
              "      <td>26428800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>733</th>\n",
              "      <td>2017-11-29</td>\n",
              "      <td>172.630005</td>\n",
              "      <td>172.919998</td>\n",
              "      <td>167.160004</td>\n",
              "      <td>169.479996</td>\n",
              "      <td>164.995453</td>\n",
              "      <td>41666400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>734</th>\n",
              "      <td>2017-11-30</td>\n",
              "      <td>170.429993</td>\n",
              "      <td>172.139999</td>\n",
              "      <td>168.440002</td>\n",
              "      <td>171.850006</td>\n",
              "      <td>167.302734</td>\n",
              "      <td>41527200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>735</th>\n",
              "      <td>2017-12-01</td>\n",
              "      <td>169.949997</td>\n",
              "      <td>171.669998</td>\n",
              "      <td>168.500000</td>\n",
              "      <td>171.050003</td>\n",
              "      <td>166.523895</td>\n",
              "      <td>39759300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>736</th>\n",
              "      <td>2017-12-04</td>\n",
              "      <td>172.479996</td>\n",
              "      <td>172.619995</td>\n",
              "      <td>169.630005</td>\n",
              "      <td>169.800003</td>\n",
              "      <td>165.306976</td>\n",
              "      <td>32542400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>737</th>\n",
              "      <td>2017-12-05</td>\n",
              "      <td>169.059998</td>\n",
              "      <td>171.520004</td>\n",
              "      <td>168.399994</td>\n",
              "      <td>169.639999</td>\n",
              "      <td>165.151184</td>\n",
              "      <td>27350200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>738</th>\n",
              "      <td>2017-12-06</td>\n",
              "      <td>167.500000</td>\n",
              "      <td>170.199997</td>\n",
              "      <td>166.460007</td>\n",
              "      <td>169.009995</td>\n",
              "      <td>164.537888</td>\n",
              "      <td>28560000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>739</th>\n",
              "      <td>2017-12-07</td>\n",
              "      <td>169.029999</td>\n",
              "      <td>170.440002</td>\n",
              "      <td>168.910004</td>\n",
              "      <td>169.320007</td>\n",
              "      <td>164.839676</td>\n",
              "      <td>25673300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>740</th>\n",
              "      <td>2017-12-08</td>\n",
              "      <td>170.490005</td>\n",
              "      <td>171.000000</td>\n",
              "      <td>168.820007</td>\n",
              "      <td>169.369995</td>\n",
              "      <td>164.888367</td>\n",
              "      <td>23355200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>741</th>\n",
              "      <td>2017-12-11</td>\n",
              "      <td>169.199997</td>\n",
              "      <td>172.889999</td>\n",
              "      <td>168.789993</td>\n",
              "      <td>172.669998</td>\n",
              "      <td>168.101028</td>\n",
              "      <td>35273800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>742</th>\n",
              "      <td>2017-12-12</td>\n",
              "      <td>172.149994</td>\n",
              "      <td>172.389999</td>\n",
              "      <td>171.460007</td>\n",
              "      <td>171.699997</td>\n",
              "      <td>167.156677</td>\n",
              "      <td>19409200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>743</th>\n",
              "      <td>2017-12-13</td>\n",
              "      <td>172.500000</td>\n",
              "      <td>173.539993</td>\n",
              "      <td>172.000000</td>\n",
              "      <td>172.270004</td>\n",
              "      <td>167.711624</td>\n",
              "      <td>23818400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>744</th>\n",
              "      <td>2017-12-14</td>\n",
              "      <td>172.399994</td>\n",
              "      <td>173.130005</td>\n",
              "      <td>171.649994</td>\n",
              "      <td>172.220001</td>\n",
              "      <td>167.662949</td>\n",
              "      <td>20476500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>745</th>\n",
              "      <td>2017-12-15</td>\n",
              "      <td>173.630005</td>\n",
              "      <td>174.169998</td>\n",
              "      <td>172.460007</td>\n",
              "      <td>173.970001</td>\n",
              "      <td>169.366638</td>\n",
              "      <td>40169300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>746</th>\n",
              "      <td>2017-12-18</td>\n",
              "      <td>174.880005</td>\n",
              "      <td>177.199997</td>\n",
              "      <td>174.860001</td>\n",
              "      <td>176.419998</td>\n",
              "      <td>171.751816</td>\n",
              "      <td>29421100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>747</th>\n",
              "      <td>2017-12-19</td>\n",
              "      <td>175.029999</td>\n",
              "      <td>175.389999</td>\n",
              "      <td>174.089996</td>\n",
              "      <td>174.539993</td>\n",
              "      <td>169.921539</td>\n",
              "      <td>27436400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>748</th>\n",
              "      <td>2017-12-20</td>\n",
              "      <td>174.869995</td>\n",
              "      <td>175.419998</td>\n",
              "      <td>173.250000</td>\n",
              "      <td>174.350006</td>\n",
              "      <td>169.736588</td>\n",
              "      <td>23475600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>749</th>\n",
              "      <td>2017-12-21</td>\n",
              "      <td>174.169998</td>\n",
              "      <td>176.020004</td>\n",
              "      <td>174.100006</td>\n",
              "      <td>175.009995</td>\n",
              "      <td>170.379120</td>\n",
              "      <td>20949900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>750</th>\n",
              "      <td>2017-12-22</td>\n",
              "      <td>174.679993</td>\n",
              "      <td>175.419998</td>\n",
              "      <td>174.500000</td>\n",
              "      <td>175.009995</td>\n",
              "      <td>170.379120</td>\n",
              "      <td>16349400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>751</th>\n",
              "      <td>2017-12-26</td>\n",
              "      <td>170.800003</td>\n",
              "      <td>171.470001</td>\n",
              "      <td>169.679993</td>\n",
              "      <td>170.570007</td>\n",
              "      <td>166.056595</td>\n",
              "      <td>33185500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>752</th>\n",
              "      <td>2017-12-27</td>\n",
              "      <td>170.100006</td>\n",
              "      <td>170.779999</td>\n",
              "      <td>169.710007</td>\n",
              "      <td>170.600006</td>\n",
              "      <td>166.085815</td>\n",
              "      <td>21498200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>753</th>\n",
              "      <td>2017-12-28</td>\n",
              "      <td>171.000000</td>\n",
              "      <td>171.850006</td>\n",
              "      <td>170.479996</td>\n",
              "      <td>171.080002</td>\n",
              "      <td>166.553101</td>\n",
              "      <td>16480200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>754</th>\n",
              "      <td>2017-12-29</td>\n",
              "      <td>170.520004</td>\n",
              "      <td>170.589996</td>\n",
              "      <td>169.220001</td>\n",
              "      <td>169.229996</td>\n",
              "      <td>164.752060</td>\n",
              "      <td>25999900</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>251 rows × 7 columns</p>\n",
              "</div>"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 10,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "month_name = dataset.copy()"
      ],
      "outputs": [],
      "execution_count": 11,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Convert Daily to Monthly\n",
        "month_name = month_name.asfreq('M')"
      ],
      "outputs": [],
      "execution_count": 12,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "month_name['Month_Name'] = month_name.index.month"
      ],
      "outputs": [],
      "execution_count": 13,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "month_name.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 14,
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-01-31         NaN         NaN         NaN         NaN         NaN   \n",
              "2015-02-28         NaN         NaN         NaN         NaN         NaN   \n",
              "2015-03-31  126.089996  126.489998  124.360001  124.430000  115.124252   \n",
              "2015-04-30  128.639999  128.639999  124.580002  125.150002  115.790398   \n",
              "2015-05-31         NaN         NaN         NaN         NaN         NaN   \n",
              "\n",
              "                Volume  Month_Name  \n",
              "Date                                \n",
              "2015-01-31         NaN           1  \n",
              "2015-02-28         NaN           2  \n",
              "2015-03-31  42090600.0           3  \n",
              "2015-04-30  83195400.0           4  \n",
              "2015-05-31         NaN           5  "
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\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>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Month_Name</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-31</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-28</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-31</th>\n",
              "      <td>126.089996</td>\n",
              "      <td>126.489998</td>\n",
              "      <td>124.360001</td>\n",
              "      <td>124.430000</td>\n",
              "      <td>115.124252</td>\n",
              "      <td>42090600.0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-04-30</th>\n",
              "      <td>128.639999</td>\n",
              "      <td>128.639999</td>\n",
              "      <td>124.580002</td>\n",
              "      <td>125.150002</td>\n",
              "      <td>115.790398</td>\n",
              "      <td>83195400.0</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-05-31</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 14,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import calendar\n",
        "\n",
        "month_name['Month_ABBR'] = month_name['Month_Name'].apply(lambda x: calendar.month_abbr[x])\n",
        "month_name.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 15,
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-01-31         NaN         NaN         NaN         NaN         NaN   \n",
              "2015-02-28         NaN         NaN         NaN         NaN         NaN   \n",
              "2015-03-31  126.089996  126.489998  124.360001  124.430000  115.124252   \n",
              "2015-04-30  128.639999  128.639999  124.580002  125.150002  115.790398   \n",
              "2015-05-31         NaN         NaN         NaN         NaN         NaN   \n",
              "\n",
              "                Volume  Month_Name Month_ABBR  \n",
              "Date                                           \n",
              "2015-01-31         NaN           1        Jan  \n",
              "2015-02-28         NaN           2        Feb  \n",
              "2015-03-31  42090600.0           3        Mar  \n",
              "2015-04-30  83195400.0           4        Apr  \n",
              "2015-05-31         NaN           5        May  "
            ],
            "text/html": [
              "<div>\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>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Month_Name</th>\n",
              "      <th>Month_ABBR</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-31</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>Jan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-28</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>Feb</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-31</th>\n",
              "      <td>126.089996</td>\n",
              "      <td>126.489998</td>\n",
              "      <td>124.360001</td>\n",
              "      <td>124.430000</td>\n",
              "      <td>115.124252</td>\n",
              "      <td>42090600.0</td>\n",
              "      <td>3</td>\n",
              "      <td>Mar</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-04-30</th>\n",
              "      <td>128.639999</td>\n",
              "      <td>128.639999</td>\n",
              "      <td>124.580002</td>\n",
              "      <td>125.150002</td>\n",
              "      <td>115.790398</td>\n",
              "      <td>83195400.0</td>\n",
              "      <td>4</td>\n",
              "      <td>Apr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-05-31</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5</td>\n",
              "      <td>May</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 15,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "month_name['Month_Name'] = month_name['Month_Name'].apply(lambda x: calendar.month_name[x])\n",
        "month_name.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 16,
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-01-31         NaN         NaN         NaN         NaN         NaN   \n",
              "2015-02-28         NaN         NaN         NaN         NaN         NaN   \n",
              "2015-03-31  126.089996  126.489998  124.360001  124.430000  115.124252   \n",
              "2015-04-30  128.639999  128.639999  124.580002  125.150002  115.790398   \n",
              "2015-05-31         NaN         NaN         NaN         NaN         NaN   \n",
              "\n",
              "                Volume Month_Name Month_ABBR  \n",
              "Date                                          \n",
              "2015-01-31         NaN    January        Jan  \n",
              "2015-02-28         NaN   February        Feb  \n",
              "2015-03-31  42090600.0      March        Mar  \n",
              "2015-04-30  83195400.0      April        Apr  \n",
              "2015-05-31         NaN        May        May  "
            ],
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              "<div>\n",
              "<style scoped>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Month_Name</th>\n",
              "      <th>Month_ABBR</th>\n",
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              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-31</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>January</td>\n",
              "      <td>Jan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-28</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>February</td>\n",
              "      <td>Feb</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-31</th>\n",
              "      <td>126.089996</td>\n",
              "      <td>126.489998</td>\n",
              "      <td>124.360001</td>\n",
              "      <td>124.430000</td>\n",
              "      <td>115.124252</td>\n",
              "      <td>42090600.0</td>\n",
              "      <td>March</td>\n",
              "      <td>Mar</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-04-30</th>\n",
              "      <td>128.639999</td>\n",
              "      <td>128.639999</td>\n",
              "      <td>124.580002</td>\n",
              "      <td>125.150002</td>\n",
              "      <td>115.790398</td>\n",
              "      <td>83195400.0</td>\n",
              "      <td>April</td>\n",
              "      <td>Apr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-05-31</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>May</td>\n",
              "      <td>May</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 16,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Pivot Table Date\n",
        "df_months = pd.pivot_table(df, index=df.index.month, columns=df.index.year, values = 'Adj Close') # each months \n",
        "df_months"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 17,
          "data": {
            "text/plain": [
              "Date        2015        2016        2017        2018\n",
              "Date                                                \n",
              "1     101.964537   92.255288  114.563798  169.400941\n",
              "2     115.983100   90.154997  128.500691  163.667434\n",
              "3     116.549917   98.257715  135.314523  170.571521\n",
              "4     117.771681  100.587027  137.497963  166.014473\n",
              "5     119.531181   89.968385  146.875109  181.813889\n",
              "6     118.742459   91.607716  142.843179  185.090041\n",
              "7     116.446370   93.441559  143.295523  186.748400\n",
              "8     105.759628  102.559884  154.077625  209.869185\n",
              "9     105.272106  105.673184  152.888451  218.680258\n",
              "10    105.796970  110.296387  153.090975  217.470995\n",
              "11    110.678055  105.490317  167.643493  188.799593\n",
              "12    104.719086  109.548666  167.343133  162.320619"
            ],
            "text/html": [
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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>Date</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>101.964537</td>\n",
              "      <td>92.255288</td>\n",
              "      <td>114.563798</td>\n",
              "      <td>169.400941</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>115.983100</td>\n",
              "      <td>90.154997</td>\n",
              "      <td>128.500691</td>\n",
              "      <td>163.667434</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>116.549917</td>\n",
              "      <td>98.257715</td>\n",
              "      <td>135.314523</td>\n",
              "      <td>170.571521</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>117.771681</td>\n",
              "      <td>100.587027</td>\n",
              "      <td>137.497963</td>\n",
              "      <td>166.014473</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>119.531181</td>\n",
              "      <td>89.968385</td>\n",
              "      <td>146.875109</td>\n",
              "      <td>181.813889</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>118.742459</td>\n",
              "      <td>91.607716</td>\n",
              "      <td>142.843179</td>\n",
              "      <td>185.090041</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>116.446370</td>\n",
              "      <td>93.441559</td>\n",
              "      <td>143.295523</td>\n",
              "      <td>186.748400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>105.759628</td>\n",
              "      <td>102.559884</td>\n",
              "      <td>154.077625</td>\n",
              "      <td>209.869185</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>105.272106</td>\n",
              "      <td>105.673184</td>\n",
              "      <td>152.888451</td>\n",
              "      <td>218.680258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>105.796970</td>\n",
              "      <td>110.296387</td>\n",
              "      <td>153.090975</td>\n",
              "      <td>217.470995</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>110.678055</td>\n",
              "      <td>105.490317</td>\n",
              "      <td>167.643493</td>\n",
              "      <td>188.799593</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>104.719086</td>\n",
              "      <td>109.548666</td>\n",
              "      <td>167.343133</td>\n",
              "      <td>162.320619</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 17,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_days = pd.pivot_table(df, index=df.index.day, columns=df.index.year, values = 'Adj Close') # daily for one whole months\n",
        "df_days"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 18,
          "data": {
            "text/plain": [
              "Date        2015        2016        2017        2018\n",
              "Date                                                \n",
              "1     112.278507   98.499905  147.435056  189.531226\n",
              "2     111.362408   97.226121  144.733758  183.222263\n",
              "3     112.190777   97.325496  139.492377  185.844877\n",
              "4     112.785614   99.155298  142.796642  189.729939\n",
              "5     110.712699   97.696275  144.341989  186.541160\n",
              "6     111.160470   98.439295  143.856724  185.439777\n",
              "7     110.157305   99.746928  147.994895  186.454033\n",
              "8     111.041228   98.120816  150.209652  186.682379\n",
              "9     110.747270   98.088196  143.053785  185.038356\n",
              "10    112.787268   97.613995  141.390674  188.947637\n",
              "11    111.610857   97.449176  146.223695  186.813768\n",
              "12    111.011109   98.710342  144.675635  185.081941\n",
              "13    111.308500   98.949473  144.066275  185.527832\n",
              "14    109.833995  101.324100  148.877582  185.619909\n",
              "15    110.950222  100.775921  150.156828  188.884840\n",
              "16    110.179281  100.342250  147.302473  186.445270\n",
              "17    112.699409   98.957085  142.322962  191.070122\n",
              "18    112.705495   99.690221  147.084819  186.868445\n",
              "19    114.031018  100.195836  145.070966  184.238271\n",
              "20    113.468959   99.848516  145.748711  181.203544\n",
              "21    109.365221  101.525406  147.710921  181.308006\n",
              "22    111.844690  100.187995  150.072655  185.735014\n",
              "23    112.913625  100.149654  139.810736  182.365675\n",
              "24    112.330801   97.773205  143.596804  186.258326\n",
              "25    111.045156   99.064668  143.565737  188.109868\n",
              "26    112.570473   98.744476  145.001307  180.078481\n",
              "27    112.849838   98.629200  145.025115  180.924035\n",
              "28    110.778607  100.014622  148.240538  184.383739\n",
              "29    111.974048   98.786026  152.466611  185.648767\n",
              "30    110.760438  103.259011  147.167490  186.076542\n",
              "31    107.929060  101.688684  144.815728  188.106237"
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              "      <th>Date</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "    </tr>\n",
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              "      <th>1</th>\n",
              "      <td>112.278507</td>\n",
              "      <td>98.499905</td>\n",
              "      <td>147.435056</td>\n",
              "      <td>189.531226</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>111.362408</td>\n",
              "      <td>97.226121</td>\n",
              "      <td>144.733758</td>\n",
              "      <td>183.222263</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>112.190777</td>\n",
              "      <td>97.325496</td>\n",
              "      <td>139.492377</td>\n",
              "      <td>185.844877</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>112.785614</td>\n",
              "      <td>99.155298</td>\n",
              "      <td>142.796642</td>\n",
              "      <td>189.729939</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>110.712699</td>\n",
              "      <td>97.696275</td>\n",
              "      <td>144.341989</td>\n",
              "      <td>186.541160</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>111.160470</td>\n",
              "      <td>98.439295</td>\n",
              "      <td>143.856724</td>\n",
              "      <td>185.439777</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>110.157305</td>\n",
              "      <td>99.746928</td>\n",
              "      <td>147.994895</td>\n",
              "      <td>186.454033</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>111.041228</td>\n",
              "      <td>98.120816</td>\n",
              "      <td>150.209652</td>\n",
              "      <td>186.682379</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>110.747270</td>\n",
              "      <td>98.088196</td>\n",
              "      <td>143.053785</td>\n",
              "      <td>185.038356</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>112.787268</td>\n",
              "      <td>97.613995</td>\n",
              "      <td>141.390674</td>\n",
              "      <td>188.947637</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>111.610857</td>\n",
              "      <td>97.449176</td>\n",
              "      <td>146.223695</td>\n",
              "      <td>186.813768</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>111.011109</td>\n",
              "      <td>98.710342</td>\n",
              "      <td>144.675635</td>\n",
              "      <td>185.081941</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>111.308500</td>\n",
              "      <td>98.949473</td>\n",
              "      <td>144.066275</td>\n",
              "      <td>185.527832</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>109.833995</td>\n",
              "      <td>101.324100</td>\n",
              "      <td>148.877582</td>\n",
              "      <td>185.619909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>110.950222</td>\n",
              "      <td>100.775921</td>\n",
              "      <td>150.156828</td>\n",
              "      <td>188.884840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>110.179281</td>\n",
              "      <td>100.342250</td>\n",
              "      <td>147.302473</td>\n",
              "      <td>186.445270</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>112.699409</td>\n",
              "      <td>98.957085</td>\n",
              "      <td>142.322962</td>\n",
              "      <td>191.070122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>112.705495</td>\n",
              "      <td>99.690221</td>\n",
              "      <td>147.084819</td>\n",
              "      <td>186.868445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>114.031018</td>\n",
              "      <td>100.195836</td>\n",
              "      <td>145.070966</td>\n",
              "      <td>184.238271</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>113.468959</td>\n",
              "      <td>99.848516</td>\n",
              "      <td>145.748711</td>\n",
              "      <td>181.203544</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>109.365221</td>\n",
              "      <td>101.525406</td>\n",
              "      <td>147.710921</td>\n",
              "      <td>181.308006</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>111.844690</td>\n",
              "      <td>100.187995</td>\n",
              "      <td>150.072655</td>\n",
              "      <td>185.735014</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>112.913625</td>\n",
              "      <td>100.149654</td>\n",
              "      <td>139.810736</td>\n",
              "      <td>182.365675</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>112.330801</td>\n",
              "      <td>97.773205</td>\n",
              "      <td>143.596804</td>\n",
              "      <td>186.258326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>111.045156</td>\n",
              "      <td>99.064668</td>\n",
              "      <td>143.565737</td>\n",
              "      <td>188.109868</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>112.570473</td>\n",
              "      <td>98.744476</td>\n",
              "      <td>145.001307</td>\n",
              "      <td>180.078481</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>112.849838</td>\n",
              "      <td>98.629200</td>\n",
              "      <td>145.025115</td>\n",
              "      <td>180.924035</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>110.778607</td>\n",
              "      <td>100.014622</td>\n",
              "      <td>148.240538</td>\n",
              "      <td>184.383739</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>111.974048</td>\n",
              "      <td>98.786026</td>\n",
              "      <td>152.466611</td>\n",
              "      <td>185.648767</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>110.760438</td>\n",
              "      <td>103.259011</td>\n",
              "      <td>147.167490</td>\n",
              "      <td>186.076542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>107.929060</td>\n",
              "      <td>101.688684</td>\n",
              "      <td>144.815728</td>\n",
              "      <td>188.106237</td>\n",
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            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 18,
      "metadata": {
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        "inputHidden": false
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    },
    {
      "cell_type": "code",
      "source": [
        "df_all_columns = pd.pivot_table(df, index=df.index.month, columns=df.index.year)\n",
        "df_all_columns"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 19,
          "data": {
            "text/plain": [
              "       Adj Close                                           Close              \\\n",
              "Date        2015        2016        2017        2018        2015        2016   \n",
              "Date                                                                           \n",
              "1     101.964537   92.255288  114.563798  169.400941  110.641501   98.428946   \n",
              "2     115.983100   90.154997  128.500691  163.667434  125.432105   95.746500   \n",
              "3     116.549917   98.257715  135.314523  170.571521  125.970908  104.267273   \n",
              "4     117.771681  100.587027  137.497963  166.014473  127.291428  106.739048   \n",
              "5     119.531181   89.968385  146.875109  181.813889  128.761500   94.974762   \n",
              "6     118.742459   91.607716  142.843179  185.090041  127.806817   96.622273   \n",
              "7     116.446370   93.441559  143.295523  186.748400  125.335455   98.556500   \n",
              "8     105.759628  102.559884  154.077625  209.869185  113.394762  107.665218   \n",
              "9     105.272106  105.673184  152.888451  218.680258  112.797619  110.857142   \n",
              "10    105.796970  110.296387  153.090975  217.470995  113.360000  115.707143   \n",
              "11    110.678055  105.490317  167.643493  188.799593  118.162500  110.154285   \n",
              "12    104.719086  109.548666  167.343133  162.320619  111.726818  114.335714   \n",
              "\n",
              "                                    Day             ...        Open  \\\n",
              "Date        2017        2018       2015       2016  ...        2017   \n",
              "Date                                                ...               \n",
              "1     119.570000  174.005237  16.650000  16.421053  ...  119.093499   \n",
              "2     133.714209  167.638947  14.421053  14.200000  ...  133.234738   \n",
              "3     140.617826  174.496192  15.954545  15.590909  ...  140.362174   \n",
              "4     142.886842  169.834287  16.285714  15.761905  ...  143.030001   \n",
              "5     152.227726  185.536818  15.300000  15.285714  ...  151.965908   \n",
              "6     147.831362  188.621429  14.954545  15.681818  ...  148.215001   \n",
              "7     148.299500  190.311429  16.954545  16.350000  ...  148.096500   \n",
              "8     159.021306  213.346089  16.238095  15.652174  ...  158.946958   \n",
              "9     157.608500  222.073685  15.714286  16.571429  ...  158.109000   \n",
              "10    157.817273  220.845652  16.045455  16.238095  ...  157.355907   \n",
              "11    172.406191  191.235714  14.700000  14.904762  ...  172.490476   \n",
              "12    171.891500  164.266317  15.590909  15.571429  ...  171.721999   \n",
              "\n",
              "                        Volume                                            \\\n",
              "Date        2018          2015          2016          2017          2018   \n",
              "Date                                                                       \n",
              "1     174.021428  6.526317e+07  6.693937e+07  2.815610e+07  3.141330e+07   \n",
              "2     167.276316  5.981764e+07  4.054313e+07  3.026151e+07  4.883654e+07   \n",
              "3     175.047143  5.175646e+07  3.391135e+07  2.441863e+07  3.398703e+07   \n",
              "4     169.765238  4.743502e+07  4.154208e+07  1.964758e+07  3.172163e+07   \n",
              "5     184.956365  4.770760e+07  4.288912e+07  2.972645e+07  2.822620e+07   \n",
              "6     188.720477  3.993667e+07  3.543171e+07  3.109900e+07  2.512498e+07   \n",
              "7     190.196190  4.810366e+07  3.428898e+07  2.110060e+07  1.874721e+07   \n",
              "8     212.486957  7.651520e+07  2.739689e+07  2.874213e+07  3.044865e+07   \n",
              "9     222.331053  5.745463e+07  4.609598e+07  3.401870e+07  3.573537e+07   \n",
              "10    221.200001  5.056873e+07  3.271020e+07  2.292233e+07  3.433689e+07   \n",
              "11    191.819523  3.753203e+07  3.435976e+07  2.860302e+07  4.577745e+07   \n",
              "12    165.243158  4.190524e+07  2.898913e+07  2.655919e+07  4.731171e+07   \n",
              "\n",
              "      Year                    \n",
              "Date  2015  2016  2017  2018  \n",
              "Date                          \n",
              "1     2015  2016  2017  2018  \n",
              "2     2015  2016  2017  2018  \n",
              "3     2015  2016  2017  2018  \n",
              "4     2015  2016  2017  2018  \n",
              "5     2015  2016  2017  2018  \n",
              "6     2015  2016  2017  2018  \n",
              "7     2015  2016  2017  2018  \n",
              "8     2015  2016  2017  2018  \n",
              "9     2015  2016  2017  2018  \n",
              "10    2015  2016  2017  2018  \n",
              "11    2015  2016  2017  2018  \n",
              "12    2015  2016  2017  2018  \n",
              "\n",
              "[12 rows x 36 columns]"
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              "      <td>101.964537</td>\n",
              "      <td>92.255288</td>\n",
              "      <td>114.563798</td>\n",
              "      <td>169.400941</td>\n",
              "      <td>110.641501</td>\n",
              "      <td>98.428946</td>\n",
              "      <td>119.570000</td>\n",
              "      <td>174.005237</td>\n",
              "      <td>16.650000</td>\n",
              "      <td>16.421053</td>\n",
              "      <td>...</td>\n",
              "      <td>119.093499</td>\n",
              "      <td>174.021428</td>\n",
              "      <td>6.526317e+07</td>\n",
              "      <td>6.693937e+07</td>\n",
              "      <td>2.815610e+07</td>\n",
              "      <td>3.141330e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>115.983100</td>\n",
              "      <td>90.154997</td>\n",
              "      <td>128.500691</td>\n",
              "      <td>163.667434</td>\n",
              "      <td>125.432105</td>\n",
              "      <td>95.746500</td>\n",
              "      <td>133.714209</td>\n",
              "      <td>167.638947</td>\n",
              "      <td>14.421053</td>\n",
              "      <td>14.200000</td>\n",
              "      <td>...</td>\n",
              "      <td>133.234738</td>\n",
              "      <td>167.276316</td>\n",
              "      <td>5.981764e+07</td>\n",
              "      <td>4.054313e+07</td>\n",
              "      <td>3.026151e+07</td>\n",
              "      <td>4.883654e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>116.549917</td>\n",
              "      <td>98.257715</td>\n",
              "      <td>135.314523</td>\n",
              "      <td>170.571521</td>\n",
              "      <td>125.970908</td>\n",
              "      <td>104.267273</td>\n",
              "      <td>140.617826</td>\n",
              "      <td>174.496192</td>\n",
              "      <td>15.954545</td>\n",
              "      <td>15.590909</td>\n",
              "      <td>...</td>\n",
              "      <td>140.362174</td>\n",
              "      <td>175.047143</td>\n",
              "      <td>5.175646e+07</td>\n",
              "      <td>3.391135e+07</td>\n",
              "      <td>2.441863e+07</td>\n",
              "      <td>3.398703e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>117.771681</td>\n",
              "      <td>100.587027</td>\n",
              "      <td>137.497963</td>\n",
              "      <td>166.014473</td>\n",
              "      <td>127.291428</td>\n",
              "      <td>106.739048</td>\n",
              "      <td>142.886842</td>\n",
              "      <td>169.834287</td>\n",
              "      <td>16.285714</td>\n",
              "      <td>15.761905</td>\n",
              "      <td>...</td>\n",
              "      <td>143.030001</td>\n",
              "      <td>169.765238</td>\n",
              "      <td>4.743502e+07</td>\n",
              "      <td>4.154208e+07</td>\n",
              "      <td>1.964758e+07</td>\n",
              "      <td>3.172163e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>119.531181</td>\n",
              "      <td>89.968385</td>\n",
              "      <td>146.875109</td>\n",
              "      <td>181.813889</td>\n",
              "      <td>128.761500</td>\n",
              "      <td>94.974762</td>\n",
              "      <td>152.227726</td>\n",
              "      <td>185.536818</td>\n",
              "      <td>15.300000</td>\n",
              "      <td>15.285714</td>\n",
              "      <td>...</td>\n",
              "      <td>151.965908</td>\n",
              "      <td>184.956365</td>\n",
              "      <td>4.770760e+07</td>\n",
              "      <td>4.288912e+07</td>\n",
              "      <td>2.972645e+07</td>\n",
              "      <td>2.822620e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>118.742459</td>\n",
              "      <td>91.607716</td>\n",
              "      <td>142.843179</td>\n",
              "      <td>185.090041</td>\n",
              "      <td>127.806817</td>\n",
              "      <td>96.622273</td>\n",
              "      <td>147.831362</td>\n",
              "      <td>188.621429</td>\n",
              "      <td>14.954545</td>\n",
              "      <td>15.681818</td>\n",
              "      <td>...</td>\n",
              "      <td>148.215001</td>\n",
              "      <td>188.720477</td>\n",
              "      <td>3.993667e+07</td>\n",
              "      <td>3.543171e+07</td>\n",
              "      <td>3.109900e+07</td>\n",
              "      <td>2.512498e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>116.446370</td>\n",
              "      <td>93.441559</td>\n",
              "      <td>143.295523</td>\n",
              "      <td>186.748400</td>\n",
              "      <td>125.335455</td>\n",
              "      <td>98.556500</td>\n",
              "      <td>148.299500</td>\n",
              "      <td>190.311429</td>\n",
              "      <td>16.954545</td>\n",
              "      <td>16.350000</td>\n",
              "      <td>...</td>\n",
              "      <td>148.096500</td>\n",
              "      <td>190.196190</td>\n",
              "      <td>4.810366e+07</td>\n",
              "      <td>3.428898e+07</td>\n",
              "      <td>2.110060e+07</td>\n",
              "      <td>1.874721e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>105.759628</td>\n",
              "      <td>102.559884</td>\n",
              "      <td>154.077625</td>\n",
              "      <td>209.869185</td>\n",
              "      <td>113.394762</td>\n",
              "      <td>107.665218</td>\n",
              "      <td>159.021306</td>\n",
              "      <td>213.346089</td>\n",
              "      <td>16.238095</td>\n",
              "      <td>15.652174</td>\n",
              "      <td>...</td>\n",
              "      <td>158.946958</td>\n",
              "      <td>212.486957</td>\n",
              "      <td>7.651520e+07</td>\n",
              "      <td>2.739689e+07</td>\n",
              "      <td>2.874213e+07</td>\n",
              "      <td>3.044865e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>105.272106</td>\n",
              "      <td>105.673184</td>\n",
              "      <td>152.888451</td>\n",
              "      <td>218.680258</td>\n",
              "      <td>112.797619</td>\n",
              "      <td>110.857142</td>\n",
              "      <td>157.608500</td>\n",
              "      <td>222.073685</td>\n",
              "      <td>15.714286</td>\n",
              "      <td>16.571429</td>\n",
              "      <td>...</td>\n",
              "      <td>158.109000</td>\n",
              "      <td>222.331053</td>\n",
              "      <td>5.745463e+07</td>\n",
              "      <td>4.609598e+07</td>\n",
              "      <td>3.401870e+07</td>\n",
              "      <td>3.573537e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>105.796970</td>\n",
              "      <td>110.296387</td>\n",
              "      <td>153.090975</td>\n",
              "      <td>217.470995</td>\n",
              "      <td>113.360000</td>\n",
              "      <td>115.707143</td>\n",
              "      <td>157.817273</td>\n",
              "      <td>220.845652</td>\n",
              "      <td>16.045455</td>\n",
              "      <td>16.238095</td>\n",
              "      <td>...</td>\n",
              "      <td>157.355907</td>\n",
              "      <td>221.200001</td>\n",
              "      <td>5.056873e+07</td>\n",
              "      <td>3.271020e+07</td>\n",
              "      <td>2.292233e+07</td>\n",
              "      <td>3.433689e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>110.678055</td>\n",
              "      <td>105.490317</td>\n",
              "      <td>167.643493</td>\n",
              "      <td>188.799593</td>\n",
              "      <td>118.162500</td>\n",
              "      <td>110.154285</td>\n",
              "      <td>172.406191</td>\n",
              "      <td>191.235714</td>\n",
              "      <td>14.700000</td>\n",
              "      <td>14.904762</td>\n",
              "      <td>...</td>\n",
              "      <td>172.490476</td>\n",
              "      <td>191.819523</td>\n",
              "      <td>3.753203e+07</td>\n",
              "      <td>3.435976e+07</td>\n",
              "      <td>2.860302e+07</td>\n",
              "      <td>4.577745e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>104.719086</td>\n",
              "      <td>109.548666</td>\n",
              "      <td>167.343133</td>\n",
              "      <td>162.320619</td>\n",
              "      <td>111.726818</td>\n",
              "      <td>114.335714</td>\n",
              "      <td>171.891500</td>\n",
              "      <td>164.266317</td>\n",
              "      <td>15.590909</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>...</td>\n",
              "      <td>171.721999</td>\n",
              "      <td>165.243158</td>\n",
              "      <td>4.190524e+07</td>\n",
              "      <td>2.898913e+07</td>\n",
              "      <td>2.655919e+07</td>\n",
              "      <td>4.731171e+07</td>\n",
              "      <td>2015</td>\n",
              "      <td>2016</td>\n",
              "      <td>2017</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>12 rows × 36 columns</p>\n",
              "</div>"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 19,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "stock_data = df.copy()\n",
        "\n",
        "stock_data['Year'] = df.index.year\n",
        "stock_data['Month'] = df.index.month\n",
        "stock_data['Day'] = df.index.day\n",
        "stock_data['Week_Day'] = df.index.dayofweek\n",
        "stock_data['Week_Day_Name'] = df.index.strftime('%A')\n",
        "stock_data.tail(10)"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 20,
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2018-12-17  165.449997  168.350006  162.729996  163.940002  161.998169   \n",
              "2018-12-18  165.380005  167.529999  164.389999  166.070007  164.102936   \n",
              "2018-12-19  166.000000  167.449997  159.089996  160.889999  158.984299   \n",
              "2018-12-20  160.399994  162.110001  155.300003  156.830002  154.972397   \n",
              "2018-12-21  156.860001  158.160004  149.630005  150.729996  148.944626   \n",
              "2018-12-24  148.149994  151.550003  146.589996  146.830002  145.090836   \n",
              "2018-12-26  148.300003  157.229996  146.720001  157.169998  155.308350   \n",
              "2018-12-27  155.839996  156.770004  150.070007  156.149994  154.300446   \n",
              "2018-12-28  157.500000  158.520004  154.550003  156.229996  154.379486   \n",
              "2018-12-31  158.529999  159.360001  156.479996  157.740005  155.871613   \n",
              "\n",
              "              Volume  Year  Month  Day  Week_Day Week_Day_Name  \n",
              "Date                                                            \n",
              "2018-12-17  44287900  2018     12   17         0        Monday  \n",
              "2018-12-18  33841500  2018     12   18         1       Tuesday  \n",
              "2018-12-19  49047300  2018     12   19         2     Wednesday  \n",
              "2018-12-20  64773000  2018     12   20         3      Thursday  \n",
              "2018-12-21  95744600  2018     12   21         4        Friday  \n",
              "2018-12-24  37169200  2018     12   24         0        Monday  \n",
              "2018-12-26  58582500  2018     12   26         2     Wednesday  \n",
              "2018-12-27  53117100  2018     12   27         3      Thursday  \n",
              "2018-12-28  42291400  2018     12   28         4        Friday  \n",
              "2018-12-31  35003500  2018     12   31         0        Monday  "
            ],
            "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>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Year</th>\n",
              "      <th>Month</th>\n",
              "      <th>Day</th>\n",
              "      <th>Week_Day</th>\n",
              "      <th>Week_Day_Name</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2018-12-17</th>\n",
              "      <td>165.449997</td>\n",
              "      <td>168.350006</td>\n",
              "      <td>162.729996</td>\n",
              "      <td>163.940002</td>\n",
              "      <td>161.998169</td>\n",
              "      <td>44287900</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>17</td>\n",
              "      <td>0</td>\n",
              "      <td>Monday</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-18</th>\n",
              "      <td>165.380005</td>\n",
              "      <td>167.529999</td>\n",
              "      <td>164.389999</td>\n",
              "      <td>166.070007</td>\n",
              "      <td>164.102936</td>\n",
              "      <td>33841500</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>18</td>\n",
              "      <td>1</td>\n",
              "      <td>Tuesday</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-19</th>\n",
              "      <td>166.000000</td>\n",
              "      <td>167.449997</td>\n",
              "      <td>159.089996</td>\n",
              "      <td>160.889999</td>\n",
              "      <td>158.984299</td>\n",
              "      <td>49047300</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>19</td>\n",
              "      <td>2</td>\n",
              "      <td>Wednesday</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-20</th>\n",
              "      <td>160.399994</td>\n",
              "      <td>162.110001</td>\n",
              "      <td>155.300003</td>\n",
              "      <td>156.830002</td>\n",
              "      <td>154.972397</td>\n",
              "      <td>64773000</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>20</td>\n",
              "      <td>3</td>\n",
              "      <td>Thursday</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-21</th>\n",
              "      <td>156.860001</td>\n",
              "      <td>158.160004</td>\n",
              "      <td>149.630005</td>\n",
              "      <td>150.729996</td>\n",
              "      <td>148.944626</td>\n",
              "      <td>95744600</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>21</td>\n",
              "      <td>4</td>\n",
              "      <td>Friday</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-24</th>\n",
              "      <td>148.149994</td>\n",
              "      <td>151.550003</td>\n",
              "      <td>146.589996</td>\n",
              "      <td>146.830002</td>\n",
              "      <td>145.090836</td>\n",
              "      <td>37169200</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>24</td>\n",
              "      <td>0</td>\n",
              "      <td>Monday</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-26</th>\n",
              "      <td>148.300003</td>\n",
              "      <td>157.229996</td>\n",
              "      <td>146.720001</td>\n",
              "      <td>157.169998</td>\n",
              "      <td>155.308350</td>\n",
              "      <td>58582500</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>26</td>\n",
              "      <td>2</td>\n",
              "      <td>Wednesday</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-27</th>\n",
              "      <td>155.839996</td>\n",
              "      <td>156.770004</td>\n",
              "      <td>150.070007</td>\n",
              "      <td>156.149994</td>\n",
              "      <td>154.300446</td>\n",
              "      <td>53117100</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>27</td>\n",
              "      <td>3</td>\n",
              "      <td>Thursday</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-28</th>\n",
              "      <td>157.500000</td>\n",
              "      <td>158.520004</td>\n",
              "      <td>154.550003</td>\n",
              "      <td>156.229996</td>\n",
              "      <td>154.379486</td>\n",
              "      <td>42291400</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>28</td>\n",
              "      <td>4</td>\n",
              "      <td>Friday</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-31</th>\n",
              "      <td>158.529999</td>\n",
              "      <td>159.360001</td>\n",
              "      <td>156.479996</td>\n",
              "      <td>157.740005</td>\n",
              "      <td>155.871613</td>\n",
              "      <td>35003500</td>\n",
              "      <td>2018</td>\n",
              "      <td>12</td>\n",
              "      <td>31</td>\n",
              "      <td>0</td>\n",
              "      <td>Monday</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 20,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "approach1 = stock_data.groupby(['Year', 'Month']).first()['Adj Close']\n",
        "approach1.tail(12)"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 21,
          "data": {
            "text/plain": [
              "Year  Month\n",
              "2018  1        167.701889\n",
              "      2        163.340424\n",
              "      3        171.063995\n",
              "      4        162.931122\n",
              "      5        165.296692\n",
              "      6        186.678314\n",
              "      7        183.675583\n",
              "      8        197.727493\n",
              "      9        224.870499\n",
              "      10       223.787323\n",
              "      11       218.824341\n",
              "      12       182.630859\n",
              "Name: Adj Close, dtype: float64"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 21,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "approach2 = stock_data.groupby(['Year', 'Day']).first()['Adj Close']\n",
        "approach2.tail(12)"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 22,
          "data": {
            "text/plain": [
              "Year  Day\n",
              "2018  20     167.984848\n",
              "      21     167.222412\n",
              "      22     172.316452\n",
              "      23     172.355392\n",
              "      24     169.610016\n",
              "      25     166.582321\n",
              "      26     166.971725\n",
              "      27     174.377747\n",
              "      28     174.113831\n",
              "      29     163.515671\n",
              "      30     162.551865\n",
              "      31     162.999695\n",
              "Name: Adj Close, dtype: float64"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 22,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Convert Date to String"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "string_date = dataset.copy()"
      ],
      "outputs": [],
      "execution_count": 23,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "string_date['Date'] = string_date.index\n",
        "string_date.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 24,
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-01-02  111.389999  111.440002  107.349998  109.330002  100.755898   \n",
              "2015-01-05  108.290001  108.650002  105.410004  106.250000   97.917427   \n",
              "2015-01-06  106.540001  107.430000  104.629997  106.260002   97.926666   \n",
              "2015-01-07  107.199997  108.199997  106.699997  107.750000   99.299805   \n",
              "2015-01-08  109.230003  112.150002  108.699997  111.889999  103.115128   \n",
              "\n",
              "              Volume       Date  \n",
              "Date                             \n",
              "2015-01-02  53204600 2015-01-02  \n",
              "2015-01-05  64285500 2015-01-05  \n",
              "2015-01-06  65797100 2015-01-06  \n",
              "2015-01-07  40105900 2015-01-07  \n",
              "2015-01-08  59364500 2015-01-08  "
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Date</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-02</th>\n",
              "      <td>111.389999</td>\n",
              "      <td>111.440002</td>\n",
              "      <td>107.349998</td>\n",
              "      <td>109.330002</td>\n",
              "      <td>100.755898</td>\n",
              "      <td>53204600</td>\n",
              "      <td>2015-01-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-05</th>\n",
              "      <td>108.290001</td>\n",
              "      <td>108.650002</td>\n",
              "      <td>105.410004</td>\n",
              "      <td>106.250000</td>\n",
              "      <td>97.917427</td>\n",
              "      <td>64285500</td>\n",
              "      <td>2015-01-05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-06</th>\n",
              "      <td>106.540001</td>\n",
              "      <td>107.430000</td>\n",
              "      <td>104.629997</td>\n",
              "      <td>106.260002</td>\n",
              "      <td>97.926666</td>\n",
              "      <td>65797100</td>\n",
              "      <td>2015-01-06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-07</th>\n",
              "      <td>107.199997</td>\n",
              "      <td>108.199997</td>\n",
              "      <td>106.699997</td>\n",
              "      <td>107.750000</td>\n",
              "      <td>99.299805</td>\n",
              "      <td>40105900</td>\n",
              "      <td>2015-01-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-08</th>\n",
              "      <td>109.230003</td>\n",
              "      <td>112.150002</td>\n",
              "      <td>108.699997</td>\n",
              "      <td>111.889999</td>\n",
              "      <td>103.115128</td>\n",
              "      <td>59364500</td>\n",
              "      <td>2015-01-08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 24,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "string_date['Date'] = string_date['Date'].dt.strftime(\"%Y%m%d\").astype(int)"
      ],
      "outputs": [],
      "execution_count": 25,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Convert Date to Numbers\n",
        "string_date.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 26,
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-01-02  111.389999  111.440002  107.349998  109.330002  100.755898   \n",
              "2015-01-05  108.290001  108.650002  105.410004  106.250000   97.917427   \n",
              "2015-01-06  106.540001  107.430000  104.629997  106.260002   97.926666   \n",
              "2015-01-07  107.199997  108.199997  106.699997  107.750000   99.299805   \n",
              "2015-01-08  109.230003  112.150002  108.699997  111.889999  103.115128   \n",
              "\n",
              "              Volume      Date  \n",
              "Date                            \n",
              "2015-01-02  53204600  20150102  \n",
              "2015-01-05  64285500  20150105  \n",
              "2015-01-06  65797100  20150106  \n",
              "2015-01-07  40105900  20150107  \n",
              "2015-01-08  59364500  20150108  "
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Date</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-02</th>\n",
              "      <td>111.389999</td>\n",
              "      <td>111.440002</td>\n",
              "      <td>107.349998</td>\n",
              "      <td>109.330002</td>\n",
              "      <td>100.755898</td>\n",
              "      <td>53204600</td>\n",
              "      <td>20150102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-05</th>\n",
              "      <td>108.290001</td>\n",
              "      <td>108.650002</td>\n",
              "      <td>105.410004</td>\n",
              "      <td>106.250000</td>\n",
              "      <td>97.917427</td>\n",
              "      <td>64285500</td>\n",
              "      <td>20150105</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-06</th>\n",
              "      <td>106.540001</td>\n",
              "      <td>107.430000</td>\n",
              "      <td>104.629997</td>\n",
              "      <td>106.260002</td>\n",
              "      <td>97.926666</td>\n",
              "      <td>65797100</td>\n",
              "      <td>20150106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-07</th>\n",
              "      <td>107.199997</td>\n",
              "      <td>108.199997</td>\n",
              "      <td>106.699997</td>\n",
              "      <td>107.750000</td>\n",
              "      <td>99.299805</td>\n",
              "      <td>40105900</td>\n",
              "      <td>20150107</td>\n",
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              "    <tr>\n",
              "      <th>2015-01-08</th>\n",
              "      <td>109.230003</td>\n",
              "      <td>112.150002</td>\n",
              "      <td>108.699997</td>\n",
              "      <td>111.889999</td>\n",
              "      <td>103.115128</td>\n",
              "      <td>59364500</td>\n",
              "      <td>20150108</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 26,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    }
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