Decision Trees Research.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Decision Trees\n",
    "(Reon)\n",
    "\n",
    "### Contents:\n",
    "1. Data Analysis\n",
    "2. Feature engineering\n",
    "2. Tree Building/Training\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "File b'AAPL.csv' does not exist",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-8-705125e9ad1f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'AAPL.csv'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#Read the data in\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDate\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_datetime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDate\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mformat\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'%d/%m/%Y'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#Set the date column to datetime\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Date'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#Set the index to the date column\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrename\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumns\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;34m'Adj Close'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;34m'Adj_Close'\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m20\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#Observe a few rows of data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, doublequote, delim_whitespace, low_memory, memory_map, float_precision)\u001b[0m\n\u001b[0;32m    676\u001b[0m                     skip_blank_lines=skip_blank_lines)\n\u001b[0;32m    677\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 678\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    679\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    680\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m_read\u001b[1;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[0;32m    438\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    439\u001b[0m     \u001b[1;31m# Create the parser.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 440\u001b[1;33m     \u001b[0mparser\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    441\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    442\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[0;32m    785\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'has_index_names'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'has_index_names'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    786\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 787\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    788\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    789\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[1;34m(self, engine)\u001b[0m\n\u001b[0;32m   1012\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'c'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1013\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'c'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1014\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1015\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1016\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'python'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, src, **kwds)\u001b[0m\n\u001b[0;32m   1706\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'usecols'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0musecols\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1707\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1708\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1709\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1710\u001b[0m         \u001b[0mpassed_names\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnames\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: File b'AAPL.csv' does not exist"
     ]
    }
   ],
   "source": [
    "df = pd.read_csv('AAPL.csv') #Read the data in\n",
    "df.Date = pd.to_datetime(df.Date, format='%d/%m/%Y') #Set the date column to datetime\n",
    "df.set_index('Date', inplace=True) #Set the index to the date column\n",
    "df = df.rename(columns = {'Adj Close':'Adj_Close'})\n",
    "df.head(20) #Observe a few rows of data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "aapl = pd.read_csv(\"C:\\\\Users\\\\reonh\\\\Documents\\\\NUS\\\\1920 S1\\\\FINTECH\\\\AAPL (2).csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Date</th>\n",
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       "      <td>111.760002</td>\n",
       "      <td>114.209999</td>\n",
       "      <td>106.590263</td>\n",
       "      <td>49915500</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>14/9/2015</td>\n",
       "      <td>116.580002</td>\n",
       "      <td>116.889999</td>\n",
       "      <td>114.860001</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>16/9/2015</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>17/9/2015</td>\n",
       "      <td>115.660004</td>\n",
       "      <td>116.489998</td>\n",
       "      <td>113.720001</td>\n",
       "      <td>113.919998</td>\n",
       "      <td>106.319611</td>\n",
       "      <td>64112600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>18/9/2015</td>\n",
       "      <td>112.209999</td>\n",
       "      <td>114.300003</td>\n",
       "      <td>111.870003</td>\n",
       "      <td>113.449997</td>\n",
       "      <td>105.880959</td>\n",
       "      <td>74285300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21/9/2015</td>\n",
       "      <td>113.669998</td>\n",
       "      <td>115.370003</td>\n",
       "      <td>113.660004</td>\n",
       "      <td>115.209999</td>\n",
       "      <td>107.523544</td>\n",
       "      <td>50222000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>22/9/2015</td>\n",
       "      <td>113.379997</td>\n",
       "      <td>114.180000</td>\n",
       "      <td>112.519997</td>\n",
       "      <td>113.400002</td>\n",
       "      <td>105.834305</td>\n",
       "      <td>50346200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>23/9/2015</td>\n",
       "      <td>113.629997</td>\n",
       "      <td>114.720001</td>\n",
       "      <td>113.300003</td>\n",
       "      <td>114.320000</td>\n",
       "      <td>106.692917</td>\n",
       "      <td>35756700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>24/9/2015</td>\n",
       "      <td>113.250000</td>\n",
       "      <td>115.500000</td>\n",
       "      <td>112.370003</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>107.327568</td>\n",
       "      <td>50219500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>25/9/2015</td>\n",
       "      <td>116.440002</td>\n",
       "      <td>116.690002</td>\n",
       "      <td>114.019997</td>\n",
       "      <td>114.709999</td>\n",
       "      <td>107.056892</td>\n",
       "      <td>56151900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>28/9/2015</td>\n",
       "      <td>113.849998</td>\n",
       "      <td>114.570000</td>\n",
       "      <td>112.440002</td>\n",
       "      <td>112.440002</td>\n",
       "      <td>104.938339</td>\n",
       "      <td>52109000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>29/9/2015</td>\n",
       "      <td>112.830002</td>\n",
       "      <td>113.510002</td>\n",
       "      <td>107.860001</td>\n",
       "      <td>109.059998</td>\n",
       "      <td>101.783844</td>\n",
       "      <td>73365400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>30/9/2015</td>\n",
       "      <td>110.169998</td>\n",
       "      <td>111.540001</td>\n",
       "      <td>108.730003</td>\n",
       "      <td>110.300003</td>\n",
       "      <td>102.941124</td>\n",
       "      <td>66473000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1/10/2015</td>\n",
       "      <td>109.070000</td>\n",
       "      <td>109.620003</td>\n",
       "      <td>107.309998</td>\n",
       "      <td>109.580002</td>\n",
       "      <td>102.269157</td>\n",
       "      <td>63929100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2/10/2015</td>\n",
       "      <td>108.010002</td>\n",
       "      <td>111.010002</td>\n",
       "      <td>107.550003</td>\n",
       "      <td>110.379997</td>\n",
       "      <td>103.015785</td>\n",
       "      <td>58019800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>5/10/2015</td>\n",
       "      <td>109.879997</td>\n",
       "      <td>111.370003</td>\n",
       "      <td>109.070000</td>\n",
       "      <td>110.779999</td>\n",
       "      <td>103.389107</td>\n",
       "      <td>52064700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>6/10/2015</td>\n",
       "      <td>110.629997</td>\n",
       "      <td>111.739998</td>\n",
       "      <td>109.769997</td>\n",
       "      <td>111.309998</td>\n",
       "      <td>103.883736</td>\n",
       "      <td>48196800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>7/10/2015</td>\n",
       "      <td>111.739998</td>\n",
       "      <td>111.769997</td>\n",
       "      <td>109.410004</td>\n",
       "      <td>110.779999</td>\n",
       "      <td>103.389107</td>\n",
       "      <td>46765600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>8/10/2015</td>\n",
       "      <td>110.190002</td>\n",
       "      <td>110.190002</td>\n",
       "      <td>108.209999</td>\n",
       "      <td>109.500000</td>\n",
       "      <td>102.194481</td>\n",
       "      <td>61979600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>9/10/2015</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>112.279999</td>\n",
       "      <td>109.489998</td>\n",
       "      <td>112.120003</td>\n",
       "      <td>104.639717</td>\n",
       "      <td>52766100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>12/10/2015</td>\n",
       "      <td>112.730003</td>\n",
       "      <td>112.750000</td>\n",
       "      <td>111.440002</td>\n",
       "      <td>111.599998</td>\n",
       "      <td>104.154366</td>\n",
       "      <td>30467200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>13/10/2015</td>\n",
       "      <td>110.820000</td>\n",
       "      <td>112.449997</td>\n",
       "      <td>110.680000</td>\n",
       "      <td>111.790001</td>\n",
       "      <td>104.331711</td>\n",
       "      <td>33049300</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>977</th>\n",
       "      <td>22/7/2019</td>\n",
       "      <td>203.649994</td>\n",
       "      <td>207.229996</td>\n",
       "      <td>203.610001</td>\n",
       "      <td>207.220001</td>\n",
       "      <td>206.435654</td>\n",
       "      <td>22277900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>23/7/2019</td>\n",
       "      <td>208.460007</td>\n",
       "      <td>208.910004</td>\n",
       "      <td>207.289993</td>\n",
       "      <td>208.839996</td>\n",
       "      <td>208.049515</td>\n",
       "      <td>18355200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>979</th>\n",
       "      <td>24/7/2019</td>\n",
       "      <td>207.669998</td>\n",
       "      <td>209.149994</td>\n",
       "      <td>207.169998</td>\n",
       "      <td>208.669998</td>\n",
       "      <td>207.880173</td>\n",
       "      <td>14991600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>980</th>\n",
       "      <td>25/7/2019</td>\n",
       "      <td>208.889999</td>\n",
       "      <td>209.240005</td>\n",
       "      <td>206.729996</td>\n",
       "      <td>207.020004</td>\n",
       "      <td>206.236420</td>\n",
       "      <td>13909600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>26/7/2019</td>\n",
       "      <td>207.479996</td>\n",
       "      <td>209.729996</td>\n",
       "      <td>207.139999</td>\n",
       "      <td>207.740005</td>\n",
       "      <td>206.953690</td>\n",
       "      <td>17618900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>29/7/2019</td>\n",
       "      <td>208.460007</td>\n",
       "      <td>210.639999</td>\n",
       "      <td>208.440002</td>\n",
       "      <td>209.679993</td>\n",
       "      <td>208.886337</td>\n",
       "      <td>21673400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>30/7/2019</td>\n",
       "      <td>208.759995</td>\n",
       "      <td>210.160004</td>\n",
       "      <td>207.309998</td>\n",
       "      <td>208.779999</td>\n",
       "      <td>207.989746</td>\n",
       "      <td>33935700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>984</th>\n",
       "      <td>31/7/2019</td>\n",
       "      <td>216.419998</td>\n",
       "      <td>221.369995</td>\n",
       "      <td>211.300003</td>\n",
       "      <td>213.039993</td>\n",
       "      <td>212.233627</td>\n",
       "      <td>69281400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>1/8/2019</td>\n",
       "      <td>213.899994</td>\n",
       "      <td>218.029999</td>\n",
       "      <td>206.740005</td>\n",
       "      <td>208.429993</td>\n",
       "      <td>207.641068</td>\n",
       "      <td>54017900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>2/8/2019</td>\n",
       "      <td>205.529999</td>\n",
       "      <td>206.429993</td>\n",
       "      <td>201.630005</td>\n",
       "      <td>204.020004</td>\n",
       "      <td>203.247772</td>\n",
       "      <td>40862100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>987</th>\n",
       "      <td>5/8/2019</td>\n",
       "      <td>197.990005</td>\n",
       "      <td>198.649994</td>\n",
       "      <td>192.580002</td>\n",
       "      <td>193.339996</td>\n",
       "      <td>192.608185</td>\n",
       "      <td>52393000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>6/8/2019</td>\n",
       "      <td>196.309998</td>\n",
       "      <td>198.070007</td>\n",
       "      <td>194.039993</td>\n",
       "      <td>197.000000</td>\n",
       "      <td>196.254333</td>\n",
       "      <td>35824800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989</th>\n",
       "      <td>7/8/2019</td>\n",
       "      <td>195.410004</td>\n",
       "      <td>199.559998</td>\n",
       "      <td>193.820007</td>\n",
       "      <td>199.039993</td>\n",
       "      <td>198.286606</td>\n",
       "      <td>33364400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990</th>\n",
       "      <td>8/8/2019</td>\n",
       "      <td>200.199997</td>\n",
       "      <td>203.529999</td>\n",
       "      <td>199.389999</td>\n",
       "      <td>203.429993</td>\n",
       "      <td>202.659988</td>\n",
       "      <td>27009500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>9/8/2019</td>\n",
       "      <td>201.300003</td>\n",
       "      <td>202.759995</td>\n",
       "      <td>199.289993</td>\n",
       "      <td>200.990005</td>\n",
       "      <td>200.990005</td>\n",
       "      <td>24619700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>12/8/2019</td>\n",
       "      <td>199.619995</td>\n",
       "      <td>202.050003</td>\n",
       "      <td>199.149994</td>\n",
       "      <td>200.479996</td>\n",
       "      <td>200.479996</td>\n",
       "      <td>22474900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>13/8/2019</td>\n",
       "      <td>201.020004</td>\n",
       "      <td>212.139999</td>\n",
       "      <td>200.479996</td>\n",
       "      <td>208.970001</td>\n",
       "      <td>208.970001</td>\n",
       "      <td>47218500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>14/8/2019</td>\n",
       "      <td>203.160004</td>\n",
       "      <td>206.440002</td>\n",
       "      <td>202.589996</td>\n",
       "      <td>202.750000</td>\n",
       "      <td>202.750000</td>\n",
       "      <td>36547400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>15/8/2019</td>\n",
       "      <td>203.460007</td>\n",
       "      <td>205.139999</td>\n",
       "      <td>199.669998</td>\n",
       "      <td>201.740005</td>\n",
       "      <td>201.740005</td>\n",
       "      <td>27227400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>16/8/2019</td>\n",
       "      <td>204.279999</td>\n",
       "      <td>207.160004</td>\n",
       "      <td>203.839996</td>\n",
       "      <td>206.500000</td>\n",
       "      <td>206.500000</td>\n",
       "      <td>27620400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>19/8/2019</td>\n",
       "      <td>210.619995</td>\n",
       "      <td>212.729996</td>\n",
       "      <td>210.029999</td>\n",
       "      <td>210.350006</td>\n",
       "      <td>210.350006</td>\n",
       "      <td>24413600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>20/8/2019</td>\n",
       "      <td>210.880005</td>\n",
       "      <td>213.350006</td>\n",
       "      <td>210.320007</td>\n",
       "      <td>210.360001</td>\n",
       "      <td>210.360001</td>\n",
       "      <td>26884300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>21/8/2019</td>\n",
       "      <td>212.990005</td>\n",
       "      <td>213.649994</td>\n",
       "      <td>211.600006</td>\n",
       "      <td>212.639999</td>\n",
       "      <td>212.639999</td>\n",
       "      <td>21535400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>22/8/2019</td>\n",
       "      <td>213.190002</td>\n",
       "      <td>214.440002</td>\n",
       "      <td>210.750000</td>\n",
       "      <td>212.460007</td>\n",
       "      <td>212.460007</td>\n",
       "      <td>22253700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1001</th>\n",
       "      <td>23/8/2019</td>\n",
       "      <td>209.429993</td>\n",
       "      <td>212.050003</td>\n",
       "      <td>201.000000</td>\n",
       "      <td>202.639999</td>\n",
       "      <td>202.639999</td>\n",
       "      <td>46818000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1002</th>\n",
       "      <td>26/8/2019</td>\n",
       "      <td>205.860001</td>\n",
       "      <td>207.190002</td>\n",
       "      <td>205.059998</td>\n",
       "      <td>206.490005</td>\n",
       "      <td>206.490005</td>\n",
       "      <td>26043600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1003</th>\n",
       "      <td>27/8/2019</td>\n",
       "      <td>207.860001</td>\n",
       "      <td>208.550003</td>\n",
       "      <td>203.529999</td>\n",
       "      <td>204.160004</td>\n",
       "      <td>204.160004</td>\n",
       "      <td>25873300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1004</th>\n",
       "      <td>28/8/2019</td>\n",
       "      <td>204.100006</td>\n",
       "      <td>205.720001</td>\n",
       "      <td>203.320007</td>\n",
       "      <td>205.529999</td>\n",
       "      <td>205.529999</td>\n",
       "      <td>15938800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>29/8/2019</td>\n",
       "      <td>208.500000</td>\n",
       "      <td>209.320007</td>\n",
       "      <td>206.660004</td>\n",
       "      <td>209.009995</td>\n",
       "      <td>209.009995</td>\n",
       "      <td>20990500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1006</th>\n",
       "      <td>30/8/2019</td>\n",
       "      <td>210.160004</td>\n",
       "      <td>210.449997</td>\n",
       "      <td>207.199997</td>\n",
       "      <td>208.740005</td>\n",
       "      <td>208.740005</td>\n",
       "      <td>21143400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1007 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date        Open        High         Low       Close   Adj Close  \\\n",
       "0       1/9/2015  110.150002  111.879997  107.360001  107.720001  100.533249   \n",
       "1       2/9/2015  110.230003  112.339996  109.129997  112.339996  104.845024   \n",
       "2       3/9/2015  112.489998  112.779999  110.040001  110.370003  103.006447   \n",
       "3       4/9/2015  108.970001  110.449997  108.510002  109.269997  101.979836   \n",
       "4       8/9/2015  111.750000  112.559998  110.320000  112.309998  104.817017   \n",
       "5       9/9/2015  113.760002  114.019997  109.769997  110.150002  102.801125   \n",
       "6      10/9/2015  110.269997  113.279999  109.900002  112.570000  105.059677   \n",
       "7      11/9/2015  111.790001  114.209999  111.760002  114.209999  106.590263   \n",
       "8      14/9/2015  116.580002  116.889999  114.860001  115.309998  107.616867   \n",
       "9      15/9/2015  115.930000  116.529999  114.419998  116.279999  108.522148   \n",
       "10     16/9/2015  116.250000  116.540001  115.440002  116.410004  108.643478   \n",
       "11     17/9/2015  115.660004  116.489998  113.720001  113.919998  106.319611   \n",
       "12     18/9/2015  112.209999  114.300003  111.870003  113.449997  105.880959   \n",
       "13     21/9/2015  113.669998  115.370003  113.660004  115.209999  107.523544   \n",
       "14     22/9/2015  113.379997  114.180000  112.519997  113.400002  105.834305   \n",
       "15     23/9/2015  113.629997  114.720001  113.300003  114.320000  106.692917   \n",
       "16     24/9/2015  113.250000  115.500000  112.370003  115.000000  107.327568   \n",
       "17     25/9/2015  116.440002  116.690002  114.019997  114.709999  107.056892   \n",
       "18     28/9/2015  113.849998  114.570000  112.440002  112.440002  104.938339   \n",
       "19     29/9/2015  112.830002  113.510002  107.860001  109.059998  101.783844   \n",
       "20     30/9/2015  110.169998  111.540001  108.730003  110.300003  102.941124   \n",
       "21     1/10/2015  109.070000  109.620003  107.309998  109.580002  102.269157   \n",
       "22     2/10/2015  108.010002  111.010002  107.550003  110.379997  103.015785   \n",
       "23     5/10/2015  109.879997  111.370003  109.070000  110.779999  103.389107   \n",
       "24     6/10/2015  110.629997  111.739998  109.769997  111.309998  103.883736   \n",
       "25     7/10/2015  111.739998  111.769997  109.410004  110.779999  103.389107   \n",
       "26     8/10/2015  110.190002  110.190002  108.209999  109.500000  102.194481   \n",
       "27     9/10/2015  110.000000  112.279999  109.489998  112.120003  104.639717   \n",
       "28    12/10/2015  112.730003  112.750000  111.440002  111.599998  104.154366   \n",
       "29    13/10/2015  110.820000  112.449997  110.680000  111.790001  104.331711   \n",
       "...          ...         ...         ...         ...         ...         ...   \n",
       "977    22/7/2019  203.649994  207.229996  203.610001  207.220001  206.435654   \n",
       "978    23/7/2019  208.460007  208.910004  207.289993  208.839996  208.049515   \n",
       "979    24/7/2019  207.669998  209.149994  207.169998  208.669998  207.880173   \n",
       "980    25/7/2019  208.889999  209.240005  206.729996  207.020004  206.236420   \n",
       "981    26/7/2019  207.479996  209.729996  207.139999  207.740005  206.953690   \n",
       "982    29/7/2019  208.460007  210.639999  208.440002  209.679993  208.886337   \n",
       "983    30/7/2019  208.759995  210.160004  207.309998  208.779999  207.989746   \n",
       "984    31/7/2019  216.419998  221.369995  211.300003  213.039993  212.233627   \n",
       "985     1/8/2019  213.899994  218.029999  206.740005  208.429993  207.641068   \n",
       "986     2/8/2019  205.529999  206.429993  201.630005  204.020004  203.247772   \n",
       "987     5/8/2019  197.990005  198.649994  192.580002  193.339996  192.608185   \n",
       "988     6/8/2019  196.309998  198.070007  194.039993  197.000000  196.254333   \n",
       "989     7/8/2019  195.410004  199.559998  193.820007  199.039993  198.286606   \n",
       "990     8/8/2019  200.199997  203.529999  199.389999  203.429993  202.659988   \n",
       "991     9/8/2019  201.300003  202.759995  199.289993  200.990005  200.990005   \n",
       "992    12/8/2019  199.619995  202.050003  199.149994  200.479996  200.479996   \n",
       "993    13/8/2019  201.020004  212.139999  200.479996  208.970001  208.970001   \n",
       "994    14/8/2019  203.160004  206.440002  202.589996  202.750000  202.750000   \n",
       "995    15/8/2019  203.460007  205.139999  199.669998  201.740005  201.740005   \n",
       "996    16/8/2019  204.279999  207.160004  203.839996  206.500000  206.500000   \n",
       "997    19/8/2019  210.619995  212.729996  210.029999  210.350006  210.350006   \n",
       "998    20/8/2019  210.880005  213.350006  210.320007  210.360001  210.360001   \n",
       "999    21/8/2019  212.990005  213.649994  211.600006  212.639999  212.639999   \n",
       "1000   22/8/2019  213.190002  214.440002  210.750000  212.460007  212.460007   \n",
       "1001   23/8/2019  209.429993  212.050003  201.000000  202.639999  202.639999   \n",
       "1002   26/8/2019  205.860001  207.190002  205.059998  206.490005  206.490005   \n",
       "1003   27/8/2019  207.860001  208.550003  203.529999  204.160004  204.160004   \n",
       "1004   28/8/2019  204.100006  205.720001  203.320007  205.529999  205.529999   \n",
       "1005   29/8/2019  208.500000  209.320007  206.660004  209.009995  209.009995   \n",
       "1006   30/8/2019  210.160004  210.449997  207.199997  208.740005  208.740005   \n",
       "\n",
       "        Volume  \n",
       "0     76845900  \n",
       "1     61888800  \n",
       "2     53233900  \n",
       "3     49996300  \n",
       "4     54843600  \n",
       "5     85010800  \n",
       "6     62892800  \n",
       "7     49915500  \n",
       "8     58363400  \n",
       "9     43341200  \n",
       "10    37173500  \n",
       "11    64112600  \n",
       "12    74285300  \n",
       "13    50222000  \n",
       "14    50346200  \n",
       "15    35756700  \n",
       "16    50219500  \n",
       "17    56151900  \n",
       "18    52109000  \n",
       "19    73365400  \n",
       "20    66473000  \n",
       "21    63929100  \n",
       "22    58019800  \n",
       "23    52064700  \n",
       "24    48196800  \n",
       "25    46765600  \n",
       "26    61979600  \n",
       "27    52766100  \n",
       "28    30467200  \n",
       "29    33049300  \n",
       "...        ...  \n",
       "977   22277900  \n",
       "978   18355200  \n",
       "979   14991600  \n",
       "980   13909600  \n",
       "981   17618900  \n",
       "982   21673400  \n",
       "983   33935700  \n",
       "984   69281400  \n",
       "985   54017900  \n",
       "986   40862100  \n",
       "987   52393000  \n",
       "988   35824800  \n",
       "989   33364400  \n",
       "990   27009500  \n",
       "991   24619700  \n",
       "992   22474900  \n",
       "993   47218500  \n",
       "994   36547400  \n",
       "995   27227400  \n",
       "996   27620400  \n",
       "997   24413600  \n",
       "998   26884300  \n",
       "999   21535400  \n",
       "1000  22253700  \n",
       "1001  46818000  \n",
       "1002  26043600  \n",
       "1003  25873300  \n",
       "1004  15938800  \n",
       "1005  20990500  \n",
       "1006  21143400  \n",
       "\n",
       "[1007 rows x 7 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = aapl[aapl[\"Date\"]"
   ]
  }
 ],
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