05.AR and MA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"fb.csv\",parse_dates=['Date'],index_col='Date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.head of                   Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2014-08-11   73.459999   73.910004   73.059998   73.440002   73.440002   \n",
       "2014-08-12   73.089996   73.330002   72.220001   72.830002   72.830002   \n",
       "2014-08-13   73.120003   74.250000   73.050003   73.769997   73.769997   \n",
       "2014-08-14   73.970001   74.379997   73.690002   74.300003   74.300003   \n",
       "2014-08-15   74.320000   74.650002   73.000000   73.629997   73.629997   \n",
       "2014-08-18   74.000000   74.720001   73.959999   74.589996   74.589996   \n",
       "2014-08-19   74.809998   75.580002   74.510002   75.290001   75.290001   \n",
       "2014-08-20   74.970001   75.180000   74.620003   74.809998   74.809998   \n",
       "2014-08-21   74.919998   75.190002   74.410004   74.570000   74.570000   \n",
       "2014-08-22   74.339996   74.730003   73.570000   74.570000   74.570000   \n",
       "2014-08-25   74.940002   75.279999   74.790001   75.019997   75.019997   \n",
       "2014-08-26   75.000000   75.989998   74.730003   75.959999   75.959999   \n",
       "2014-08-27   75.269997   75.489998   74.459999   74.629997   74.629997   \n",
       "2014-08-28   74.000000   74.430000   73.730003   73.860001   73.860001   \n",
       "2014-08-29   74.300003   74.820000   74.010002   74.820000   74.820000   \n",
       "2014-09-02   75.010002   76.699997   74.820000   76.680000   76.680000   \n",
       "2014-09-03   77.139999   77.480003   75.599998   75.830002   75.830002   \n",
       "2014-09-04   75.889999   76.930000   75.529999   75.949997   75.949997   \n",
       "2014-09-05   76.099998   77.379997   75.599998   77.260002   77.260002   \n",
       "2014-09-08   77.260002   78.169998   77.010002   77.889999   77.889999   \n",
       "2014-09-09   77.589996   78.169998   76.199997   76.669998   76.669998   \n",
       "2014-09-10   76.519997   77.949997   76.510002   77.430000   77.430000   \n",
       "2014-09-11   77.129997   78.360001   77.050003   77.919998   77.919998   \n",
       "2014-09-12   78.019997   78.300003   77.099998   77.480003   77.480003   \n",
       "2014-09-15   77.150002   77.250000   73.430000   74.580002   74.580002   \n",
       "2014-09-16   73.519997   76.230003   73.070000   76.080002   76.080002   \n",
       "2014-09-17   75.959999   77.250000   75.570000   76.430000   76.430000   \n",
       "2014-09-18   76.769997   77.330002   76.519997   77.000000   77.000000   \n",
       "2014-09-19   77.400002   78.300003   76.440002   77.910004   77.910004   \n",
       "2014-09-22   77.000000   77.529999   75.949997   76.800003   76.800003   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2019-06-28  190.550003  193.199997  189.940002  193.000000  193.000000   \n",
       "2019-07-01  195.210007  195.279999  191.929993  193.000000  193.000000   \n",
       "2019-07-02  193.000000  195.000000  192.710007  195.000000  195.000000   \n",
       "2019-07-03  194.160004  197.399994  194.160004  197.199997  197.199997   \n",
       "2019-07-05  196.179993  197.070007  194.169998  196.399994  196.399994   \n",
       "2019-07-08  195.190002  196.679993  193.639999  195.759995  195.759995   \n",
       "2019-07-09  194.970001  199.460007  194.889999  199.210007  199.210007   \n",
       "2019-07-10  200.000000  202.960007  199.669998  202.729996  202.729996   \n",
       "2019-07-11  203.259995  203.800003  200.210007  201.229996  201.229996   \n",
       "2019-07-12  199.679993  205.300003  199.160004  204.869995  204.869995   \n",
       "2019-07-15  204.250000  205.330002  201.820007  203.910004  203.910004   \n",
       "2019-07-16  203.889999  205.470001  203.100006  203.839996  203.839996   \n",
       "2019-07-17  204.179993  204.360001  201.589996  201.800003  201.800003   \n",
       "2019-07-18  200.149994  202.470001  199.380005  200.779999  200.779999   \n",
       "2019-07-19  202.179993  202.330002  198.070007  198.360001  198.360001   \n",
       "2019-07-22  199.910004  202.570007  198.809998  202.320007  202.320007   \n",
       "2019-07-23  202.839996  204.240005  200.960007  202.360001  202.360001   \n",
       "2019-07-24  197.630005  204.809998  197.220001  204.660004  204.660004   \n",
       "2019-07-25  206.699997  208.660004  198.259995  200.710007  200.710007   \n",
       "2019-07-26  200.190002  202.880005  196.250000  199.750000  199.750000   \n",
       "2019-07-29  199.000000  199.630005  195.300003  195.940002  195.940002   \n",
       "2019-07-30  195.389999  198.710007  193.500000  197.039993  197.039993   \n",
       "2019-07-31  196.949997  198.759995  192.679993  194.229996  194.229996   \n",
       "2019-08-01  194.169998  198.470001  190.880005  192.729996  192.729996   \n",
       "2019-08-02  191.100006  192.619995  188.070007  189.020004  189.020004   \n",
       "2019-08-05  184.690002  185.669998  179.339996  181.729996  181.729996   \n",
       "2019-08-06  183.690002  185.789993  183.089996  184.509995  184.509995   \n",
       "2019-08-07  183.600006  186.369995  181.220001  185.149994  185.149994   \n",
       "2019-08-08  186.619995  190.339996  184.050003  190.160004  190.160004   \n",
       "2019-08-09  190.000000  190.979996  187.119995  187.850006  187.850006   \n",
       "\n",
       "              Volume  \n",
       "Date                  \n",
       "2014-08-11  24591000  \n",
       "2014-08-12  27419000  \n",
       "2014-08-13  29266000  \n",
       "2014-08-14  22207000  \n",
       "2014-08-15  38846600  \n",
       "2014-08-18  23974000  \n",
       "2014-08-19  26679000  \n",
       "2014-08-20  22917000  \n",
       "2014-08-21  20102000  \n",
       "2014-08-22  20897000  \n",
       "2014-08-25  19734000  \n",
       "2014-08-26  23993000  \n",
       "2014-08-27  36323000  \n",
       "2014-08-28  21947000  \n",
       "2014-08-29  26241000  \n",
       "2014-09-02  34979000  \n",
       "2014-09-03  32389000  \n",
       "2014-09-04  26676000  \n",
       "2014-09-05  29476000  \n",
       "2014-09-08  28183000  \n",
       "2014-09-09  28882000  \n",
       "2014-09-10  29909000  \n",
       "2014-09-11  32219000  \n",
       "2014-09-12  26676800  \n",
       "2014-09-15  49679000  \n",
       "2014-09-16  37742000  \n",
       "2014-09-17  28693000  \n",
       "2014-09-18  23031000  \n",
       "2014-09-19  76671000  \n",
       "2014-09-22  31961000  \n",
       "...              ...  \n",
       "2019-06-28  16378900  \n",
       "2019-07-01  14204700  \n",
       "2019-07-02   9050000  \n",
       "2019-07-03  10246100  \n",
       "2019-07-05  11164100  \n",
       "2019-07-08   9723900  \n",
       "2019-07-09  14698600  \n",
       "2019-07-10  20571700  \n",
       "2019-07-11  13678500  \n",
       "2019-07-12  15366300  \n",
       "2019-07-15  16030300  \n",
       "2019-07-16  12132700  \n",
       "2019-07-17  12083700  \n",
       "2019-07-18  11956600  \n",
       "2019-07-19  12098300  \n",
       "2019-07-22  13589000  \n",
       "2019-07-23  14583700  \n",
       "2019-07-24  32532500  \n",
       "2019-07-25  39889900  \n",
       "2019-07-26  24434000  \n",
       "2019-07-29  16530800  \n",
       "2019-07-30  11903600  \n",
       "2019-07-31  14593500  \n",
       "2019-08-01  17777000  \n",
       "2019-08-02  15297000  \n",
       "2019-08-05  23086700  \n",
       "2019-08-06  18035700  \n",
       "2019-08-07  15833200  \n",
       "2019-08-08  14828900  \n",
       "2019-08-09  10507300  \n",
       "\n",
       "[1259 rows x 6 columns]>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-08-11</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-12</th>\n",
       "      <td>73.459999</td>\n",
       "      <td>73.910004</td>\n",
       "      <td>73.059998</td>\n",
       "      <td>73.440002</td>\n",
       "      <td>73.440002</td>\n",
       "      <td>24591000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-13</th>\n",
       "      <td>73.089996</td>\n",
       "      <td>73.330002</td>\n",
       "      <td>72.220001</td>\n",
       "      <td>72.830002</td>\n",
       "      <td>72.830002</td>\n",
       "      <td>27419000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-14</th>\n",
       "      <td>73.120003</td>\n",
       "      <td>74.250000</td>\n",
       "      <td>73.050003</td>\n",
       "      <td>73.769997</td>\n",
       "      <td>73.769997</td>\n",
       "      <td>29266000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-15</th>\n",
       "      <td>73.970001</td>\n",
       "      <td>74.379997</td>\n",
       "      <td>73.690002</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>22207000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-18</th>\n",
       "      <td>74.320000</td>\n",
       "      <td>74.650002</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>73.629997</td>\n",
       "      <td>73.629997</td>\n",
       "      <td>38846600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-19</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>74.720001</td>\n",
       "      <td>73.959999</td>\n",
       "      <td>74.589996</td>\n",
       "      <td>74.589996</td>\n",
       "      <td>23974000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-20</th>\n",
       "      <td>74.809998</td>\n",
       "      <td>75.580002</td>\n",
       "      <td>74.510002</td>\n",
       "      <td>75.290001</td>\n",
       "      <td>75.290001</td>\n",
       "      <td>26679000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-21</th>\n",
       "      <td>74.970001</td>\n",
       "      <td>75.180000</td>\n",
       "      <td>74.620003</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>22917000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-22</th>\n",
       "      <td>74.919998</td>\n",
       "      <td>75.190002</td>\n",
       "      <td>74.410004</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>20102000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-25</th>\n",
       "      <td>74.339996</td>\n",
       "      <td>74.730003</td>\n",
       "      <td>73.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>20897000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-26</th>\n",
       "      <td>74.940002</td>\n",
       "      <td>75.279999</td>\n",
       "      <td>74.790001</td>\n",
       "      <td>75.019997</td>\n",
       "      <td>75.019997</td>\n",
       "      <td>19734000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>75.000000</td>\n",
       "      <td>75.989998</td>\n",
       "      <td>74.730003</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>23993000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>75.269997</td>\n",
       "      <td>75.489998</td>\n",
       "      <td>74.459999</td>\n",
       "      <td>74.629997</td>\n",
       "      <td>74.629997</td>\n",
       "      <td>36323000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>74.430000</td>\n",
       "      <td>73.730003</td>\n",
       "      <td>73.860001</td>\n",
       "      <td>73.860001</td>\n",
       "      <td>21947000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-02</th>\n",
       "      <td>74.300003</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>74.010002</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>26241000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-03</th>\n",
       "      <td>75.010002</td>\n",
       "      <td>76.699997</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>76.680000</td>\n",
       "      <td>76.680000</td>\n",
       "      <td>34979000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-04</th>\n",
       "      <td>77.139999</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>75.599998</td>\n",
       "      <td>75.830002</td>\n",
       "      <td>75.830002</td>\n",
       "      <td>32389000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-05</th>\n",
       "      <td>75.889999</td>\n",
       "      <td>76.930000</td>\n",
       "      <td>75.529999</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>26676000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-08</th>\n",
       "      <td>76.099998</td>\n",
       "      <td>77.379997</td>\n",
       "      <td>75.599998</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>29476000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-09</th>\n",
       "      <td>77.260002</td>\n",
       "      <td>78.169998</td>\n",
       "      <td>77.010002</td>\n",
       "      <td>77.889999</td>\n",
       "      <td>77.889999</td>\n",
       "      <td>28183000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-10</th>\n",
       "      <td>77.589996</td>\n",
       "      <td>78.169998</td>\n",
       "      <td>76.199997</td>\n",
       "      <td>76.669998</td>\n",
       "      <td>76.669998</td>\n",
       "      <td>28882000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-11</th>\n",
       "      <td>76.519997</td>\n",
       "      <td>77.949997</td>\n",
       "      <td>76.510002</td>\n",
       "      <td>77.430000</td>\n",
       "      <td>77.430000</td>\n",
       "      <td>29909000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-12</th>\n",
       "      <td>77.129997</td>\n",
       "      <td>78.360001</td>\n",
       "      <td>77.050003</td>\n",
       "      <td>77.919998</td>\n",
       "      <td>77.919998</td>\n",
       "      <td>32219000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-15</th>\n",
       "      <td>78.019997</td>\n",
       "      <td>78.300003</td>\n",
       "      <td>77.099998</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>26676800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-16</th>\n",
       "      <td>77.150002</td>\n",
       "      <td>77.250000</td>\n",
       "      <td>73.430000</td>\n",
       "      <td>74.580002</td>\n",
       "      <td>74.580002</td>\n",
       "      <td>49679000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-17</th>\n",
       "      <td>73.519997</td>\n",
       "      <td>76.230003</td>\n",
       "      <td>73.070000</td>\n",
       "      <td>76.080002</td>\n",
       "      <td>76.080002</td>\n",
       "      <td>37742000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-18</th>\n",
       "      <td>75.959999</td>\n",
       "      <td>77.250000</td>\n",
       "      <td>75.570000</td>\n",
       "      <td>76.430000</td>\n",
       "      <td>76.430000</td>\n",
       "      <td>28693000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-19</th>\n",
       "      <td>76.769997</td>\n",
       "      <td>77.330002</td>\n",
       "      <td>76.519997</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>23031000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-22</th>\n",
       "      <td>77.400002</td>\n",
       "      <td>78.300003</td>\n",
       "      <td>76.440002</td>\n",
       "      <td>77.910004</td>\n",
       "      <td>77.910004</td>\n",
       "      <td>76671000.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>189.880005</td>\n",
       "      <td>198.880005</td>\n",
       "      <td>188.270004</td>\n",
       "      <td>189.500000</td>\n",
       "      <td>189.500000</td>\n",
       "      <td>11159000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>190.550003</td>\n",
       "      <td>193.199997</td>\n",
       "      <td>189.940002</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>16378900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>195.210007</td>\n",
       "      <td>195.279999</td>\n",
       "      <td>191.929993</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>14204700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>193.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>192.710007</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>9050000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>194.160004</td>\n",
       "      <td>197.399994</td>\n",
       "      <td>194.160004</td>\n",
       "      <td>197.199997</td>\n",
       "      <td>197.199997</td>\n",
       "      <td>10246100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>196.179993</td>\n",
       "      <td>197.070007</td>\n",
       "      <td>194.169998</td>\n",
       "      <td>196.399994</td>\n",
       "      <td>196.399994</td>\n",
       "      <td>11164100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-09</th>\n",
       "      <td>195.190002</td>\n",
       "      <td>196.679993</td>\n",
       "      <td>193.639999</td>\n",
       "      <td>195.759995</td>\n",
       "      <td>195.759995</td>\n",
       "      <td>9723900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-10</th>\n",
       "      <td>194.970001</td>\n",
       "      <td>199.460007</td>\n",
       "      <td>194.889999</td>\n",
       "      <td>199.210007</td>\n",
       "      <td>199.210007</td>\n",
       "      <td>14698600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-11</th>\n",
       "      <td>200.000000</td>\n",
       "      <td>202.960007</td>\n",
       "      <td>199.669998</td>\n",
       "      <td>202.729996</td>\n",
       "      <td>202.729996</td>\n",
       "      <td>20571700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-12</th>\n",
       "      <td>203.259995</td>\n",
       "      <td>203.800003</td>\n",
       "      <td>200.210007</td>\n",
       "      <td>201.229996</td>\n",
       "      <td>201.229996</td>\n",
       "      <td>13678500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>199.679993</td>\n",
       "      <td>205.300003</td>\n",
       "      <td>199.160004</td>\n",
       "      <td>204.869995</td>\n",
       "      <td>204.869995</td>\n",
       "      <td>15366300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>204.250000</td>\n",
       "      <td>205.330002</td>\n",
       "      <td>201.820007</td>\n",
       "      <td>203.910004</td>\n",
       "      <td>203.910004</td>\n",
       "      <td>16030300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>203.889999</td>\n",
       "      <td>205.470001</td>\n",
       "      <td>203.100006</td>\n",
       "      <td>203.839996</td>\n",
       "      <td>203.839996</td>\n",
       "      <td>12132700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>204.179993</td>\n",
       "      <td>204.360001</td>\n",
       "      <td>201.589996</td>\n",
       "      <td>201.800003</td>\n",
       "      <td>201.800003</td>\n",
       "      <td>12083700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>200.149994</td>\n",
       "      <td>202.470001</td>\n",
       "      <td>199.380005</td>\n",
       "      <td>200.779999</td>\n",
       "      <td>200.779999</td>\n",
       "      <td>11956600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-22</th>\n",
       "      <td>202.179993</td>\n",
       "      <td>202.330002</td>\n",
       "      <td>198.070007</td>\n",
       "      <td>198.360001</td>\n",
       "      <td>198.360001</td>\n",
       "      <td>12098300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-23</th>\n",
       "      <td>199.910004</td>\n",
       "      <td>202.570007</td>\n",
       "      <td>198.809998</td>\n",
       "      <td>202.320007</td>\n",
       "      <td>202.320007</td>\n",
       "      <td>13589000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-24</th>\n",
       "      <td>202.839996</td>\n",
       "      <td>204.240005</td>\n",
       "      <td>200.960007</td>\n",
       "      <td>202.360001</td>\n",
       "      <td>202.360001</td>\n",
       "      <td>14583700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-25</th>\n",
       "      <td>197.630005</td>\n",
       "      <td>204.809998</td>\n",
       "      <td>197.220001</td>\n",
       "      <td>204.660004</td>\n",
       "      <td>204.660004</td>\n",
       "      <td>32532500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-26</th>\n",
       "      <td>206.699997</td>\n",
       "      <td>208.660004</td>\n",
       "      <td>198.259995</td>\n",
       "      <td>200.710007</td>\n",
       "      <td>200.710007</td>\n",
       "      <td>39889900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-29</th>\n",
       "      <td>200.190002</td>\n",
       "      <td>202.880005</td>\n",
       "      <td>196.250000</td>\n",
       "      <td>199.750000</td>\n",
       "      <td>199.750000</td>\n",
       "      <td>24434000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-30</th>\n",
       "      <td>199.000000</td>\n",
       "      <td>199.630005</td>\n",
       "      <td>195.300003</td>\n",
       "      <td>195.940002</td>\n",
       "      <td>195.940002</td>\n",
       "      <td>16530800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-31</th>\n",
       "      <td>195.389999</td>\n",
       "      <td>198.710007</td>\n",
       "      <td>193.500000</td>\n",
       "      <td>197.039993</td>\n",
       "      <td>197.039993</td>\n",
       "      <td>11903600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-01</th>\n",
       "      <td>196.949997</td>\n",
       "      <td>198.759995</td>\n",
       "      <td>192.679993</td>\n",
       "      <td>194.229996</td>\n",
       "      <td>194.229996</td>\n",
       "      <td>14593500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-02</th>\n",
       "      <td>194.169998</td>\n",
       "      <td>198.470001</td>\n",
       "      <td>190.880005</td>\n",
       "      <td>192.729996</td>\n",
       "      <td>192.729996</td>\n",
       "      <td>17777000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-05</th>\n",
       "      <td>191.100006</td>\n",
       "      <td>192.619995</td>\n",
       "      <td>188.070007</td>\n",
       "      <td>189.020004</td>\n",
       "      <td>189.020004</td>\n",
       "      <td>15297000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-06</th>\n",
       "      <td>184.690002</td>\n",
       "      <td>185.669998</td>\n",
       "      <td>179.339996</td>\n",
       "      <td>181.729996</td>\n",
       "      <td>181.729996</td>\n",
       "      <td>23086700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-07</th>\n",
       "      <td>183.690002</td>\n",
       "      <td>185.789993</td>\n",
       "      <td>183.089996</td>\n",
       "      <td>184.509995</td>\n",
       "      <td>184.509995</td>\n",
       "      <td>18035700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-08</th>\n",
       "      <td>183.600006</td>\n",
       "      <td>186.369995</td>\n",
       "      <td>181.220001</td>\n",
       "      <td>185.149994</td>\n",
       "      <td>185.149994</td>\n",
       "      <td>15833200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-09</th>\n",
       "      <td>186.619995</td>\n",
       "      <td>190.339996</td>\n",
       "      <td>184.050003</td>\n",
       "      <td>190.160004</td>\n",
       "      <td>190.160004</td>\n",
       "      <td>14828900.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1259 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2014-08-11         NaN         NaN         NaN         NaN         NaN   \n",
       "2014-08-12   73.459999   73.910004   73.059998   73.440002   73.440002   \n",
       "2014-08-13   73.089996   73.330002   72.220001   72.830002   72.830002   \n",
       "2014-08-14   73.120003   74.250000   73.050003   73.769997   73.769997   \n",
       "2014-08-15   73.970001   74.379997   73.690002   74.300003   74.300003   \n",
       "2014-08-18   74.320000   74.650002   73.000000   73.629997   73.629997   \n",
       "2014-08-19   74.000000   74.720001   73.959999   74.589996   74.589996   \n",
       "2014-08-20   74.809998   75.580002   74.510002   75.290001   75.290001   \n",
       "2014-08-21   74.970001   75.180000   74.620003   74.809998   74.809998   \n",
       "2014-08-22   74.919998   75.190002   74.410004   74.570000   74.570000   \n",
       "2014-08-25   74.339996   74.730003   73.570000   74.570000   74.570000   \n",
       "2014-08-26   74.940002   75.279999   74.790001   75.019997   75.019997   \n",
       "2014-08-27   75.000000   75.989998   74.730003   75.959999   75.959999   \n",
       "2014-08-28   75.269997   75.489998   74.459999   74.629997   74.629997   \n",
       "2014-08-29   74.000000   74.430000   73.730003   73.860001   73.860001   \n",
       "2014-09-02   74.300003   74.820000   74.010002   74.820000   74.820000   \n",
       "2014-09-03   75.010002   76.699997   74.820000   76.680000   76.680000   \n",
       "2014-09-04   77.139999   77.480003   75.599998   75.830002   75.830002   \n",
       "2014-09-05   75.889999   76.930000   75.529999   75.949997   75.949997   \n",
       "2014-09-08   76.099998   77.379997   75.599998   77.260002   77.260002   \n",
       "2014-09-09   77.260002   78.169998   77.010002   77.889999   77.889999   \n",
       "2014-09-10   77.589996   78.169998   76.199997   76.669998   76.669998   \n",
       "2014-09-11   76.519997   77.949997   76.510002   77.430000   77.430000   \n",
       "2014-09-12   77.129997   78.360001   77.050003   77.919998   77.919998   \n",
       "2014-09-15   78.019997   78.300003   77.099998   77.480003   77.480003   \n",
       "2014-09-16   77.150002   77.250000   73.430000   74.580002   74.580002   \n",
       "2014-09-17   73.519997   76.230003   73.070000   76.080002   76.080002   \n",
       "2014-09-18   75.959999   77.250000   75.570000   76.430000   76.430000   \n",
       "2014-09-19   76.769997   77.330002   76.519997   77.000000   77.000000   \n",
       "2014-09-22   77.400002   78.300003   76.440002   77.910004   77.910004   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2019-06-28  189.880005  198.880005  188.270004  189.500000  189.500000   \n",
       "2019-07-01  190.550003  193.199997  189.940002  193.000000  193.000000   \n",
       "2019-07-02  195.210007  195.279999  191.929993  193.000000  193.000000   \n",
       "2019-07-03  193.000000  195.000000  192.710007  195.000000  195.000000   \n",
       "2019-07-05  194.160004  197.399994  194.160004  197.199997  197.199997   \n",
       "2019-07-08  196.179993  197.070007  194.169998  196.399994  196.399994   \n",
       "2019-07-09  195.190002  196.679993  193.639999  195.759995  195.759995   \n",
       "2019-07-10  194.970001  199.460007  194.889999  199.210007  199.210007   \n",
       "2019-07-11  200.000000  202.960007  199.669998  202.729996  202.729996   \n",
       "2019-07-12  203.259995  203.800003  200.210007  201.229996  201.229996   \n",
       "2019-07-15  199.679993  205.300003  199.160004  204.869995  204.869995   \n",
       "2019-07-16  204.250000  205.330002  201.820007  203.910004  203.910004   \n",
       "2019-07-17  203.889999  205.470001  203.100006  203.839996  203.839996   \n",
       "2019-07-18  204.179993  204.360001  201.589996  201.800003  201.800003   \n",
       "2019-07-19  200.149994  202.470001  199.380005  200.779999  200.779999   \n",
       "2019-07-22  202.179993  202.330002  198.070007  198.360001  198.360001   \n",
       "2019-07-23  199.910004  202.570007  198.809998  202.320007  202.320007   \n",
       "2019-07-24  202.839996  204.240005  200.960007  202.360001  202.360001   \n",
       "2019-07-25  197.630005  204.809998  197.220001  204.660004  204.660004   \n",
       "2019-07-26  206.699997  208.660004  198.259995  200.710007  200.710007   \n",
       "2019-07-29  200.190002  202.880005  196.250000  199.750000  199.750000   \n",
       "2019-07-30  199.000000  199.630005  195.300003  195.940002  195.940002   \n",
       "2019-07-31  195.389999  198.710007  193.500000  197.039993  197.039993   \n",
       "2019-08-01  196.949997  198.759995  192.679993  194.229996  194.229996   \n",
       "2019-08-02  194.169998  198.470001  190.880005  192.729996  192.729996   \n",
       "2019-08-05  191.100006  192.619995  188.070007  189.020004  189.020004   \n",
       "2019-08-06  184.690002  185.669998  179.339996  181.729996  181.729996   \n",
       "2019-08-07  183.690002  185.789993  183.089996  184.509995  184.509995   \n",
       "2019-08-08  183.600006  186.369995  181.220001  185.149994  185.149994   \n",
       "2019-08-09  186.619995  190.339996  184.050003  190.160004  190.160004   \n",
       "\n",
       "                Volume  \n",
       "Date                    \n",
       "2014-08-11         NaN  \n",
       "2014-08-12  24591000.0  \n",
       "2014-08-13  27419000.0  \n",
       "2014-08-14  29266000.0  \n",
       "2014-08-15  22207000.0  \n",
       "2014-08-18  38846600.0  \n",
       "2014-08-19  23974000.0  \n",
       "2014-08-20  26679000.0  \n",
       "2014-08-21  22917000.0  \n",
       "2014-08-22  20102000.0  \n",
       "2014-08-25  20897000.0  \n",
       "2014-08-26  19734000.0  \n",
       "2014-08-27  23993000.0  \n",
       "2014-08-28  36323000.0  \n",
       "2014-08-29  21947000.0  \n",
       "2014-09-02  26241000.0  \n",
       "2014-09-03  34979000.0  \n",
       "2014-09-04  32389000.0  \n",
       "2014-09-05  26676000.0  \n",
       "2014-09-08  29476000.0  \n",
       "2014-09-09  28183000.0  \n",
       "2014-09-10  28882000.0  \n",
       "2014-09-11  29909000.0  \n",
       "2014-09-12  32219000.0  \n",
       "2014-09-15  26676800.0  \n",
       "2014-09-16  49679000.0  \n",
       "2014-09-17  37742000.0  \n",
       "2014-09-18  28693000.0  \n",
       "2014-09-19  23031000.0  \n",
       "2014-09-22  76671000.0  \n",
       "...                ...  \n",
       "2019-06-28  11159000.0  \n",
       "2019-07-01  16378900.0  \n",
       "2019-07-02  14204700.0  \n",
       "2019-07-03   9050000.0  \n",
       "2019-07-05  10246100.0  \n",
       "2019-07-08  11164100.0  \n",
       "2019-07-09   9723900.0  \n",
       "2019-07-10  14698600.0  \n",
       "2019-07-11  20571700.0  \n",
       "2019-07-12  13678500.0  \n",
       "2019-07-15  15366300.0  \n",
       "2019-07-16  16030300.0  \n",
       "2019-07-17  12132700.0  \n",
       "2019-07-18  12083700.0  \n",
       "2019-07-19  11956600.0  \n",
       "2019-07-22  12098300.0  \n",
       "2019-07-23  13589000.0  \n",
       "2019-07-24  14583700.0  \n",
       "2019-07-25  32532500.0  \n",
       "2019-07-26  39889900.0  \n",
       "2019-07-29  24434000.0  \n",
       "2019-07-30  16530800.0  \n",
       "2019-07-31  11903600.0  \n",
       "2019-08-01  14593500.0  \n",
       "2019-08-02  17777000.0  \n",
       "2019-08-05  15297000.0  \n",
       "2019-08-06  23086700.0  \n",
       "2019-08-07  18035700.0  \n",
       "2019-08-08  15833200.0  \n",
       "2019-08-09  14828900.0  \n",
       "\n",
       "[1259 rows x 6 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-08-11</th>\n",
       "      <td>73.089996</td>\n",
       "      <td>73.330002</td>\n",
       "      <td>72.220001</td>\n",
       "      <td>72.830002</td>\n",
       "      <td>72.830002</td>\n",
       "      <td>27419000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-12</th>\n",
       "      <td>73.120003</td>\n",
       "      <td>74.250000</td>\n",
       "      <td>73.050003</td>\n",
       "      <td>73.769997</td>\n",
       "      <td>73.769997</td>\n",
       "      <td>29266000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-13</th>\n",
       "      <td>73.970001</td>\n",
       "      <td>74.379997</td>\n",
       "      <td>73.690002</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>22207000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-14</th>\n",
       "      <td>74.320000</td>\n",
       "      <td>74.650002</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>73.629997</td>\n",
       "      <td>73.629997</td>\n",
       "      <td>38846600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-15</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>74.720001</td>\n",
       "      <td>73.959999</td>\n",
       "      <td>74.589996</td>\n",
       "      <td>74.589996</td>\n",
       "      <td>23974000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-18</th>\n",
       "      <td>74.809998</td>\n",
       "      <td>75.580002</td>\n",
       "      <td>74.510002</td>\n",
       "      <td>75.290001</td>\n",
       "      <td>75.290001</td>\n",
       "      <td>26679000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-19</th>\n",
       "      <td>74.970001</td>\n",
       "      <td>75.180000</td>\n",
       "      <td>74.620003</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>22917000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-20</th>\n",
       "      <td>74.919998</td>\n",
       "      <td>75.190002</td>\n",
       "      <td>74.410004</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>20102000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-21</th>\n",
       "      <td>74.339996</td>\n",
       "      <td>74.730003</td>\n",
       "      <td>73.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>20897000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-22</th>\n",
       "      <td>74.940002</td>\n",
       "      <td>75.279999</td>\n",
       "      <td>74.790001</td>\n",
       "      <td>75.019997</td>\n",
       "      <td>75.019997</td>\n",
       "      <td>19734000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-25</th>\n",
       "      <td>75.000000</td>\n",
       "      <td>75.989998</td>\n",
       "      <td>74.730003</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>23993000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-26</th>\n",
       "      <td>75.269997</td>\n",
       "      <td>75.489998</td>\n",
       "      <td>74.459999</td>\n",
       "      <td>74.629997</td>\n",
       "      <td>74.629997</td>\n",
       "      <td>36323000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>74.430000</td>\n",
       "      <td>73.730003</td>\n",
       "      <td>73.860001</td>\n",
       "      <td>73.860001</td>\n",
       "      <td>21947000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>74.300003</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>74.010002</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>26241000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>75.010002</td>\n",
       "      <td>76.699997</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>76.680000</td>\n",
       "      <td>76.680000</td>\n",
       "      <td>34979000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-02</th>\n",
       "      <td>77.139999</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>75.599998</td>\n",
       "      <td>75.830002</td>\n",
       "      <td>75.830002</td>\n",
       "      <td>32389000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-03</th>\n",
       "      <td>75.889999</td>\n",
       "      <td>76.930000</td>\n",
       "      <td>75.529999</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>26676000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-04</th>\n",
       "      <td>76.099998</td>\n",
       "      <td>77.379997</td>\n",
       "      <td>75.599998</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>29476000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-05</th>\n",
       "      <td>77.260002</td>\n",
       "      <td>78.169998</td>\n",
       "      <td>77.010002</td>\n",
       "      <td>77.889999</td>\n",
       "      <td>77.889999</td>\n",
       "      <td>28183000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-08</th>\n",
       "      <td>77.589996</td>\n",
       "      <td>78.169998</td>\n",
       "      <td>76.199997</td>\n",
       "      <td>76.669998</td>\n",
       "      <td>76.669998</td>\n",
       "      <td>28882000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-09</th>\n",
       "      <td>76.519997</td>\n",
       "      <td>77.949997</td>\n",
       "      <td>76.510002</td>\n",
       "      <td>77.430000</td>\n",
       "      <td>77.430000</td>\n",
       "      <td>29909000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-10</th>\n",
       "      <td>77.129997</td>\n",
       "      <td>78.360001</td>\n",
       "      <td>77.050003</td>\n",
       "      <td>77.919998</td>\n",
       "      <td>77.919998</td>\n",
       "      <td>32219000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-11</th>\n",
       "      <td>78.019997</td>\n",
       "      <td>78.300003</td>\n",
       "      <td>77.099998</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>26676800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-12</th>\n",
       "      <td>77.150002</td>\n",
       "      <td>77.250000</td>\n",
       "      <td>73.430000</td>\n",
       "      <td>74.580002</td>\n",
       "      <td>74.580002</td>\n",
       "      <td>49679000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-15</th>\n",
       "      <td>73.519997</td>\n",
       "      <td>76.230003</td>\n",
       "      <td>73.070000</td>\n",
       "      <td>76.080002</td>\n",
       "      <td>76.080002</td>\n",
       "      <td>37742000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-16</th>\n",
       "      <td>75.959999</td>\n",
       "      <td>77.250000</td>\n",
       "      <td>75.570000</td>\n",
       "      <td>76.430000</td>\n",
       "      <td>76.430000</td>\n",
       "      <td>28693000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-17</th>\n",
       "      <td>76.769997</td>\n",
       "      <td>77.330002</td>\n",
       "      <td>76.519997</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>23031000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-18</th>\n",
       "      <td>77.400002</td>\n",
       "      <td>78.300003</td>\n",
       "      <td>76.440002</td>\n",
       "      <td>77.910004</td>\n",
       "      <td>77.910004</td>\n",
       "      <td>76671000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-19</th>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.529999</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>76.800003</td>\n",
       "      <td>76.800003</td>\n",
       "      <td>31961000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-22</th>\n",
       "      <td>76.330002</td>\n",
       "      <td>78.629997</td>\n",
       "      <td>76.040001</td>\n",
       "      <td>78.290001</td>\n",
       "      <td>78.290001</td>\n",
       "      <td>36814000.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>195.210007</td>\n",
       "      <td>195.279999</td>\n",
       "      <td>191.929993</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>14204700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>193.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>192.710007</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>9050000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>194.160004</td>\n",
       "      <td>197.399994</td>\n",
       "      <td>194.160004</td>\n",
       "      <td>197.199997</td>\n",
       "      <td>197.199997</td>\n",
       "      <td>10246100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>196.179993</td>\n",
       "      <td>197.070007</td>\n",
       "      <td>194.169998</td>\n",
       "      <td>196.399994</td>\n",
       "      <td>196.399994</td>\n",
       "      <td>11164100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>195.190002</td>\n",
       "      <td>196.679993</td>\n",
       "      <td>193.639999</td>\n",
       "      <td>195.759995</td>\n",
       "      <td>195.759995</td>\n",
       "      <td>9723900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>194.970001</td>\n",
       "      <td>199.460007</td>\n",
       "      <td>194.889999</td>\n",
       "      <td>199.210007</td>\n",
       "      <td>199.210007</td>\n",
       "      <td>14698600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-09</th>\n",
       "      <td>200.000000</td>\n",
       "      <td>202.960007</td>\n",
       "      <td>199.669998</td>\n",
       "      <td>202.729996</td>\n",
       "      <td>202.729996</td>\n",
       "      <td>20571700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-10</th>\n",
       "      <td>203.259995</td>\n",
       "      <td>203.800003</td>\n",
       "      <td>200.210007</td>\n",
       "      <td>201.229996</td>\n",
       "      <td>201.229996</td>\n",
       "      <td>13678500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-11</th>\n",
       "      <td>199.679993</td>\n",
       "      <td>205.300003</td>\n",
       "      <td>199.160004</td>\n",
       "      <td>204.869995</td>\n",
       "      <td>204.869995</td>\n",
       "      <td>15366300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-12</th>\n",
       "      <td>204.250000</td>\n",
       "      <td>205.330002</td>\n",
       "      <td>201.820007</td>\n",
       "      <td>203.910004</td>\n",
       "      <td>203.910004</td>\n",
       "      <td>16030300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>203.889999</td>\n",
       "      <td>205.470001</td>\n",
       "      <td>203.100006</td>\n",
       "      <td>203.839996</td>\n",
       "      <td>203.839996</td>\n",
       "      <td>12132700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>204.179993</td>\n",
       "      <td>204.360001</td>\n",
       "      <td>201.589996</td>\n",
       "      <td>201.800003</td>\n",
       "      <td>201.800003</td>\n",
       "      <td>12083700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>200.149994</td>\n",
       "      <td>202.470001</td>\n",
       "      <td>199.380005</td>\n",
       "      <td>200.779999</td>\n",
       "      <td>200.779999</td>\n",
       "      <td>11956600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>202.179993</td>\n",
       "      <td>202.330002</td>\n",
       "      <td>198.070007</td>\n",
       "      <td>198.360001</td>\n",
       "      <td>198.360001</td>\n",
       "      <td>12098300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>199.910004</td>\n",
       "      <td>202.570007</td>\n",
       "      <td>198.809998</td>\n",
       "      <td>202.320007</td>\n",
       "      <td>202.320007</td>\n",
       "      <td>13589000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-22</th>\n",
       "      <td>202.839996</td>\n",
       "      <td>204.240005</td>\n",
       "      <td>200.960007</td>\n",
       "      <td>202.360001</td>\n",
       "      <td>202.360001</td>\n",
       "      <td>14583700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-23</th>\n",
       "      <td>197.630005</td>\n",
       "      <td>204.809998</td>\n",
       "      <td>197.220001</td>\n",
       "      <td>204.660004</td>\n",
       "      <td>204.660004</td>\n",
       "      <td>32532500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-24</th>\n",
       "      <td>206.699997</td>\n",
       "      <td>208.660004</td>\n",
       "      <td>198.259995</td>\n",
       "      <td>200.710007</td>\n",
       "      <td>200.710007</td>\n",
       "      <td>39889900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-25</th>\n",
       "      <td>200.190002</td>\n",
       "      <td>202.880005</td>\n",
       "      <td>196.250000</td>\n",
       "      <td>199.750000</td>\n",
       "      <td>199.750000</td>\n",
       "      <td>24434000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-26</th>\n",
       "      <td>199.000000</td>\n",
       "      <td>199.630005</td>\n",
       "      <td>195.300003</td>\n",
       "      <td>195.940002</td>\n",
       "      <td>195.940002</td>\n",
       "      <td>16530800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-29</th>\n",
       "      <td>195.389999</td>\n",
       "      <td>198.710007</td>\n",
       "      <td>193.500000</td>\n",
       "      <td>197.039993</td>\n",
       "      <td>197.039993</td>\n",
       "      <td>11903600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-30</th>\n",
       "      <td>196.949997</td>\n",
       "      <td>198.759995</td>\n",
       "      <td>192.679993</td>\n",
       "      <td>194.229996</td>\n",
       "      <td>194.229996</td>\n",
       "      <td>14593500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-31</th>\n",
       "      <td>194.169998</td>\n",
       "      <td>198.470001</td>\n",
       "      <td>190.880005</td>\n",
       "      <td>192.729996</td>\n",
       "      <td>192.729996</td>\n",
       "      <td>17777000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-01</th>\n",
       "      <td>191.100006</td>\n",
       "      <td>192.619995</td>\n",
       "      <td>188.070007</td>\n",
       "      <td>189.020004</td>\n",
       "      <td>189.020004</td>\n",
       "      <td>15297000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-02</th>\n",
       "      <td>184.690002</td>\n",
       "      <td>185.669998</td>\n",
       "      <td>179.339996</td>\n",
       "      <td>181.729996</td>\n",
       "      <td>181.729996</td>\n",
       "      <td>23086700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-05</th>\n",
       "      <td>183.690002</td>\n",
       "      <td>185.789993</td>\n",
       "      <td>183.089996</td>\n",
       "      <td>184.509995</td>\n",
       "      <td>184.509995</td>\n",
       "      <td>18035700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-06</th>\n",
       "      <td>183.600006</td>\n",
       "      <td>186.369995</td>\n",
       "      <td>181.220001</td>\n",
       "      <td>185.149994</td>\n",
       "      <td>185.149994</td>\n",
       "      <td>15833200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-07</th>\n",
       "      <td>186.619995</td>\n",
       "      <td>190.339996</td>\n",
       "      <td>184.050003</td>\n",
       "      <td>190.160004</td>\n",
       "      <td>190.160004</td>\n",
       "      <td>14828900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-08</th>\n",
       "      <td>190.000000</td>\n",
       "      <td>190.979996</td>\n",
       "      <td>187.119995</td>\n",
       "      <td>187.850006</td>\n",
       "      <td>187.850006</td>\n",
       "      <td>10507300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-09</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1259 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2014-08-11   73.089996   73.330002   72.220001   72.830002   72.830002   \n",
       "2014-08-12   73.120003   74.250000   73.050003   73.769997   73.769997   \n",
       "2014-08-13   73.970001   74.379997   73.690002   74.300003   74.300003   \n",
       "2014-08-14   74.320000   74.650002   73.000000   73.629997   73.629997   \n",
       "2014-08-15   74.000000   74.720001   73.959999   74.589996   74.589996   \n",
       "2014-08-18   74.809998   75.580002   74.510002   75.290001   75.290001   \n",
       "2014-08-19   74.970001   75.180000   74.620003   74.809998   74.809998   \n",
       "2014-08-20   74.919998   75.190002   74.410004   74.570000   74.570000   \n",
       "2014-08-21   74.339996   74.730003   73.570000   74.570000   74.570000   \n",
       "2014-08-22   74.940002   75.279999   74.790001   75.019997   75.019997   \n",
       "2014-08-25   75.000000   75.989998   74.730003   75.959999   75.959999   \n",
       "2014-08-26   75.269997   75.489998   74.459999   74.629997   74.629997   \n",
       "2014-08-27   74.000000   74.430000   73.730003   73.860001   73.860001   \n",
       "2014-08-28   74.300003   74.820000   74.010002   74.820000   74.820000   \n",
       "2014-08-29   75.010002   76.699997   74.820000   76.680000   76.680000   \n",
       "2014-09-02   77.139999   77.480003   75.599998   75.830002   75.830002   \n",
       "2014-09-03   75.889999   76.930000   75.529999   75.949997   75.949997   \n",
       "2014-09-04   76.099998   77.379997   75.599998   77.260002   77.260002   \n",
       "2014-09-05   77.260002   78.169998   77.010002   77.889999   77.889999   \n",
       "2014-09-08   77.589996   78.169998   76.199997   76.669998   76.669998   \n",
       "2014-09-09   76.519997   77.949997   76.510002   77.430000   77.430000   \n",
       "2014-09-10   77.129997   78.360001   77.050003   77.919998   77.919998   \n",
       "2014-09-11   78.019997   78.300003   77.099998   77.480003   77.480003   \n",
       "2014-09-12   77.150002   77.250000   73.430000   74.580002   74.580002   \n",
       "2014-09-15   73.519997   76.230003   73.070000   76.080002   76.080002   \n",
       "2014-09-16   75.959999   77.250000   75.570000   76.430000   76.430000   \n",
       "2014-09-17   76.769997   77.330002   76.519997   77.000000   77.000000   \n",
       "2014-09-18   77.400002   78.300003   76.440002   77.910004   77.910004   \n",
       "2014-09-19   77.000000   77.529999   75.949997   76.800003   76.800003   \n",
       "2014-09-22   76.330002   78.629997   76.040001   78.290001   78.290001   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2019-06-28  195.210007  195.279999  191.929993  193.000000  193.000000   \n",
       "2019-07-01  193.000000  195.000000  192.710007  195.000000  195.000000   \n",
       "2019-07-02  194.160004  197.399994  194.160004  197.199997  197.199997   \n",
       "2019-07-03  196.179993  197.070007  194.169998  196.399994  196.399994   \n",
       "2019-07-05  195.190002  196.679993  193.639999  195.759995  195.759995   \n",
       "2019-07-08  194.970001  199.460007  194.889999  199.210007  199.210007   \n",
       "2019-07-09  200.000000  202.960007  199.669998  202.729996  202.729996   \n",
       "2019-07-10  203.259995  203.800003  200.210007  201.229996  201.229996   \n",
       "2019-07-11  199.679993  205.300003  199.160004  204.869995  204.869995   \n",
       "2019-07-12  204.250000  205.330002  201.820007  203.910004  203.910004   \n",
       "2019-07-15  203.889999  205.470001  203.100006  203.839996  203.839996   \n",
       "2019-07-16  204.179993  204.360001  201.589996  201.800003  201.800003   \n",
       "2019-07-17  200.149994  202.470001  199.380005  200.779999  200.779999   \n",
       "2019-07-18  202.179993  202.330002  198.070007  198.360001  198.360001   \n",
       "2019-07-19  199.910004  202.570007  198.809998  202.320007  202.320007   \n",
       "2019-07-22  202.839996  204.240005  200.960007  202.360001  202.360001   \n",
       "2019-07-23  197.630005  204.809998  197.220001  204.660004  204.660004   \n",
       "2019-07-24  206.699997  208.660004  198.259995  200.710007  200.710007   \n",
       "2019-07-25  200.190002  202.880005  196.250000  199.750000  199.750000   \n",
       "2019-07-26  199.000000  199.630005  195.300003  195.940002  195.940002   \n",
       "2019-07-29  195.389999  198.710007  193.500000  197.039993  197.039993   \n",
       "2019-07-30  196.949997  198.759995  192.679993  194.229996  194.229996   \n",
       "2019-07-31  194.169998  198.470001  190.880005  192.729996  192.729996   \n",
       "2019-08-01  191.100006  192.619995  188.070007  189.020004  189.020004   \n",
       "2019-08-02  184.690002  185.669998  179.339996  181.729996  181.729996   \n",
       "2019-08-05  183.690002  185.789993  183.089996  184.509995  184.509995   \n",
       "2019-08-06  183.600006  186.369995  181.220001  185.149994  185.149994   \n",
       "2019-08-07  186.619995  190.339996  184.050003  190.160004  190.160004   \n",
       "2019-08-08  190.000000  190.979996  187.119995  187.850006  187.850006   \n",
       "2019-08-09         NaN         NaN         NaN         NaN         NaN   \n",
       "\n",
       "                Volume  \n",
       "Date                    \n",
       "2014-08-11  27419000.0  \n",
       "2014-08-12  29266000.0  \n",
       "2014-08-13  22207000.0  \n",
       "2014-08-14  38846600.0  \n",
       "2014-08-15  23974000.0  \n",
       "2014-08-18  26679000.0  \n",
       "2014-08-19  22917000.0  \n",
       "2014-08-20  20102000.0  \n",
       "2014-08-21  20897000.0  \n",
       "2014-08-22  19734000.0  \n",
       "2014-08-25  23993000.0  \n",
       "2014-08-26  36323000.0  \n",
       "2014-08-27  21947000.0  \n",
       "2014-08-28  26241000.0  \n",
       "2014-08-29  34979000.0  \n",
       "2014-09-02  32389000.0  \n",
       "2014-09-03  26676000.0  \n",
       "2014-09-04  29476000.0  \n",
       "2014-09-05  28183000.0  \n",
       "2014-09-08  28882000.0  \n",
       "2014-09-09  29909000.0  \n",
       "2014-09-10  32219000.0  \n",
       "2014-09-11  26676800.0  \n",
       "2014-09-12  49679000.0  \n",
       "2014-09-15  37742000.0  \n",
       "2014-09-16  28693000.0  \n",
       "2014-09-17  23031000.0  \n",
       "2014-09-18  76671000.0  \n",
       "2014-09-19  31961000.0  \n",
       "2014-09-22  36814000.0  \n",
       "...                ...  \n",
       "2019-06-28  14204700.0  \n",
       "2019-07-01   9050000.0  \n",
       "2019-07-02  10246100.0  \n",
       "2019-07-03  11164100.0  \n",
       "2019-07-05   9723900.0  \n",
       "2019-07-08  14698600.0  \n",
       "2019-07-09  20571700.0  \n",
       "2019-07-10  13678500.0  \n",
       "2019-07-11  15366300.0  \n",
       "2019-07-12  16030300.0  \n",
       "2019-07-15  12132700.0  \n",
       "2019-07-16  12083700.0  \n",
       "2019-07-17  11956600.0  \n",
       "2019-07-18  12098300.0  \n",
       "2019-07-19  13589000.0  \n",
       "2019-07-22  14583700.0  \n",
       "2019-07-23  32532500.0  \n",
       "2019-07-24  39889900.0  \n",
       "2019-07-25  24434000.0  \n",
       "2019-07-26  16530800.0  \n",
       "2019-07-29  11903600.0  \n",
       "2019-07-30  14593500.0  \n",
       "2019-07-31  17777000.0  \n",
       "2019-08-01  15297000.0  \n",
       "2019-08-02  23086700.0  \n",
       "2019-08-05  18035700.0  \n",
       "2019-08-06  15833200.0  \n",
       "2019-08-07  14828900.0  \n",
       "2019-08-08  10507300.0  \n",
       "2019-08-09         NaN  \n",
       "\n",
       "[1259 rows x 6 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shift(-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Prev Day Price'] = df['Open'].shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2014-08-11           NaN\n",
       "2014-08-12     73.459999\n",
       "2014-08-13     73.089996\n",
       "2014-08-14     73.120003\n",
       "2014-08-15     73.970001\n",
       "2014-08-18     74.320000\n",
       "2014-08-19     74.000000\n",
       "2014-08-20     74.809998\n",
       "2014-08-21     74.970001\n",
       "2014-08-22     74.919998\n",
       "2014-08-25     74.339996\n",
       "2014-08-26     74.940002\n",
       "2014-08-27     75.000000\n",
       "2014-08-28     75.269997\n",
       "2014-08-29     74.000000\n",
       "2014-09-02     74.300003\n",
       "2014-09-03     75.010002\n",
       "2014-09-04     77.139999\n",
       "2014-09-05     75.889999\n",
       "2014-09-08     76.099998\n",
       "2014-09-09     77.260002\n",
       "2014-09-10     77.589996\n",
       "2014-09-11     76.519997\n",
       "2014-09-12     77.129997\n",
       "2014-09-15     78.019997\n",
       "2014-09-16     77.150002\n",
       "2014-09-17     73.519997\n",
       "2014-09-18     75.959999\n",
       "2014-09-19     76.769997\n",
       "2014-09-22     77.400002\n",
       "                 ...    \n",
       "2019-06-28    189.880005\n",
       "2019-07-01    190.550003\n",
       "2019-07-02    195.210007\n",
       "2019-07-03    193.000000\n",
       "2019-07-05    194.160004\n",
       "2019-07-08    196.179993\n",
       "2019-07-09    195.190002\n",
       "2019-07-10    194.970001\n",
       "2019-07-11    200.000000\n",
       "2019-07-12    203.259995\n",
       "2019-07-15    199.679993\n",
       "2019-07-16    204.250000\n",
       "2019-07-17    203.889999\n",
       "2019-07-18    204.179993\n",
       "2019-07-19    200.149994\n",
       "2019-07-22    202.179993\n",
       "2019-07-23    199.910004\n",
       "2019-07-24    202.839996\n",
       "2019-07-25    197.630005\n",
       "2019-07-26    206.699997\n",
       "2019-07-29    200.190002\n",
       "2019-07-30    199.000000\n",
       "2019-07-31    195.389999\n",
       "2019-08-01    196.949997\n",
       "2019-08-02    194.169998\n",
       "2019-08-05    191.100006\n",
       "2019-08-06    184.690002\n",
       "2019-08-07    183.690002\n",
       "2019-08-08    183.600006\n",
       "2019-08-09    186.619995\n",
       "Name: Prev Day Price, Length: 1259, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Prev Day Price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Prev Day Price</th>\n",
       "      <th>Price Change</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>2014-08-11</th>\n",
       "      <td>73.459999</td>\n",
       "      <td>73.910004</td>\n",
       "      <td>73.059998</td>\n",
       "      <td>73.440002</td>\n",
       "      <td>73.440002</td>\n",
       "      <td>24591000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-12</th>\n",
       "      <td>73.089996</td>\n",
       "      <td>73.330002</td>\n",
       "      <td>72.220001</td>\n",
       "      <td>72.830002</td>\n",
       "      <td>72.830002</td>\n",
       "      <td>27419000</td>\n",
       "      <td>73.459999</td>\n",
       "      <td>-0.370003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-13</th>\n",
       "      <td>73.120003</td>\n",
       "      <td>74.250000</td>\n",
       "      <td>73.050003</td>\n",
       "      <td>73.769997</td>\n",
       "      <td>73.769997</td>\n",
       "      <td>29266000</td>\n",
       "      <td>73.089996</td>\n",
       "      <td>0.030007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-14</th>\n",
       "      <td>73.970001</td>\n",
       "      <td>74.379997</td>\n",
       "      <td>73.690002</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>22207000</td>\n",
       "      <td>73.120003</td>\n",
       "      <td>0.849998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-15</th>\n",
       "      <td>74.320000</td>\n",
       "      <td>74.650002</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>73.629997</td>\n",
       "      <td>73.629997</td>\n",
       "      <td>38846600</td>\n",
       "      <td>73.970001</td>\n",
       "      <td>0.349999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-18</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>74.720001</td>\n",
       "      <td>73.959999</td>\n",
       "      <td>74.589996</td>\n",
       "      <td>74.589996</td>\n",
       "      <td>23974000</td>\n",
       "      <td>74.320000</td>\n",
       "      <td>-0.320000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-19</th>\n",
       "      <td>74.809998</td>\n",
       "      <td>75.580002</td>\n",
       "      <td>74.510002</td>\n",
       "      <td>75.290001</td>\n",
       "      <td>75.290001</td>\n",
       "      <td>26679000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>0.809998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-20</th>\n",
       "      <td>74.970001</td>\n",
       "      <td>75.180000</td>\n",
       "      <td>74.620003</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>22917000</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>0.160003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-21</th>\n",
       "      <td>74.919998</td>\n",
       "      <td>75.190002</td>\n",
       "      <td>74.410004</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>20102000</td>\n",
       "      <td>74.970001</td>\n",
       "      <td>-0.050003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-22</th>\n",
       "      <td>74.339996</td>\n",
       "      <td>74.730003</td>\n",
       "      <td>73.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>20897000</td>\n",
       "      <td>74.919998</td>\n",
       "      <td>-0.580002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-25</th>\n",
       "      <td>74.940002</td>\n",
       "      <td>75.279999</td>\n",
       "      <td>74.790001</td>\n",
       "      <td>75.019997</td>\n",
       "      <td>75.019997</td>\n",
       "      <td>19734000</td>\n",
       "      <td>74.339996</td>\n",
       "      <td>0.600006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-26</th>\n",
       "      <td>75.000000</td>\n",
       "      <td>75.989998</td>\n",
       "      <td>74.730003</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>23993000</td>\n",
       "      <td>74.940002</td>\n",
       "      <td>0.059998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>75.269997</td>\n",
       "      <td>75.489998</td>\n",
       "      <td>74.459999</td>\n",
       "      <td>74.629997</td>\n",
       "      <td>74.629997</td>\n",
       "      <td>36323000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>0.269997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>74.430000</td>\n",
       "      <td>73.730003</td>\n",
       "      <td>73.860001</td>\n",
       "      <td>73.860001</td>\n",
       "      <td>21947000</td>\n",
       "      <td>75.269997</td>\n",
       "      <td>-1.269997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>74.300003</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>74.010002</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>26241000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>0.300003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-02</th>\n",
       "      <td>75.010002</td>\n",
       "      <td>76.699997</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>76.680000</td>\n",
       "      <td>76.680000</td>\n",
       "      <td>34979000</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>0.709999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-03</th>\n",
       "      <td>77.139999</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>75.599998</td>\n",
       "      <td>75.830002</td>\n",
       "      <td>75.830002</td>\n",
       "      <td>32389000</td>\n",
       "      <td>75.010002</td>\n",
       "      <td>2.129997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-04</th>\n",
       "      <td>75.889999</td>\n",
       "      <td>76.930000</td>\n",
       "      <td>75.529999</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>26676000</td>\n",
       "      <td>77.139999</td>\n",
       "      <td>-1.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-05</th>\n",
       "      <td>76.099998</td>\n",
       "      <td>77.379997</td>\n",
       "      <td>75.599998</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>29476000</td>\n",
       "      <td>75.889999</td>\n",
       "      <td>0.209999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-08</th>\n",
       "      <td>77.260002</td>\n",
       "      <td>78.169998</td>\n",
       "      <td>77.010002</td>\n",
       "      <td>77.889999</td>\n",
       "      <td>77.889999</td>\n",
       "      <td>28183000</td>\n",
       "      <td>76.099998</td>\n",
       "      <td>1.160004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-09</th>\n",
       "      <td>77.589996</td>\n",
       "      <td>78.169998</td>\n",
       "      <td>76.199997</td>\n",
       "      <td>76.669998</td>\n",
       "      <td>76.669998</td>\n",
       "      <td>28882000</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>0.329994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-10</th>\n",
       "      <td>76.519997</td>\n",
       "      <td>77.949997</td>\n",
       "      <td>76.510002</td>\n",
       "      <td>77.430000</td>\n",
       "      <td>77.430000</td>\n",
       "      <td>29909000</td>\n",
       "      <td>77.589996</td>\n",
       "      <td>-1.069999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-11</th>\n",
       "      <td>77.129997</td>\n",
       "      <td>78.360001</td>\n",
       "      <td>77.050003</td>\n",
       "      <td>77.919998</td>\n",
       "      <td>77.919998</td>\n",
       "      <td>32219000</td>\n",
       "      <td>76.519997</td>\n",
       "      <td>0.610000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-12</th>\n",
       "      <td>78.019997</td>\n",
       "      <td>78.300003</td>\n",
       "      <td>77.099998</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>26676800</td>\n",
       "      <td>77.129997</td>\n",
       "      <td>0.890000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-15</th>\n",
       "      <td>77.150002</td>\n",
       "      <td>77.250000</td>\n",
       "      <td>73.430000</td>\n",
       "      <td>74.580002</td>\n",
       "      <td>74.580002</td>\n",
       "      <td>49679000</td>\n",
       "      <td>78.019997</td>\n",
       "      <td>-0.869995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-16</th>\n",
       "      <td>73.519997</td>\n",
       "      <td>76.230003</td>\n",
       "      <td>73.070000</td>\n",
       "      <td>76.080002</td>\n",
       "      <td>76.080002</td>\n",
       "      <td>37742000</td>\n",
       "      <td>77.150002</td>\n",
       "      <td>-3.630005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-17</th>\n",
       "      <td>75.959999</td>\n",
       "      <td>77.250000</td>\n",
       "      <td>75.570000</td>\n",
       "      <td>76.430000</td>\n",
       "      <td>76.430000</td>\n",
       "      <td>28693000</td>\n",
       "      <td>73.519997</td>\n",
       "      <td>2.440002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-18</th>\n",
       "      <td>76.769997</td>\n",
       "      <td>77.330002</td>\n",
       "      <td>76.519997</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>23031000</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>0.809998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-19</th>\n",
       "      <td>77.400002</td>\n",
       "      <td>78.300003</td>\n",
       "      <td>76.440002</td>\n",
       "      <td>77.910004</td>\n",
       "      <td>77.910004</td>\n",
       "      <td>76671000</td>\n",
       "      <td>76.769997</td>\n",
       "      <td>0.630005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-22</th>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.529999</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>76.800003</td>\n",
       "      <td>76.800003</td>\n",
       "      <td>31961000</td>\n",
       "      <td>77.400002</td>\n",
       "      <td>-0.400002</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>190.550003</td>\n",
       "      <td>193.199997</td>\n",
       "      <td>189.940002</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>16378900</td>\n",
       "      <td>189.880005</td>\n",
       "      <td>0.669998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>195.210007</td>\n",
       "      <td>195.279999</td>\n",
       "      <td>191.929993</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>14204700</td>\n",
       "      <td>190.550003</td>\n",
       "      <td>4.660004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>193.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>192.710007</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>9050000</td>\n",
       "      <td>195.210007</td>\n",
       "      <td>-2.210007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>194.160004</td>\n",
       "      <td>197.399994</td>\n",
       "      <td>194.160004</td>\n",
       "      <td>197.199997</td>\n",
       "      <td>197.199997</td>\n",
       "      <td>10246100</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>1.160004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>196.179993</td>\n",
       "      <td>197.070007</td>\n",
       "      <td>194.169998</td>\n",
       "      <td>196.399994</td>\n",
       "      <td>196.399994</td>\n",
       "      <td>11164100</td>\n",
       "      <td>194.160004</td>\n",
       "      <td>2.019989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>195.190002</td>\n",
       "      <td>196.679993</td>\n",
       "      <td>193.639999</td>\n",
       "      <td>195.759995</td>\n",
       "      <td>195.759995</td>\n",
       "      <td>9723900</td>\n",
       "      <td>196.179993</td>\n",
       "      <td>-0.989991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-09</th>\n",
       "      <td>194.970001</td>\n",
       "      <td>199.460007</td>\n",
       "      <td>194.889999</td>\n",
       "      <td>199.210007</td>\n",
       "      <td>199.210007</td>\n",
       "      <td>14698600</td>\n",
       "      <td>195.190002</td>\n",
       "      <td>-0.220001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-10</th>\n",
       "      <td>200.000000</td>\n",
       "      <td>202.960007</td>\n",
       "      <td>199.669998</td>\n",
       "      <td>202.729996</td>\n",
       "      <td>202.729996</td>\n",
       "      <td>20571700</td>\n",
       "      <td>194.970001</td>\n",
       "      <td>5.029999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-11</th>\n",
       "      <td>203.259995</td>\n",
       "      <td>203.800003</td>\n",
       "      <td>200.210007</td>\n",
       "      <td>201.229996</td>\n",
       "      <td>201.229996</td>\n",
       "      <td>13678500</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>3.259995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-12</th>\n",
       "      <td>199.679993</td>\n",
       "      <td>205.300003</td>\n",
       "      <td>199.160004</td>\n",
       "      <td>204.869995</td>\n",
       "      <td>204.869995</td>\n",
       "      <td>15366300</td>\n",
       "      <td>203.259995</td>\n",
       "      <td>-3.580002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>204.250000</td>\n",
       "      <td>205.330002</td>\n",
       "      <td>201.820007</td>\n",
       "      <td>203.910004</td>\n",
       "      <td>203.910004</td>\n",
       "      <td>16030300</td>\n",
       "      <td>199.679993</td>\n",
       "      <td>4.570007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>203.889999</td>\n",
       "      <td>205.470001</td>\n",
       "      <td>203.100006</td>\n",
       "      <td>203.839996</td>\n",
       "      <td>203.839996</td>\n",
       "      <td>12132700</td>\n",
       "      <td>204.250000</td>\n",
       "      <td>-0.360001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>204.179993</td>\n",
       "      <td>204.360001</td>\n",
       "      <td>201.589996</td>\n",
       "      <td>201.800003</td>\n",
       "      <td>201.800003</td>\n",
       "      <td>12083700</td>\n",
       "      <td>203.889999</td>\n",
       "      <td>0.289994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>200.149994</td>\n",
       "      <td>202.470001</td>\n",
       "      <td>199.380005</td>\n",
       "      <td>200.779999</td>\n",
       "      <td>200.779999</td>\n",
       "      <td>11956600</td>\n",
       "      <td>204.179993</td>\n",
       "      <td>-4.029999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>202.179993</td>\n",
       "      <td>202.330002</td>\n",
       "      <td>198.070007</td>\n",
       "      <td>198.360001</td>\n",
       "      <td>198.360001</td>\n",
       "      <td>12098300</td>\n",
       "      <td>200.149994</td>\n",
       "      <td>2.029999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-22</th>\n",
       "      <td>199.910004</td>\n",
       "      <td>202.570007</td>\n",
       "      <td>198.809998</td>\n",
       "      <td>202.320007</td>\n",
       "      <td>202.320007</td>\n",
       "      <td>13589000</td>\n",
       "      <td>202.179993</td>\n",
       "      <td>-2.269989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-23</th>\n",
       "      <td>202.839996</td>\n",
       "      <td>204.240005</td>\n",
       "      <td>200.960007</td>\n",
       "      <td>202.360001</td>\n",
       "      <td>202.360001</td>\n",
       "      <td>14583700</td>\n",
       "      <td>199.910004</td>\n",
       "      <td>2.929992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-24</th>\n",
       "      <td>197.630005</td>\n",
       "      <td>204.809998</td>\n",
       "      <td>197.220001</td>\n",
       "      <td>204.660004</td>\n",
       "      <td>204.660004</td>\n",
       "      <td>32532500</td>\n",
       "      <td>202.839996</td>\n",
       "      <td>-5.209991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-25</th>\n",
       "      <td>206.699997</td>\n",
       "      <td>208.660004</td>\n",
       "      <td>198.259995</td>\n",
       "      <td>200.710007</td>\n",
       "      <td>200.710007</td>\n",
       "      <td>39889900</td>\n",
       "      <td>197.630005</td>\n",
       "      <td>9.069992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-26</th>\n",
       "      <td>200.190002</td>\n",
       "      <td>202.880005</td>\n",
       "      <td>196.250000</td>\n",
       "      <td>199.750000</td>\n",
       "      <td>199.750000</td>\n",
       "      <td>24434000</td>\n",
       "      <td>206.699997</td>\n",
       "      <td>-6.509995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-29</th>\n",
       "      <td>199.000000</td>\n",
       "      <td>199.630005</td>\n",
       "      <td>195.300003</td>\n",
       "      <td>195.940002</td>\n",
       "      <td>195.940002</td>\n",
       "      <td>16530800</td>\n",
       "      <td>200.190002</td>\n",
       "      <td>-1.190002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-30</th>\n",
       "      <td>195.389999</td>\n",
       "      <td>198.710007</td>\n",
       "      <td>193.500000</td>\n",
       "      <td>197.039993</td>\n",
       "      <td>197.039993</td>\n",
       "      <td>11903600</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>-3.610001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-31</th>\n",
       "      <td>196.949997</td>\n",
       "      <td>198.759995</td>\n",
       "      <td>192.679993</td>\n",
       "      <td>194.229996</td>\n",
       "      <td>194.229996</td>\n",
       "      <td>14593500</td>\n",
       "      <td>195.389999</td>\n",
       "      <td>1.559998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-01</th>\n",
       "      <td>194.169998</td>\n",
       "      <td>198.470001</td>\n",
       "      <td>190.880005</td>\n",
       "      <td>192.729996</td>\n",
       "      <td>192.729996</td>\n",
       "      <td>17777000</td>\n",
       "      <td>196.949997</td>\n",
       "      <td>-2.779999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-02</th>\n",
       "      <td>191.100006</td>\n",
       "      <td>192.619995</td>\n",
       "      <td>188.070007</td>\n",
       "      <td>189.020004</td>\n",
       "      <td>189.020004</td>\n",
       "      <td>15297000</td>\n",
       "      <td>194.169998</td>\n",
       "      <td>-3.069992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-05</th>\n",
       "      <td>184.690002</td>\n",
       "      <td>185.669998</td>\n",
       "      <td>179.339996</td>\n",
       "      <td>181.729996</td>\n",
       "      <td>181.729996</td>\n",
       "      <td>23086700</td>\n",
       "      <td>191.100006</td>\n",
       "      <td>-6.410004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-06</th>\n",
       "      <td>183.690002</td>\n",
       "      <td>185.789993</td>\n",
       "      <td>183.089996</td>\n",
       "      <td>184.509995</td>\n",
       "      <td>184.509995</td>\n",
       "      <td>18035700</td>\n",
       "      <td>184.690002</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-07</th>\n",
       "      <td>183.600006</td>\n",
       "      <td>186.369995</td>\n",
       "      <td>181.220001</td>\n",
       "      <td>185.149994</td>\n",
       "      <td>185.149994</td>\n",
       "      <td>15833200</td>\n",
       "      <td>183.690002</td>\n",
       "      <td>-0.089996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-08</th>\n",
       "      <td>186.619995</td>\n",
       "      <td>190.339996</td>\n",
       "      <td>184.050003</td>\n",
       "      <td>190.160004</td>\n",
       "      <td>190.160004</td>\n",
       "      <td>14828900</td>\n",
       "      <td>183.600006</td>\n",
       "      <td>3.019989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-09</th>\n",
       "      <td>190.000000</td>\n",
       "      <td>190.979996</td>\n",
       "      <td>187.119995</td>\n",
       "      <td>187.850006</td>\n",
       "      <td>187.850006</td>\n",
       "      <td>10507300</td>\n",
       "      <td>186.619995</td>\n",
       "      <td>3.380005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1259 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2014-08-11   73.459999   73.910004   73.059998   73.440002   73.440002   \n",
       "2014-08-12   73.089996   73.330002   72.220001   72.830002   72.830002   \n",
       "2014-08-13   73.120003   74.250000   73.050003   73.769997   73.769997   \n",
       "2014-08-14   73.970001   74.379997   73.690002   74.300003   74.300003   \n",
       "2014-08-15   74.320000   74.650002   73.000000   73.629997   73.629997   \n",
       "2014-08-18   74.000000   74.720001   73.959999   74.589996   74.589996   \n",
       "2014-08-19   74.809998   75.580002   74.510002   75.290001   75.290001   \n",
       "2014-08-20   74.970001   75.180000   74.620003   74.809998   74.809998   \n",
       "2014-08-21   74.919998   75.190002   74.410004   74.570000   74.570000   \n",
       "2014-08-22   74.339996   74.730003   73.570000   74.570000   74.570000   \n",
       "2014-08-25   74.940002   75.279999   74.790001   75.019997   75.019997   \n",
       "2014-08-26   75.000000   75.989998   74.730003   75.959999   75.959999   \n",
       "2014-08-27   75.269997   75.489998   74.459999   74.629997   74.629997   \n",
       "2014-08-28   74.000000   74.430000   73.730003   73.860001   73.860001   \n",
       "2014-08-29   74.300003   74.820000   74.010002   74.820000   74.820000   \n",
       "2014-09-02   75.010002   76.699997   74.820000   76.680000   76.680000   \n",
       "2014-09-03   77.139999   77.480003   75.599998   75.830002   75.830002   \n",
       "2014-09-04   75.889999   76.930000   75.529999   75.949997   75.949997   \n",
       "2014-09-05   76.099998   77.379997   75.599998   77.260002   77.260002   \n",
       "2014-09-08   77.260002   78.169998   77.010002   77.889999   77.889999   \n",
       "2014-09-09   77.589996   78.169998   76.199997   76.669998   76.669998   \n",
       "2014-09-10   76.519997   77.949997   76.510002   77.430000   77.430000   \n",
       "2014-09-11   77.129997   78.360001   77.050003   77.919998   77.919998   \n",
       "2014-09-12   78.019997   78.300003   77.099998   77.480003   77.480003   \n",
       "2014-09-15   77.150002   77.250000   73.430000   74.580002   74.580002   \n",
       "2014-09-16   73.519997   76.230003   73.070000   76.080002   76.080002   \n",
       "2014-09-17   75.959999   77.250000   75.570000   76.430000   76.430000   \n",
       "2014-09-18   76.769997   77.330002   76.519997   77.000000   77.000000   \n",
       "2014-09-19   77.400002   78.300003   76.440002   77.910004   77.910004   \n",
       "2014-09-22   77.000000   77.529999   75.949997   76.800003   76.800003   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2019-06-28  190.550003  193.199997  189.940002  193.000000  193.000000   \n",
       "2019-07-01  195.210007  195.279999  191.929993  193.000000  193.000000   \n",
       "2019-07-02  193.000000  195.000000  192.710007  195.000000  195.000000   \n",
       "2019-07-03  194.160004  197.399994  194.160004  197.199997  197.199997   \n",
       "2019-07-05  196.179993  197.070007  194.169998  196.399994  196.399994   \n",
       "2019-07-08  195.190002  196.679993  193.639999  195.759995  195.759995   \n",
       "2019-07-09  194.970001  199.460007  194.889999  199.210007  199.210007   \n",
       "2019-07-10  200.000000  202.960007  199.669998  202.729996  202.729996   \n",
       "2019-07-11  203.259995  203.800003  200.210007  201.229996  201.229996   \n",
       "2019-07-12  199.679993  205.300003  199.160004  204.869995  204.869995   \n",
       "2019-07-15  204.250000  205.330002  201.820007  203.910004  203.910004   \n",
       "2019-07-16  203.889999  205.470001  203.100006  203.839996  203.839996   \n",
       "2019-07-17  204.179993  204.360001  201.589996  201.800003  201.800003   \n",
       "2019-07-18  200.149994  202.470001  199.380005  200.779999  200.779999   \n",
       "2019-07-19  202.179993  202.330002  198.070007  198.360001  198.360001   \n",
       "2019-07-22  199.910004  202.570007  198.809998  202.320007  202.320007   \n",
       "2019-07-23  202.839996  204.240005  200.960007  202.360001  202.360001   \n",
       "2019-07-24  197.630005  204.809998  197.220001  204.660004  204.660004   \n",
       "2019-07-25  206.699997  208.660004  198.259995  200.710007  200.710007   \n",
       "2019-07-26  200.190002  202.880005  196.250000  199.750000  199.750000   \n",
       "2019-07-29  199.000000  199.630005  195.300003  195.940002  195.940002   \n",
       "2019-07-30  195.389999  198.710007  193.500000  197.039993  197.039993   \n",
       "2019-07-31  196.949997  198.759995  192.679993  194.229996  194.229996   \n",
       "2019-08-01  194.169998  198.470001  190.880005  192.729996  192.729996   \n",
       "2019-08-02  191.100006  192.619995  188.070007  189.020004  189.020004   \n",
       "2019-08-05  184.690002  185.669998  179.339996  181.729996  181.729996   \n",
       "2019-08-06  183.690002  185.789993  183.089996  184.509995  184.509995   \n",
       "2019-08-07  183.600006  186.369995  181.220001  185.149994  185.149994   \n",
       "2019-08-08  186.619995  190.339996  184.050003  190.160004  190.160004   \n",
       "2019-08-09  190.000000  190.979996  187.119995  187.850006  187.850006   \n",
       "\n",
       "              Volume  Prev Day Price  Price Change  \n",
       "Date                                                \n",
       "2014-08-11  24591000             NaN           NaN  \n",
       "2014-08-12  27419000       73.459999     -0.370003  \n",
       "2014-08-13  29266000       73.089996      0.030007  \n",
       "2014-08-14  22207000       73.120003      0.849998  \n",
       "2014-08-15  38846600       73.970001      0.349999  \n",
       "2014-08-18  23974000       74.320000     -0.320000  \n",
       "2014-08-19  26679000       74.000000      0.809998  \n",
       "2014-08-20  22917000       74.809998      0.160003  \n",
       "2014-08-21  20102000       74.970001     -0.050003  \n",
       "2014-08-22  20897000       74.919998     -0.580002  \n",
       "2014-08-25  19734000       74.339996      0.600006  \n",
       "2014-08-26  23993000       74.940002      0.059998  \n",
       "2014-08-27  36323000       75.000000      0.269997  \n",
       "2014-08-28  21947000       75.269997     -1.269997  \n",
       "2014-08-29  26241000       74.000000      0.300003  \n",
       "2014-09-02  34979000       74.300003      0.709999  \n",
       "2014-09-03  32389000       75.010002      2.129997  \n",
       "2014-09-04  26676000       77.139999     -1.250000  \n",
       "2014-09-05  29476000       75.889999      0.209999  \n",
       "2014-09-08  28183000       76.099998      1.160004  \n",
       "2014-09-09  28882000       77.260002      0.329994  \n",
       "2014-09-10  29909000       77.589996     -1.069999  \n",
       "2014-09-11  32219000       76.519997      0.610000  \n",
       "2014-09-12  26676800       77.129997      0.890000  \n",
       "2014-09-15  49679000       78.019997     -0.869995  \n",
       "2014-09-16  37742000       77.150002     -3.630005  \n",
       "2014-09-17  28693000       73.519997      2.440002  \n",
       "2014-09-18  23031000       75.959999      0.809998  \n",
       "2014-09-19  76671000       76.769997      0.630005  \n",
       "2014-09-22  31961000       77.400002     -0.400002  \n",
       "...              ...             ...           ...  \n",
       "2019-06-28  16378900      189.880005      0.669998  \n",
       "2019-07-01  14204700      190.550003      4.660004  \n",
       "2019-07-02   9050000      195.210007     -2.210007  \n",
       "2019-07-03  10246100      193.000000      1.160004  \n",
       "2019-07-05  11164100      194.160004      2.019989  \n",
       "2019-07-08   9723900      196.179993     -0.989991  \n",
       "2019-07-09  14698600      195.190002     -0.220001  \n",
       "2019-07-10  20571700      194.970001      5.029999  \n",
       "2019-07-11  13678500      200.000000      3.259995  \n",
       "2019-07-12  15366300      203.259995     -3.580002  \n",
       "2019-07-15  16030300      199.679993      4.570007  \n",
       "2019-07-16  12132700      204.250000     -0.360001  \n",
       "2019-07-17  12083700      203.889999      0.289994  \n",
       "2019-07-18  11956600      204.179993     -4.029999  \n",
       "2019-07-19  12098300      200.149994      2.029999  \n",
       "2019-07-22  13589000      202.179993     -2.269989  \n",
       "2019-07-23  14583700      199.910004      2.929992  \n",
       "2019-07-24  32532500      202.839996     -5.209991  \n",
       "2019-07-25  39889900      197.630005      9.069992  \n",
       "2019-07-26  24434000      206.699997     -6.509995  \n",
       "2019-07-29  16530800      200.190002     -1.190002  \n",
       "2019-07-30  11903600      199.000000     -3.610001  \n",
       "2019-07-31  14593500      195.389999      1.559998  \n",
       "2019-08-01  17777000      196.949997     -2.779999  \n",
       "2019-08-02  15297000      194.169998     -3.069992  \n",
       "2019-08-05  23086700      191.100006     -6.410004  \n",
       "2019-08-06  18035700      184.690002     -1.000000  \n",
       "2019-08-07  15833200      183.690002     -0.089996  \n",
       "2019-08-08  14828900      183.600006      3.019989  \n",
       "2019-08-09  10507300      186.619995      3.380005  \n",
       "\n",
       "[1259 rows x 8 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Price Change'] = df['Open'] - df['Prev Day Price']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Prev Day Price</th>\n",
       "      <th>Price Change</th>\n",
       "      <th>5 day return</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-08-11</th>\n",
       "      <td>73.459999</td>\n",
       "      <td>73.910004</td>\n",
       "      <td>73.059998</td>\n",
       "      <td>73.440002</td>\n",
       "      <td>73.440002</td>\n",
       "      <td>24591000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-12</th>\n",
       "      <td>73.089996</td>\n",
       "      <td>73.330002</td>\n",
       "      <td>72.220001</td>\n",
       "      <td>72.830002</td>\n",
       "      <td>72.830002</td>\n",
       "      <td>27419000</td>\n",
       "      <td>73.459999</td>\n",
       "      <td>-0.370003</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-13</th>\n",
       "      <td>73.120003</td>\n",
       "      <td>74.250000</td>\n",
       "      <td>73.050003</td>\n",
       "      <td>73.769997</td>\n",
       "      <td>73.769997</td>\n",
       "      <td>29266000</td>\n",
       "      <td>73.089996</td>\n",
       "      <td>0.030007</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-14</th>\n",
       "      <td>73.970001</td>\n",
       "      <td>74.379997</td>\n",
       "      <td>73.690002</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>22207000</td>\n",
       "      <td>73.120003</td>\n",
       "      <td>0.849998</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-15</th>\n",
       "      <td>74.320000</td>\n",
       "      <td>74.650002</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>73.629997</td>\n",
       "      <td>73.629997</td>\n",
       "      <td>38846600</td>\n",
       "      <td>73.970001</td>\n",
       "      <td>0.349999</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-18</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>74.720001</td>\n",
       "      <td>73.959999</td>\n",
       "      <td>74.589996</td>\n",
       "      <td>74.589996</td>\n",
       "      <td>23974000</td>\n",
       "      <td>74.320000</td>\n",
       "      <td>-0.320000</td>\n",
       "      <td>0.735095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-19</th>\n",
       "      <td>74.809998</td>\n",
       "      <td>75.580002</td>\n",
       "      <td>74.510002</td>\n",
       "      <td>75.290001</td>\n",
       "      <td>75.290001</td>\n",
       "      <td>26679000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>0.809998</td>\n",
       "      <td>2.353266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-20</th>\n",
       "      <td>74.970001</td>\n",
       "      <td>75.180000</td>\n",
       "      <td>74.620003</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>22917000</td>\n",
       "      <td>74.809998</td>\n",
       "      <td>0.160003</td>\n",
       "      <td>2.530085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-21</th>\n",
       "      <td>74.919998</td>\n",
       "      <td>75.190002</td>\n",
       "      <td>74.410004</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>20102000</td>\n",
       "      <td>74.970001</td>\n",
       "      <td>-0.050003</td>\n",
       "      <td>1.284300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-22</th>\n",
       "      <td>74.339996</td>\n",
       "      <td>74.730003</td>\n",
       "      <td>73.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>74.570000</td>\n",
       "      <td>20897000</td>\n",
       "      <td>74.919998</td>\n",
       "      <td>-0.580002</td>\n",
       "      <td>0.026905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-25</th>\n",
       "      <td>74.940002</td>\n",
       "      <td>75.279999</td>\n",
       "      <td>74.790001</td>\n",
       "      <td>75.019997</td>\n",
       "      <td>75.019997</td>\n",
       "      <td>19734000</td>\n",
       "      <td>74.339996</td>\n",
       "      <td>0.600006</td>\n",
       "      <td>1.270273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-26</th>\n",
       "      <td>75.000000</td>\n",
       "      <td>75.989998</td>\n",
       "      <td>74.730003</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>23993000</td>\n",
       "      <td>74.940002</td>\n",
       "      <td>0.059998</td>\n",
       "      <td>0.253979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>75.269997</td>\n",
       "      <td>75.489998</td>\n",
       "      <td>74.459999</td>\n",
       "      <td>74.629997</td>\n",
       "      <td>74.629997</td>\n",
       "      <td>36323000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>0.269997</td>\n",
       "      <td>0.400155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>74.430000</td>\n",
       "      <td>73.730003</td>\n",
       "      <td>73.860001</td>\n",
       "      <td>73.860001</td>\n",
       "      <td>21947000</td>\n",
       "      <td>75.269997</td>\n",
       "      <td>-1.269997</td>\n",
       "      <td>-1.227974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>74.300003</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>74.010002</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>26241000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>0.300003</td>\n",
       "      <td>-0.053797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-02</th>\n",
       "      <td>75.010002</td>\n",
       "      <td>76.699997</td>\n",
       "      <td>74.820000</td>\n",
       "      <td>76.680000</td>\n",
       "      <td>76.680000</td>\n",
       "      <td>34979000</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>0.709999</td>\n",
       "      <td>0.093408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-03</th>\n",
       "      <td>77.139999</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>75.599998</td>\n",
       "      <td>75.830002</td>\n",
       "      <td>75.830002</td>\n",
       "      <td>32389000</td>\n",
       "      <td>75.010002</td>\n",
       "      <td>2.129997</td>\n",
       "      <td>2.853332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-04</th>\n",
       "      <td>75.889999</td>\n",
       "      <td>76.930000</td>\n",
       "      <td>75.529999</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>26676000</td>\n",
       "      <td>77.139999</td>\n",
       "      <td>-1.250000</td>\n",
       "      <td>0.823704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-05</th>\n",
       "      <td>76.099998</td>\n",
       "      <td>77.379997</td>\n",
       "      <td>75.599998</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>29476000</td>\n",
       "      <td>75.889999</td>\n",
       "      <td>0.209999</td>\n",
       "      <td>2.837835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-08</th>\n",
       "      <td>77.260002</td>\n",
       "      <td>78.169998</td>\n",
       "      <td>77.010002</td>\n",
       "      <td>77.889999</td>\n",
       "      <td>77.889999</td>\n",
       "      <td>28183000</td>\n",
       "      <td>76.099998</td>\n",
       "      <td>1.160004</td>\n",
       "      <td>3.983848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-09</th>\n",
       "      <td>77.589996</td>\n",
       "      <td>78.169998</td>\n",
       "      <td>76.199997</td>\n",
       "      <td>76.669998</td>\n",
       "      <td>76.669998</td>\n",
       "      <td>28882000</td>\n",
       "      <td>77.260002</td>\n",
       "      <td>0.329994</td>\n",
       "      <td>3.439533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-10</th>\n",
       "      <td>76.519997</td>\n",
       "      <td>77.949997</td>\n",
       "      <td>76.510002</td>\n",
       "      <td>77.430000</td>\n",
       "      <td>77.430000</td>\n",
       "      <td>29909000</td>\n",
       "      <td>77.589996</td>\n",
       "      <td>-1.069999</td>\n",
       "      <td>-0.803736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-11</th>\n",
       "      <td>77.129997</td>\n",
       "      <td>78.360001</td>\n",
       "      <td>77.050003</td>\n",
       "      <td>77.919998</td>\n",
       "      <td>77.919998</td>\n",
       "      <td>32219000</td>\n",
       "      <td>76.519997</td>\n",
       "      <td>0.610000</td>\n",
       "      <td>1.633941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-12</th>\n",
       "      <td>78.019997</td>\n",
       "      <td>78.300003</td>\n",
       "      <td>77.099998</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>77.480003</td>\n",
       "      <td>26676800</td>\n",
       "      <td>77.129997</td>\n",
       "      <td>0.890000</td>\n",
       "      <td>2.522995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-15</th>\n",
       "      <td>77.150002</td>\n",
       "      <td>77.250000</td>\n",
       "      <td>73.430000</td>\n",
       "      <td>74.580002</td>\n",
       "      <td>74.580002</td>\n",
       "      <td>49679000</td>\n",
       "      <td>78.019997</td>\n",
       "      <td>-0.869995</td>\n",
       "      <td>-0.142376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-16</th>\n",
       "      <td>73.519997</td>\n",
       "      <td>76.230003</td>\n",
       "      <td>73.070000</td>\n",
       "      <td>76.080002</td>\n",
       "      <td>76.080002</td>\n",
       "      <td>37742000</td>\n",
       "      <td>77.150002</td>\n",
       "      <td>-3.630005</td>\n",
       "      <td>-5.245520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-17</th>\n",
       "      <td>75.959999</td>\n",
       "      <td>77.250000</td>\n",
       "      <td>75.570000</td>\n",
       "      <td>76.430000</td>\n",
       "      <td>76.430000</td>\n",
       "      <td>28693000</td>\n",
       "      <td>73.519997</td>\n",
       "      <td>2.440002</td>\n",
       "      <td>-0.731832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-18</th>\n",
       "      <td>76.769997</td>\n",
       "      <td>77.330002</td>\n",
       "      <td>76.519997</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>23031000</td>\n",
       "      <td>75.959999</td>\n",
       "      <td>0.809998</td>\n",
       "      <td>-0.466744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-19</th>\n",
       "      <td>77.400002</td>\n",
       "      <td>78.300003</td>\n",
       "      <td>76.440002</td>\n",
       "      <td>77.910004</td>\n",
       "      <td>77.910004</td>\n",
       "      <td>76671000</td>\n",
       "      <td>76.769997</td>\n",
       "      <td>0.630005</td>\n",
       "      <td>-0.794662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-22</th>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.529999</td>\n",
       "      <td>75.949997</td>\n",
       "      <td>76.800003</td>\n",
       "      <td>76.800003</td>\n",
       "      <td>31961000</td>\n",
       "      <td>77.400002</td>\n",
       "      <td>-0.400002</td>\n",
       "      <td>-0.194429</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>190.550003</td>\n",
       "      <td>193.199997</td>\n",
       "      <td>189.940002</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>16378900</td>\n",
       "      <td>189.880005</td>\n",
       "      <td>0.669998</td>\n",
       "      <td>0.953644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>195.210007</td>\n",
       "      <td>195.279999</td>\n",
       "      <td>191.929993</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>14204700</td>\n",
       "      <td>190.550003</td>\n",
       "      <td>4.660004</td>\n",
       "      <td>1.449958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>193.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>192.710007</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>9050000</td>\n",
       "      <td>195.210007</td>\n",
       "      <td>-2.210007</td>\n",
       "      <td>0.062212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>194.160004</td>\n",
       "      <td>197.399994</td>\n",
       "      <td>194.160004</td>\n",
       "      <td>197.199997</td>\n",
       "      <td>197.199997</td>\n",
       "      <td>10246100</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>1.160004</td>\n",
       "      <td>2.437486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>196.179993</td>\n",
       "      <td>197.070007</td>\n",
       "      <td>194.169998</td>\n",
       "      <td>196.399994</td>\n",
       "      <td>196.399994</td>\n",
       "      <td>11164100</td>\n",
       "      <td>194.160004</td>\n",
       "      <td>2.019989</td>\n",
       "      <td>3.317879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>195.190002</td>\n",
       "      <td>196.679993</td>\n",
       "      <td>193.639999</td>\n",
       "      <td>195.759995</td>\n",
       "      <td>195.759995</td>\n",
       "      <td>9723900</td>\n",
       "      <td>196.179993</td>\n",
       "      <td>-0.989991</td>\n",
       "      <td>2.435056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-09</th>\n",
       "      <td>194.970001</td>\n",
       "      <td>199.460007</td>\n",
       "      <td>194.889999</td>\n",
       "      <td>199.210007</td>\n",
       "      <td>199.210007</td>\n",
       "      <td>14698600</td>\n",
       "      <td>195.190002</td>\n",
       "      <td>-0.220001</td>\n",
       "      <td>-0.122948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-10</th>\n",
       "      <td>200.000000</td>\n",
       "      <td>202.960007</td>\n",
       "      <td>199.669998</td>\n",
       "      <td>202.729996</td>\n",
       "      <td>202.729996</td>\n",
       "      <td>20571700</td>\n",
       "      <td>194.970001</td>\n",
       "      <td>5.029999</td>\n",
       "      <td>3.626943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-11</th>\n",
       "      <td>203.259995</td>\n",
       "      <td>203.800003</td>\n",
       "      <td>200.210007</td>\n",
       "      <td>201.229996</td>\n",
       "      <td>201.229996</td>\n",
       "      <td>13678500</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>3.259995</td>\n",
       "      <td>4.686851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-12</th>\n",
       "      <td>199.679993</td>\n",
       "      <td>205.300003</td>\n",
       "      <td>199.160004</td>\n",
       "      <td>204.869995</td>\n",
       "      <td>204.869995</td>\n",
       "      <td>15366300</td>\n",
       "      <td>203.259995</td>\n",
       "      <td>-3.580002</td>\n",
       "      <td>1.784076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>204.250000</td>\n",
       "      <td>205.330002</td>\n",
       "      <td>201.820007</td>\n",
       "      <td>203.910004</td>\n",
       "      <td>203.910004</td>\n",
       "      <td>16030300</td>\n",
       "      <td>199.679993</td>\n",
       "      <td>4.570007</td>\n",
       "      <td>4.641630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>203.889999</td>\n",
       "      <td>205.470001</td>\n",
       "      <td>203.100006</td>\n",
       "      <td>203.839996</td>\n",
       "      <td>203.839996</td>\n",
       "      <td>12132700</td>\n",
       "      <td>204.250000</td>\n",
       "      <td>-0.360001</td>\n",
       "      <td>4.575062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>204.179993</td>\n",
       "      <td>204.360001</td>\n",
       "      <td>201.589996</td>\n",
       "      <td>201.800003</td>\n",
       "      <td>201.800003</td>\n",
       "      <td>12083700</td>\n",
       "      <td>203.889999</td>\n",
       "      <td>0.289994</td>\n",
       "      <td>2.089996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>200.149994</td>\n",
       "      <td>202.470001</td>\n",
       "      <td>199.380005</td>\n",
       "      <td>200.779999</td>\n",
       "      <td>200.779999</td>\n",
       "      <td>11956600</td>\n",
       "      <td>204.179993</td>\n",
       "      <td>-4.029999</td>\n",
       "      <td>-1.530061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>202.179993</td>\n",
       "      <td>202.330002</td>\n",
       "      <td>198.070007</td>\n",
       "      <td>198.360001</td>\n",
       "      <td>198.360001</td>\n",
       "      <td>12098300</td>\n",
       "      <td>200.149994</td>\n",
       "      <td>2.029999</td>\n",
       "      <td>1.252003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-22</th>\n",
       "      <td>199.910004</td>\n",
       "      <td>202.570007</td>\n",
       "      <td>198.809998</td>\n",
       "      <td>202.320007</td>\n",
       "      <td>202.320007</td>\n",
       "      <td>13589000</td>\n",
       "      <td>202.179993</td>\n",
       "      <td>-2.269989</td>\n",
       "      <td>-2.124845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-23</th>\n",
       "      <td>202.839996</td>\n",
       "      <td>204.240005</td>\n",
       "      <td>200.960007</td>\n",
       "      <td>202.360001</td>\n",
       "      <td>202.360001</td>\n",
       "      <td>14583700</td>\n",
       "      <td>199.910004</td>\n",
       "      <td>2.929992</td>\n",
       "      <td>-0.514985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-24</th>\n",
       "      <td>197.630005</td>\n",
       "      <td>204.809998</td>\n",
       "      <td>197.220001</td>\n",
       "      <td>204.660004</td>\n",
       "      <td>204.660004</td>\n",
       "      <td>32532500</td>\n",
       "      <td>202.839996</td>\n",
       "      <td>-5.209991</td>\n",
       "      <td>-3.207948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-25</th>\n",
       "      <td>206.699997</td>\n",
       "      <td>208.660004</td>\n",
       "      <td>198.259995</td>\n",
       "      <td>200.710007</td>\n",
       "      <td>200.710007</td>\n",
       "      <td>39889900</td>\n",
       "      <td>197.630005</td>\n",
       "      <td>9.069992</td>\n",
       "      <td>3.272547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-26</th>\n",
       "      <td>200.190002</td>\n",
       "      <td>202.880005</td>\n",
       "      <td>196.250000</td>\n",
       "      <td>199.750000</td>\n",
       "      <td>199.750000</td>\n",
       "      <td>24434000</td>\n",
       "      <td>206.699997</td>\n",
       "      <td>-6.509995</td>\n",
       "      <td>-0.984267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-29</th>\n",
       "      <td>199.000000</td>\n",
       "      <td>199.630005</td>\n",
       "      <td>195.300003</td>\n",
       "      <td>195.940002</td>\n",
       "      <td>195.940002</td>\n",
       "      <td>16530800</td>\n",
       "      <td>200.190002</td>\n",
       "      <td>-1.190002</td>\n",
       "      <td>-0.455207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-30</th>\n",
       "      <td>195.389999</td>\n",
       "      <td>198.710007</td>\n",
       "      <td>193.500000</td>\n",
       "      <td>197.039993</td>\n",
       "      <td>197.039993</td>\n",
       "      <td>11903600</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>-3.610001</td>\n",
       "      <td>-3.672844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-31</th>\n",
       "      <td>196.949997</td>\n",
       "      <td>198.759995</td>\n",
       "      <td>192.679993</td>\n",
       "      <td>194.229996</td>\n",
       "      <td>194.229996</td>\n",
       "      <td>14593500</td>\n",
       "      <td>195.389999</td>\n",
       "      <td>1.559998</td>\n",
       "      <td>-0.344081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-01</th>\n",
       "      <td>194.169998</td>\n",
       "      <td>198.470001</td>\n",
       "      <td>190.880005</td>\n",
       "      <td>192.729996</td>\n",
       "      <td>192.729996</td>\n",
       "      <td>17777000</td>\n",
       "      <td>196.949997</td>\n",
       "      <td>-2.779999</td>\n",
       "      <td>-6.061925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-02</th>\n",
       "      <td>191.100006</td>\n",
       "      <td>192.619995</td>\n",
       "      <td>188.070007</td>\n",
       "      <td>189.020004</td>\n",
       "      <td>189.020004</td>\n",
       "      <td>15297000</td>\n",
       "      <td>194.169998</td>\n",
       "      <td>-3.069992</td>\n",
       "      <td>-4.540684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-05</th>\n",
       "      <td>184.690002</td>\n",
       "      <td>185.669998</td>\n",
       "      <td>179.339996</td>\n",
       "      <td>181.729996</td>\n",
       "      <td>181.729996</td>\n",
       "      <td>23086700</td>\n",
       "      <td>191.100006</td>\n",
       "      <td>-6.410004</td>\n",
       "      <td>-7.190954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-06</th>\n",
       "      <td>183.690002</td>\n",
       "      <td>185.789993</td>\n",
       "      <td>183.089996</td>\n",
       "      <td>184.509995</td>\n",
       "      <td>184.509995</td>\n",
       "      <td>18035700</td>\n",
       "      <td>184.690002</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-5.988022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-07</th>\n",
       "      <td>183.600006</td>\n",
       "      <td>186.369995</td>\n",
       "      <td>181.220001</td>\n",
       "      <td>185.149994</td>\n",
       "      <td>185.149994</td>\n",
       "      <td>15833200</td>\n",
       "      <td>183.690002</td>\n",
       "      <td>-0.089996</td>\n",
       "      <td>-6.778366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-08</th>\n",
       "      <td>186.619995</td>\n",
       "      <td>190.339996</td>\n",
       "      <td>184.050003</td>\n",
       "      <td>190.160004</td>\n",
       "      <td>190.160004</td>\n",
       "      <td>14828900</td>\n",
       "      <td>183.600006</td>\n",
       "      <td>3.019989</td>\n",
       "      <td>-3.888347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-09</th>\n",
       "      <td>190.000000</td>\n",
       "      <td>190.979996</td>\n",
       "      <td>187.119995</td>\n",
       "      <td>187.850006</td>\n",
       "      <td>187.850006</td>\n",
       "      <td>10507300</td>\n",
       "      <td>186.619995</td>\n",
       "      <td>3.380005</td>\n",
       "      <td>-0.575618</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1259 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2014-08-11   73.459999   73.910004   73.059998   73.440002   73.440002   \n",
       "2014-08-12   73.089996   73.330002   72.220001   72.830002   72.830002   \n",
       "2014-08-13   73.120003   74.250000   73.050003   73.769997   73.769997   \n",
       "2014-08-14   73.970001   74.379997   73.690002   74.300003   74.300003   \n",
       "2014-08-15   74.320000   74.650002   73.000000   73.629997   73.629997   \n",
       "2014-08-18   74.000000   74.720001   73.959999   74.589996   74.589996   \n",
       "2014-08-19   74.809998   75.580002   74.510002   75.290001   75.290001   \n",
       "2014-08-20   74.970001   75.180000   74.620003   74.809998   74.809998   \n",
       "2014-08-21   74.919998   75.190002   74.410004   74.570000   74.570000   \n",
       "2014-08-22   74.339996   74.730003   73.570000   74.570000   74.570000   \n",
       "2014-08-25   74.940002   75.279999   74.790001   75.019997   75.019997   \n",
       "2014-08-26   75.000000   75.989998   74.730003   75.959999   75.959999   \n",
       "2014-08-27   75.269997   75.489998   74.459999   74.629997   74.629997   \n",
       "2014-08-28   74.000000   74.430000   73.730003   73.860001   73.860001   \n",
       "2014-08-29   74.300003   74.820000   74.010002   74.820000   74.820000   \n",
       "2014-09-02   75.010002   76.699997   74.820000   76.680000   76.680000   \n",
       "2014-09-03   77.139999   77.480003   75.599998   75.830002   75.830002   \n",
       "2014-09-04   75.889999   76.930000   75.529999   75.949997   75.949997   \n",
       "2014-09-05   76.099998   77.379997   75.599998   77.260002   77.260002   \n",
       "2014-09-08   77.260002   78.169998   77.010002   77.889999   77.889999   \n",
       "2014-09-09   77.589996   78.169998   76.199997   76.669998   76.669998   \n",
       "2014-09-10   76.519997   77.949997   76.510002   77.430000   77.430000   \n",
       "2014-09-11   77.129997   78.360001   77.050003   77.919998   77.919998   \n",
       "2014-09-12   78.019997   78.300003   77.099998   77.480003   77.480003   \n",
       "2014-09-15   77.150002   77.250000   73.430000   74.580002   74.580002   \n",
       "2014-09-16   73.519997   76.230003   73.070000   76.080002   76.080002   \n",
       "2014-09-17   75.959999   77.250000   75.570000   76.430000   76.430000   \n",
       "2014-09-18   76.769997   77.330002   76.519997   77.000000   77.000000   \n",
       "2014-09-19   77.400002   78.300003   76.440002   77.910004   77.910004   \n",
       "2014-09-22   77.000000   77.529999   75.949997   76.800003   76.800003   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2019-06-28  190.550003  193.199997  189.940002  193.000000  193.000000   \n",
       "2019-07-01  195.210007  195.279999  191.929993  193.000000  193.000000   \n",
       "2019-07-02  193.000000  195.000000  192.710007  195.000000  195.000000   \n",
       "2019-07-03  194.160004  197.399994  194.160004  197.199997  197.199997   \n",
       "2019-07-05  196.179993  197.070007  194.169998  196.399994  196.399994   \n",
       "2019-07-08  195.190002  196.679993  193.639999  195.759995  195.759995   \n",
       "2019-07-09  194.970001  199.460007  194.889999  199.210007  199.210007   \n",
       "2019-07-10  200.000000  202.960007  199.669998  202.729996  202.729996   \n",
       "2019-07-11  203.259995  203.800003  200.210007  201.229996  201.229996   \n",
       "2019-07-12  199.679993  205.300003  199.160004  204.869995  204.869995   \n",
       "2019-07-15  204.250000  205.330002  201.820007  203.910004  203.910004   \n",
       "2019-07-16  203.889999  205.470001  203.100006  203.839996  203.839996   \n",
       "2019-07-17  204.179993  204.360001  201.589996  201.800003  201.800003   \n",
       "2019-07-18  200.149994  202.470001  199.380005  200.779999  200.779999   \n",
       "2019-07-19  202.179993  202.330002  198.070007  198.360001  198.360001   \n",
       "2019-07-22  199.910004  202.570007  198.809998  202.320007  202.320007   \n",
       "2019-07-23  202.839996  204.240005  200.960007  202.360001  202.360001   \n",
       "2019-07-24  197.630005  204.809998  197.220001  204.660004  204.660004   \n",
       "2019-07-25  206.699997  208.660004  198.259995  200.710007  200.710007   \n",
       "2019-07-26  200.190002  202.880005  196.250000  199.750000  199.750000   \n",
       "2019-07-29  199.000000  199.630005  195.300003  195.940002  195.940002   \n",
       "2019-07-30  195.389999  198.710007  193.500000  197.039993  197.039993   \n",
       "2019-07-31  196.949997  198.759995  192.679993  194.229996  194.229996   \n",
       "2019-08-01  194.169998  198.470001  190.880005  192.729996  192.729996   \n",
       "2019-08-02  191.100006  192.619995  188.070007  189.020004  189.020004   \n",
       "2019-08-05  184.690002  185.669998  179.339996  181.729996  181.729996   \n",
       "2019-08-06  183.690002  185.789993  183.089996  184.509995  184.509995   \n",
       "2019-08-07  183.600006  186.369995  181.220001  185.149994  185.149994   \n",
       "2019-08-08  186.619995  190.339996  184.050003  190.160004  190.160004   \n",
       "2019-08-09  190.000000  190.979996  187.119995  187.850006  187.850006   \n",
       "\n",
       "              Volume  Prev Day Price  Price Change  5 day return  \n",
       "Date                                                              \n",
       "2014-08-11  24591000             NaN           NaN           NaN  \n",
       "2014-08-12  27419000       73.459999     -0.370003           NaN  \n",
       "2014-08-13  29266000       73.089996      0.030007           NaN  \n",
       "2014-08-14  22207000       73.120003      0.849998           NaN  \n",
       "2014-08-15  38846600       73.970001      0.349999           NaN  \n",
       "2014-08-18  23974000       74.320000     -0.320000      0.735095  \n",
       "2014-08-19  26679000       74.000000      0.809998      2.353266  \n",
       "2014-08-20  22917000       74.809998      0.160003      2.530085  \n",
       "2014-08-21  20102000       74.970001     -0.050003      1.284300  \n",
       "2014-08-22  20897000       74.919998     -0.580002      0.026905  \n",
       "2014-08-25  19734000       74.339996      0.600006      1.270273  \n",
       "2014-08-26  23993000       74.940002      0.059998      0.253979  \n",
       "2014-08-27  36323000       75.000000      0.269997      0.400155  \n",
       "2014-08-28  21947000       75.269997     -1.269997     -1.227974  \n",
       "2014-08-29  26241000       74.000000      0.300003     -0.053797  \n",
       "2014-09-02  34979000       74.300003      0.709999      0.093408  \n",
       "2014-09-03  32389000       75.010002      2.129997      2.853332  \n",
       "2014-09-04  26676000       77.139999     -1.250000      0.823704  \n",
       "2014-09-05  29476000       75.889999      0.209999      2.837835  \n",
       "2014-09-08  28183000       76.099998      1.160004      3.983848  \n",
       "2014-09-09  28882000       77.260002      0.329994      3.439533  \n",
       "2014-09-10  29909000       77.589996     -1.069999     -0.803736  \n",
       "2014-09-11  32219000       76.519997      0.610000      1.633941  \n",
       "2014-09-12  26676800       77.129997      0.890000      2.522995  \n",
       "2014-09-15  49679000       78.019997     -0.869995     -0.142376  \n",
       "2014-09-16  37742000       77.150002     -3.630005     -5.245520  \n",
       "2014-09-17  28693000       73.519997      2.440002     -0.731832  \n",
       "2014-09-18  23031000       75.959999      0.809998     -0.466744  \n",
       "2014-09-19  76671000       76.769997      0.630005     -0.794662  \n",
       "2014-09-22  31961000       77.400002     -0.400002     -0.194429  \n",
       "...              ...             ...           ...           ...  \n",
       "2019-06-28  16378900      189.880005      0.669998      0.953644  \n",
       "2019-07-01  14204700      190.550003      4.660004      1.449958  \n",
       "2019-07-02   9050000      195.210007     -2.210007      0.062212  \n",
       "2019-07-03  10246100      193.000000      1.160004      2.437486  \n",
       "2019-07-05  11164100      194.160004      2.019989      3.317879  \n",
       "2019-07-08   9723900      196.179993     -0.989991      2.435056  \n",
       "2019-07-09  14698600      195.190002     -0.220001     -0.122948  \n",
       "2019-07-10  20571700      194.970001      5.029999      3.626943  \n",
       "2019-07-11  13678500      200.000000      3.259995      4.686851  \n",
       "2019-07-12  15366300      203.259995     -3.580002      1.784076  \n",
       "2019-07-15  16030300      199.679993      4.570007      4.641630  \n",
       "2019-07-16  12132700      204.250000     -0.360001      4.575062  \n",
       "2019-07-17  12083700      203.889999      0.289994      2.089996  \n",
       "2019-07-18  11956600      204.179993     -4.029999     -1.530061  \n",
       "2019-07-19  12098300      200.149994      2.029999      1.252003  \n",
       "2019-07-22  13589000      202.179993     -2.269989     -2.124845  \n",
       "2019-07-23  14583700      199.910004      2.929992     -0.514985  \n",
       "2019-07-24  32532500      202.839996     -5.209991     -3.207948  \n",
       "2019-07-25  39889900      197.630005      9.069992      3.272547  \n",
       "2019-07-26  24434000      206.699997     -6.509995     -0.984267  \n",
       "2019-07-29  16530800      200.190002     -1.190002     -0.455207  \n",
       "2019-07-30  11903600      199.000000     -3.610001     -3.672844  \n",
       "2019-07-31  14593500      195.389999      1.559998     -0.344081  \n",
       "2019-08-01  17777000      196.949997     -2.779999     -6.061925  \n",
       "2019-08-02  15297000      194.169998     -3.069992     -4.540684  \n",
       "2019-08-05  23086700      191.100006     -6.410004     -7.190954  \n",
       "2019-08-06  18035700      184.690002     -1.000000     -5.988022  \n",
       "2019-08-07  15833200      183.690002     -0.089996     -6.778366  \n",
       "2019-08-08  14828900      183.600006      3.019989     -3.888347  \n",
       "2019-08-09  10507300      186.619995      3.380005     -0.575618  \n",
       "\n",
       "[1259 rows x 9 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['5 day return'] =  (df['Open'] - df['Open'].shift(5))*100/df['Open'].shift(5)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2014-08-11', '2014-08-12', '2014-08-13', '2014-08-14',\n",
       "               '2014-08-15', '2014-08-18', '2014-08-19', '2014-08-20',\n",
       "               '2014-08-21', '2014-08-22',\n",
       "               ...\n",
       "               '2019-07-29', '2019-07-30', '2019-07-31', '2019-08-01',\n",
       "               '2019-08-02', '2019-08-05', '2019-08-06', '2019-08-07',\n",
       "               '2019-08-08', '2019-08-09'],\n",
       "              dtype='datetime64[ns]', name='Date', length=1259, freq=None)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas import Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/angicia/anaconda3/lib/python3.7/site-packages/pandas/core/series.py:4141: FutureWarning: from_csv is deprecated. Please use read_csv(...) instead. Note that some of the default arguments are different, so please refer to the documentation for from_csv when changing your function calls\n",
      "  infer_datetime_format=infer_datetime_format)\n"
     ]
    }
   ],
   "source": [
    "series = Series.from_csv('daily-min-temperatures.csv', header=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "1981-01-01    20.7\n",
       "1981-01-02    17.9\n",
       "1981-01-03    18.8\n",
       "1981-01-04    14.6\n",
       "1981-01-05    15.8\n",
       "Name: Temp, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb3671bfdd8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "series.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.plotting import autocorrelation_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb33742a160>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "autocorrelation_plot(series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas import Series\n",
    "from pandas import DataFrame\n",
    "from pandas import concat\n",
    "from matplotlib import pyplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "values = DataFrame(series.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>17.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>15.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>17.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>21.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>16.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>13.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>16.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>20.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>20.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>24.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>17.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>18.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>12.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>16.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>18.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>19.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>17.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>15.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3620</th>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3621</th>\n",
       "      <td>16.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3622</th>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3623</th>\n",
       "      <td>20.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3624</th>\n",
       "      <td>20.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3625</th>\n",
       "      <td>19.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3626</th>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3627</th>\n",
       "      <td>14.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3628</th>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3629</th>\n",
       "      <td>11.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3630</th>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3631</th>\n",
       "      <td>11.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3632</th>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3633</th>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3634</th>\n",
       "      <td>13.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3635</th>\n",
       "      <td>13.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3636</th>\n",
       "      <td>17.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3637</th>\n",
       "      <td>14.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3638</th>\n",
       "      <td>15.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3639</th>\n",
       "      <td>13.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3640</th>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3641</th>\n",
       "      <td>13.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3642</th>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3643</th>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3644</th>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3645</th>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3646</th>\n",
       "      <td>13.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3647</th>\n",
       "      <td>13.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3648</th>\n",
       "      <td>15.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3649</th>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3650 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         0\n",
       "0     20.7\n",
       "1     17.9\n",
       "2     18.8\n",
       "3     14.6\n",
       "4     15.8\n",
       "5     15.8\n",
       "6     15.8\n",
       "7     17.4\n",
       "8     21.8\n",
       "9     20.0\n",
       "10    16.2\n",
       "11    13.3\n",
       "12    16.7\n",
       "13    21.5\n",
       "14    25.0\n",
       "15    20.7\n",
       "16    20.6\n",
       "17    24.8\n",
       "18    17.7\n",
       "19    15.5\n",
       "20    18.2\n",
       "21    12.1\n",
       "22    14.4\n",
       "23    16.0\n",
       "24    16.5\n",
       "25    18.7\n",
       "26    19.4\n",
       "27    17.2\n",
       "28    15.5\n",
       "29    15.1\n",
       "...    ...\n",
       "3620  13.2\n",
       "3621  16.2\n",
       "3622  17.3\n",
       "3623  20.5\n",
       "3624  20.2\n",
       "3625  19.4\n",
       "3626  15.5\n",
       "3627  14.1\n",
       "3628  11.0\n",
       "3629  11.1\n",
       "3630  14.0\n",
       "3631  11.4\n",
       "3632  12.5\n",
       "3633  13.4\n",
       "3634  13.6\n",
       "3635  13.9\n",
       "3636  17.2\n",
       "3637  14.7\n",
       "3638  15.4\n",
       "3639  13.1\n",
       "3640  13.2\n",
       "3641  13.9\n",
       "3642  10.0\n",
       "3643  12.9\n",
       "3644  14.6\n",
       "3645  14.0\n",
       "3646  13.6\n",
       "3647  13.5\n",
       "3648  15.7\n",
       "3649  13.0\n",
       "\n",
       "[3650 rows x 1 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframe = concat([values.shift(1), values], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>20.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.7</td>\n",
       "      <td>17.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17.9</td>\n",
       "      <td>18.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>18.8</td>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14.6</td>\n",
       "      <td>15.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15.8</td>\n",
       "      <td>15.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>15.8</td>\n",
       "      <td>15.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>15.8</td>\n",
       "      <td>17.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>17.4</td>\n",
       "      <td>21.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>21.8</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>20.0</td>\n",
       "      <td>16.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>16.2</td>\n",
       "      <td>13.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13.3</td>\n",
       "      <td>16.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>16.7</td>\n",
       "      <td>21.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>21.5</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>25.0</td>\n",
       "      <td>20.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>20.7</td>\n",
       "      <td>20.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>20.6</td>\n",
       "      <td>24.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>24.8</td>\n",
       "      <td>17.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>17.7</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>15.5</td>\n",
       "      <td>18.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>18.2</td>\n",
       "      <td>12.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>12.1</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>14.4</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>16.0</td>\n",
       "      <td>16.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>16.5</td>\n",
       "      <td>18.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>18.7</td>\n",
       "      <td>19.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>19.4</td>\n",
       "      <td>17.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>17.2</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>15.5</td>\n",
       "      <td>15.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3620</th>\n",
       "      <td>13.3</td>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3621</th>\n",
       "      <td>13.2</td>\n",
       "      <td>16.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3622</th>\n",
       "      <td>16.2</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3623</th>\n",
       "      <td>17.3</td>\n",
       "      <td>20.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3624</th>\n",
       "      <td>20.5</td>\n",
       "      <td>20.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3625</th>\n",
       "      <td>20.2</td>\n",
       "      <td>19.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3626</th>\n",
       "      <td>19.4</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3627</th>\n",
       "      <td>15.5</td>\n",
       "      <td>14.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3628</th>\n",
       "      <td>14.1</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3629</th>\n",
       "      <td>11.0</td>\n",
       "      <td>11.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3630</th>\n",
       "      <td>11.1</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3631</th>\n",
       "      <td>14.0</td>\n",
       "      <td>11.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3632</th>\n",
       "      <td>11.4</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3633</th>\n",
       "      <td>12.5</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3634</th>\n",
       "      <td>13.4</td>\n",
       "      <td>13.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3635</th>\n",
       "      <td>13.6</td>\n",
       "      <td>13.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3636</th>\n",
       "      <td>13.9</td>\n",
       "      <td>17.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3637</th>\n",
       "      <td>17.2</td>\n",
       "      <td>14.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3638</th>\n",
       "      <td>14.7</td>\n",
       "      <td>15.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3639</th>\n",
       "      <td>15.4</td>\n",
       "      <td>13.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3640</th>\n",
       "      <td>13.1</td>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3641</th>\n",
       "      <td>13.2</td>\n",
       "      <td>13.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3642</th>\n",
       "      <td>13.9</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3643</th>\n",
       "      <td>10.0</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3644</th>\n",
       "      <td>12.9</td>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3645</th>\n",
       "      <td>14.6</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3646</th>\n",
       "      <td>14.0</td>\n",
       "      <td>13.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3647</th>\n",
       "      <td>13.6</td>\n",
       "      <td>13.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3648</th>\n",
       "      <td>13.5</td>\n",
       "      <td>15.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3649</th>\n",
       "      <td>15.7</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3650 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         0     0\n",
       "0      NaN  20.7\n",
       "1     20.7  17.9\n",
       "2     17.9  18.8\n",
       "3     18.8  14.6\n",
       "4     14.6  15.8\n",
       "5     15.8  15.8\n",
       "6     15.8  15.8\n",
       "7     15.8  17.4\n",
       "8     17.4  21.8\n",
       "9     21.8  20.0\n",
       "10    20.0  16.2\n",
       "11    16.2  13.3\n",
       "12    13.3  16.7\n",
       "13    16.7  21.5\n",
       "14    21.5  25.0\n",
       "15    25.0  20.7\n",
       "16    20.7  20.6\n",
       "17    20.6  24.8\n",
       "18    24.8  17.7\n",
       "19    17.7  15.5\n",
       "20    15.5  18.2\n",
       "21    18.2  12.1\n",
       "22    12.1  14.4\n",
       "23    14.4  16.0\n",
       "24    16.0  16.5\n",
       "25    16.5  18.7\n",
       "26    18.7  19.4\n",
       "27    19.4  17.2\n",
       "28    17.2  15.5\n",
       "29    15.5  15.1\n",
       "...    ...   ...\n",
       "3620  13.3  13.2\n",
       "3621  13.2  16.2\n",
       "3622  16.2  17.3\n",
       "3623  17.3  20.5\n",
       "3624  20.5  20.2\n",
       "3625  20.2  19.4\n",
       "3626  19.4  15.5\n",
       "3627  15.5  14.1\n",
       "3628  14.1  11.0\n",
       "3629  11.0  11.1\n",
       "3630  11.1  14.0\n",
       "3631  14.0  11.4\n",
       "3632  11.4  12.5\n",
       "3633  12.5  13.4\n",
       "3634  13.4  13.6\n",
       "3635  13.6  13.9\n",
       "3636  13.9  17.2\n",
       "3637  17.2  14.7\n",
       "3638  14.7  15.4\n",
       "3639  15.4  13.1\n",
       "3640  13.1  13.2\n",
       "3641  13.2  13.9\n",
       "3642  13.9  10.0\n",
       "3643  10.0  12.9\n",
       "3644  12.9  14.6\n",
       "3645  14.6  14.0\n",
       "3646  14.0  13.6\n",
       "3647  13.6  13.5\n",
       "3648  13.5  15.7\n",
       "3649  15.7  13.0\n",
       "\n",
       "[3650 rows x 2 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframe.columns = ['t-1', 't+1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['t-1', 't+1'], dtype='object')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataframe.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = dataframe.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>t-1</th>\n",
       "      <th>t+1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>t-1</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.77487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>t+1</th>\n",
       "      <td>0.77487</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         t-1      t+1\n",
       "t-1  1.00000  0.77487\n",
       "t+1  0.77487  1.00000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.graphics.tsaplots import plot_acf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_acf(series, lags=31)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas import Series\n",
    "from pandas import DataFrame\n",
    "from pandas import concat\n",
    "from matplotlib import pyplot\n",
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = dataframe.values\n",
    "train, test = X[1:len(X)-7], X[len(X)-7:]\n",
    "train_X, train_y = train[:,0], train[:,1]\n",
    "test_X, test_y = test[:,0], test[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model_persistence(x):\n",
    "    return x\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in test_X:\n",
    "    yhat = model_persistence(x)\n",
    "    predictions.append(yhat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_score = mean_squared_error(test_y, predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.4228571428571413"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyplot.plot(test_y)\n",
    "pyplot.plot(predictions, color='red')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = series.values\n",
    "train, test = X[1:len(X)-7], X[len(X)-7:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.ar_model import AR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = AR(train)\n",
    "model_fit = model.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lag: 29\n",
      "Coefficients: [ 5.57543506e-01  5.88595221e-01 -9.08257090e-02  4.82615092e-02\n",
      "  4.00650265e-02  3.93020055e-02  2.59463738e-02  4.46675960e-02\n",
      "  1.27681498e-02  3.74362239e-02 -8.11700276e-04  4.79081949e-03\n",
      "  1.84731397e-02  2.68908418e-02  5.75906178e-04  2.48096415e-02\n",
      "  7.40316579e-03  9.91622149e-03  3.41599123e-02 -9.11961877e-03\n",
      "  2.42127561e-02  1.87870751e-02  1.21841870e-02 -1.85534575e-02\n",
      " -1.77162867e-03  1.67319894e-02  1.97615668e-02  9.83245087e-03\n",
      "  6.22710723e-03 -1.37732255e-03]\n"
     ]
    }
   ],
   "source": [
    "print('Lag: %s' % model_fit.k_ar)\n",
    "print('Coefficients: %s' % model_fit.params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = model_fit.predict(start=len(train), end=len(train)+len(test)-1, dynamic=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predicted=11.871275, expected=12.900000\n",
      "predicted=13.053794, expected=14.600000\n",
      "predicted=13.532591, expected=14.000000\n",
      "predicted=13.243126, expected=13.600000\n",
      "predicted=13.091438, expected=13.500000\n",
      "predicted=13.146989, expected=15.700000\n",
      "predicted=13.176153, expected=13.000000\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(predictions)):\n",
    "    print('predicted=%f, expected=%f' % (predictions[i], test[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "error = mean_squared_error(test, predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test MSE: 1.502\n"
     ]
    }
   ],
   "source": [
    "print('Test MSE: %.3f' % error)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyplot.plot(test)\n",
    "pyplot.plot(predictions, color='red')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "window = model_fit.k_ar\n",
    "coef = model_fit.params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "history = train[len(train)-window:]\n",
    "history = [history[i] for i in range(len(history))]\n",
    "predictions = list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predicted=11.871275, expected=12.900000\n",
      "predicted=13.659297, expected=14.600000\n",
      "predicted=14.349246, expected=14.000000\n",
      "predicted=13.427454, expected=13.600000\n",
      "predicted=13.374877, expected=13.500000\n",
      "predicted=13.479991, expected=15.700000\n",
      "predicted=14.765146, expected=13.000000\n"
     ]
    }
   ],
   "source": [
    "for t in range(len(test)):\n",
    "    length = len(history)\n",
    "    lag = [history[i] for i in range(length-window,length)]\n",
    "    yhat = coef[0]\n",
    "    for d in range(window):\n",
    "        yhat += coef[d+1] * lag[window-d-1]\n",
    "    obs = test[t]\n",
    "    predictions.append(yhat)\n",
    "    history.append(obs)\n",
    "    print('predicted=%f, expected=%f' % (yhat, obs))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test MSE: 1.451\n"
     ]
    }
   ],
   "source": [
    "error = mean_squared_error(test, predictions)\n",
    "print('Test MSE: %.3f' % error)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyplot.plot(test)\n",
    "pyplot.plot(predictions, color='red')\n",
    "pyplot.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}