Pandas Data Reader.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas_datareader import data\n",
    "from pandas.tseries.offsets import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "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>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</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>2009-12-31</th>\n",
       "      <td>30.990000</td>\n",
       "      <td>30.480000</td>\n",
       "      <td>30.980000</td>\n",
       "      <td>30.480000</td>\n",
       "      <td>31929700.0</td>\n",
       "      <td>24.345514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>31.100000</td>\n",
       "      <td>30.590000</td>\n",
       "      <td>30.620001</td>\n",
       "      <td>30.950001</td>\n",
       "      <td>38409100.0</td>\n",
       "      <td>24.720928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>31.100000</td>\n",
       "      <td>30.639999</td>\n",
       "      <td>30.850000</td>\n",
       "      <td>30.959999</td>\n",
       "      <td>49749600.0</td>\n",
       "      <td>24.728914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>31.080000</td>\n",
       "      <td>30.520000</td>\n",
       "      <td>30.879999</td>\n",
       "      <td>30.770000</td>\n",
       "      <td>58182400.0</td>\n",
       "      <td>24.577150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>30.700001</td>\n",
       "      <td>30.190001</td>\n",
       "      <td>30.629999</td>\n",
       "      <td>30.450001</td>\n",
       "      <td>50559700.0</td>\n",
       "      <td>24.321552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>30.879999</td>\n",
       "      <td>30.240000</td>\n",
       "      <td>30.280001</td>\n",
       "      <td>30.660000</td>\n",
       "      <td>51197400.0</td>\n",
       "      <td>24.489288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-11</th>\n",
       "      <td>30.760000</td>\n",
       "      <td>30.120001</td>\n",
       "      <td>30.709999</td>\n",
       "      <td>30.270000</td>\n",
       "      <td>68754700.0</td>\n",
       "      <td>24.177786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-12</th>\n",
       "      <td>30.400000</td>\n",
       "      <td>29.910000</td>\n",
       "      <td>30.150000</td>\n",
       "      <td>30.070000</td>\n",
       "      <td>65912100.0</td>\n",
       "      <td>24.018032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-13</th>\n",
       "      <td>30.520000</td>\n",
       "      <td>30.010000</td>\n",
       "      <td>30.260000</td>\n",
       "      <td>30.350000</td>\n",
       "      <td>51863500.0</td>\n",
       "      <td>24.241684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-14</th>\n",
       "      <td>31.100000</td>\n",
       "      <td>30.260000</td>\n",
       "      <td>30.309999</td>\n",
       "      <td>30.959999</td>\n",
       "      <td>63228100.0</td>\n",
       "      <td>24.728914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-15</th>\n",
       "      <td>31.240000</td>\n",
       "      <td>30.709999</td>\n",
       "      <td>31.080000</td>\n",
       "      <td>30.860001</td>\n",
       "      <td>79913200.0</td>\n",
       "      <td>24.649038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-19</th>\n",
       "      <td>31.240000</td>\n",
       "      <td>30.680000</td>\n",
       "      <td>30.750000</td>\n",
       "      <td>31.100000</td>\n",
       "      <td>46575700.0</td>\n",
       "      <td>24.840738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-20</th>\n",
       "      <td>30.940001</td>\n",
       "      <td>30.309999</td>\n",
       "      <td>30.809999</td>\n",
       "      <td>30.590000</td>\n",
       "      <td>54849500.0</td>\n",
       "      <td>24.433378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-21</th>\n",
       "      <td>30.719999</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.610001</td>\n",
       "      <td>30.010000</td>\n",
       "      <td>73086700.0</td>\n",
       "      <td>23.970112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-22</th>\n",
       "      <td>30.200001</td>\n",
       "      <td>28.840000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>28.959999</td>\n",
       "      <td>102004600.0</td>\n",
       "      <td>23.131437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-25</th>\n",
       "      <td>29.660000</td>\n",
       "      <td>29.100000</td>\n",
       "      <td>29.240000</td>\n",
       "      <td>29.320000</td>\n",
       "      <td>63373000.0</td>\n",
       "      <td>23.418983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-26</th>\n",
       "      <td>29.850000</td>\n",
       "      <td>29.090000</td>\n",
       "      <td>29.200001</td>\n",
       "      <td>29.500000</td>\n",
       "      <td>66639900.0</td>\n",
       "      <td>23.562756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-27</th>\n",
       "      <td>29.820000</td>\n",
       "      <td>29.020000</td>\n",
       "      <td>29.350000</td>\n",
       "      <td>29.670000</td>\n",
       "      <td>63949500.0</td>\n",
       "      <td>23.698549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-28</th>\n",
       "      <td>29.870001</td>\n",
       "      <td>28.889999</td>\n",
       "      <td>29.840000</td>\n",
       "      <td>29.160000</td>\n",
       "      <td>117513700.0</td>\n",
       "      <td>23.291180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-29</th>\n",
       "      <td>29.920000</td>\n",
       "      <td>27.660000</td>\n",
       "      <td>29.900000</td>\n",
       "      <td>28.180000</td>\n",
       "      <td>193888500.0</td>\n",
       "      <td>22.508421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-01</th>\n",
       "      <td>28.480000</td>\n",
       "      <td>27.920000</td>\n",
       "      <td>28.389999</td>\n",
       "      <td>28.410000</td>\n",
       "      <td>85931100.0</td>\n",
       "      <td>22.692129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-02</th>\n",
       "      <td>28.500000</td>\n",
       "      <td>28.139999</td>\n",
       "      <td>28.370001</td>\n",
       "      <td>28.459999</td>\n",
       "      <td>54413700.0</td>\n",
       "      <td>22.732069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-03</th>\n",
       "      <td>28.790001</td>\n",
       "      <td>28.120001</td>\n",
       "      <td>28.260000</td>\n",
       "      <td>28.629999</td>\n",
       "      <td>61397900.0</td>\n",
       "      <td>22.867855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-04</th>\n",
       "      <td>28.500000</td>\n",
       "      <td>27.809999</td>\n",
       "      <td>28.379999</td>\n",
       "      <td>27.840000</td>\n",
       "      <td>77850000.0</td>\n",
       "      <td>22.236853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-05</th>\n",
       "      <td>28.280001</td>\n",
       "      <td>27.570000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>28.020000</td>\n",
       "      <td>80960100.0</td>\n",
       "      <td>22.380629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-08</th>\n",
       "      <td>28.080000</td>\n",
       "      <td>27.570000</td>\n",
       "      <td>28.010000</td>\n",
       "      <td>27.719999</td>\n",
       "      <td>52820600.0</td>\n",
       "      <td>22.141001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-09</th>\n",
       "      <td>28.340000</td>\n",
       "      <td>27.750000</td>\n",
       "      <td>27.969999</td>\n",
       "      <td>28.010000</td>\n",
       "      <td>59195800.0</td>\n",
       "      <td>22.372641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-10</th>\n",
       "      <td>28.240000</td>\n",
       "      <td>27.840000</td>\n",
       "      <td>28.030001</td>\n",
       "      <td>27.990000</td>\n",
       "      <td>48591300.0</td>\n",
       "      <td>22.356657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-11</th>\n",
       "      <td>28.400000</td>\n",
       "      <td>27.700001</td>\n",
       "      <td>27.930000</td>\n",
       "      <td>28.120001</td>\n",
       "      <td>65993700.0</td>\n",
       "      <td>22.460506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-12</th>\n",
       "      <td>28.059999</td>\n",
       "      <td>27.580000</td>\n",
       "      <td>27.809999</td>\n",
       "      <td>27.930000</td>\n",
       "      <td>81117200.0</td>\n",
       "      <td>22.308741</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>2019-01-02</th>\n",
       "      <td>101.750000</td>\n",
       "      <td>98.940002</td>\n",
       "      <td>99.550003</td>\n",
       "      <td>101.120003</td>\n",
       "      <td>35329300.0</td>\n",
       "      <td>101.120003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-03</th>\n",
       "      <td>100.190002</td>\n",
       "      <td>97.199997</td>\n",
       "      <td>100.099998</td>\n",
       "      <td>97.400002</td>\n",
       "      <td>42579100.0</td>\n",
       "      <td>97.400002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-04</th>\n",
       "      <td>102.510002</td>\n",
       "      <td>98.930000</td>\n",
       "      <td>99.720001</td>\n",
       "      <td>101.930000</td>\n",
       "      <td>44060600.0</td>\n",
       "      <td>101.930000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-07</th>\n",
       "      <td>103.269997</td>\n",
       "      <td>100.980003</td>\n",
       "      <td>101.639999</td>\n",
       "      <td>102.059998</td>\n",
       "      <td>35656100.0</td>\n",
       "      <td>102.059998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-08</th>\n",
       "      <td>103.970001</td>\n",
       "      <td>101.709999</td>\n",
       "      <td>103.040001</td>\n",
       "      <td>102.800003</td>\n",
       "      <td>31514400.0</td>\n",
       "      <td>102.800003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-09</th>\n",
       "      <td>104.879997</td>\n",
       "      <td>103.239998</td>\n",
       "      <td>103.860001</td>\n",
       "      <td>104.269997</td>\n",
       "      <td>32280800.0</td>\n",
       "      <td>104.269997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-10</th>\n",
       "      <td>103.750000</td>\n",
       "      <td>102.379997</td>\n",
       "      <td>103.220001</td>\n",
       "      <td>103.599998</td>\n",
       "      <td>30067600.0</td>\n",
       "      <td>103.599998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-11</th>\n",
       "      <td>103.440002</td>\n",
       "      <td>101.639999</td>\n",
       "      <td>103.190002</td>\n",
       "      <td>102.800003</td>\n",
       "      <td>28314200.0</td>\n",
       "      <td>102.800003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-14</th>\n",
       "      <td>102.870003</td>\n",
       "      <td>101.260002</td>\n",
       "      <td>101.900002</td>\n",
       "      <td>102.050003</td>\n",
       "      <td>28437100.0</td>\n",
       "      <td>102.050003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-15</th>\n",
       "      <td>105.050003</td>\n",
       "      <td>101.879997</td>\n",
       "      <td>102.510002</td>\n",
       "      <td>105.010002</td>\n",
       "      <td>31587600.0</td>\n",
       "      <td>105.010002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-16</th>\n",
       "      <td>106.260002</td>\n",
       "      <td>104.959999</td>\n",
       "      <td>105.260002</td>\n",
       "      <td>105.379997</td>\n",
       "      <td>29853900.0</td>\n",
       "      <td>105.379997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-17</th>\n",
       "      <td>106.629997</td>\n",
       "      <td>104.760002</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>106.120003</td>\n",
       "      <td>28393000.0</td>\n",
       "      <td>106.120003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-18</th>\n",
       "      <td>107.900002</td>\n",
       "      <td>105.910004</td>\n",
       "      <td>107.459999</td>\n",
       "      <td>107.709999</td>\n",
       "      <td>37427600.0</td>\n",
       "      <td>107.709999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-22</th>\n",
       "      <td>107.099998</td>\n",
       "      <td>104.860001</td>\n",
       "      <td>106.750000</td>\n",
       "      <td>105.680000</td>\n",
       "      <td>32371300.0</td>\n",
       "      <td>105.680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-23</th>\n",
       "      <td>107.040001</td>\n",
       "      <td>105.339996</td>\n",
       "      <td>106.120003</td>\n",
       "      <td>106.709999</td>\n",
       "      <td>25874300.0</td>\n",
       "      <td>106.709999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-24</th>\n",
       "      <td>107.000000</td>\n",
       "      <td>105.339996</td>\n",
       "      <td>106.860001</td>\n",
       "      <td>106.199997</td>\n",
       "      <td>23164800.0</td>\n",
       "      <td>106.199997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-25</th>\n",
       "      <td>107.879997</td>\n",
       "      <td>106.199997</td>\n",
       "      <td>107.239998</td>\n",
       "      <td>107.169998</td>\n",
       "      <td>31225600.0</td>\n",
       "      <td>107.169998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-28</th>\n",
       "      <td>106.480003</td>\n",
       "      <td>104.660004</td>\n",
       "      <td>106.260002</td>\n",
       "      <td>105.080002</td>\n",
       "      <td>29476700.0</td>\n",
       "      <td>105.080002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-29</th>\n",
       "      <td>104.970001</td>\n",
       "      <td>102.169998</td>\n",
       "      <td>104.879997</td>\n",
       "      <td>102.940002</td>\n",
       "      <td>31490500.0</td>\n",
       "      <td>102.940002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-30</th>\n",
       "      <td>106.379997</td>\n",
       "      <td>104.330002</td>\n",
       "      <td>104.620003</td>\n",
       "      <td>106.379997</td>\n",
       "      <td>49471900.0</td>\n",
       "      <td>106.379997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-31</th>\n",
       "      <td>105.220001</td>\n",
       "      <td>103.180000</td>\n",
       "      <td>103.800003</td>\n",
       "      <td>104.430000</td>\n",
       "      <td>55636400.0</td>\n",
       "      <td>104.430000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-01</th>\n",
       "      <td>104.099998</td>\n",
       "      <td>102.349998</td>\n",
       "      <td>103.779999</td>\n",
       "      <td>102.779999</td>\n",
       "      <td>35535700.0</td>\n",
       "      <td>102.779999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-04</th>\n",
       "      <td>105.800003</td>\n",
       "      <td>102.769997</td>\n",
       "      <td>102.870003</td>\n",
       "      <td>105.739998</td>\n",
       "      <td>31315100.0</td>\n",
       "      <td>105.739998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-05</th>\n",
       "      <td>107.269997</td>\n",
       "      <td>105.959999</td>\n",
       "      <td>106.059998</td>\n",
       "      <td>107.220001</td>\n",
       "      <td>27325400.0</td>\n",
       "      <td>107.220001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-06</th>\n",
       "      <td>107.000000</td>\n",
       "      <td>105.529999</td>\n",
       "      <td>107.000000</td>\n",
       "      <td>106.029999</td>\n",
       "      <td>20609800.0</td>\n",
       "      <td>106.029999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-07</th>\n",
       "      <td>105.589996</td>\n",
       "      <td>104.290001</td>\n",
       "      <td>105.190002</td>\n",
       "      <td>105.269997</td>\n",
       "      <td>29760700.0</td>\n",
       "      <td>105.269997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-08</th>\n",
       "      <td>105.779999</td>\n",
       "      <td>104.260002</td>\n",
       "      <td>104.389999</td>\n",
       "      <td>105.669998</td>\n",
       "      <td>21461100.0</td>\n",
       "      <td>105.669998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-11</th>\n",
       "      <td>106.580002</td>\n",
       "      <td>104.970001</td>\n",
       "      <td>106.199997</td>\n",
       "      <td>105.250000</td>\n",
       "      <td>18914100.0</td>\n",
       "      <td>105.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-12</th>\n",
       "      <td>107.139999</td>\n",
       "      <td>105.480003</td>\n",
       "      <td>106.139999</td>\n",
       "      <td>106.889999</td>\n",
       "      <td>25021300.0</td>\n",
       "      <td>106.889999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-13</th>\n",
       "      <td>107.779999</td>\n",
       "      <td>106.950203</td>\n",
       "      <td>107.500000</td>\n",
       "      <td>107.220001</td>\n",
       "      <td>6004158.0</td>\n",
       "      <td>107.220001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2295 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  High         Low        Open       Close       Volume  \\\n",
       "Date                                                                      \n",
       "2009-12-31   30.990000   30.480000   30.980000   30.480000   31929700.0   \n",
       "2010-01-04   31.100000   30.590000   30.620001   30.950001   38409100.0   \n",
       "2010-01-05   31.100000   30.639999   30.850000   30.959999   49749600.0   \n",
       "2010-01-06   31.080000   30.520000   30.879999   30.770000   58182400.0   \n",
       "2010-01-07   30.700001   30.190001   30.629999   30.450001   50559700.0   \n",
       "2010-01-08   30.879999   30.240000   30.280001   30.660000   51197400.0   \n",
       "2010-01-11   30.760000   30.120001   30.709999   30.270000   68754700.0   \n",
       "2010-01-12   30.400000   29.910000   30.150000   30.070000   65912100.0   \n",
       "2010-01-13   30.520000   30.010000   30.260000   30.350000   51863500.0   \n",
       "2010-01-14   31.100000   30.260000   30.309999   30.959999   63228100.0   \n",
       "2010-01-15   31.240000   30.709999   31.080000   30.860001   79913200.0   \n",
       "2010-01-19   31.240000   30.680000   30.750000   31.100000   46575700.0   \n",
       "2010-01-20   30.940001   30.309999   30.809999   30.590000   54849500.0   \n",
       "2010-01-21   30.719999   30.000000   30.610001   30.010000   73086700.0   \n",
       "2010-01-22   30.200001   28.840000   30.000000   28.959999  102004600.0   \n",
       "2010-01-25   29.660000   29.100000   29.240000   29.320000   63373000.0   \n",
       "2010-01-26   29.850000   29.090000   29.200001   29.500000   66639900.0   \n",
       "2010-01-27   29.820000   29.020000   29.350000   29.670000   63949500.0   \n",
       "2010-01-28   29.870001   28.889999   29.840000   29.160000  117513700.0   \n",
       "2010-01-29   29.920000   27.660000   29.900000   28.180000  193888500.0   \n",
       "2010-02-01   28.480000   27.920000   28.389999   28.410000   85931100.0   \n",
       "2010-02-02   28.500000   28.139999   28.370001   28.459999   54413700.0   \n",
       "2010-02-03   28.790001   28.120001   28.260000   28.629999   61397900.0   \n",
       "2010-02-04   28.500000   27.809999   28.379999   27.840000   77850000.0   \n",
       "2010-02-05   28.280001   27.570000   28.000000   28.020000   80960100.0   \n",
       "2010-02-08   28.080000   27.570000   28.010000   27.719999   52820600.0   \n",
       "2010-02-09   28.340000   27.750000   27.969999   28.010000   59195800.0   \n",
       "2010-02-10   28.240000   27.840000   28.030001   27.990000   48591300.0   \n",
       "2010-02-11   28.400000   27.700001   27.930000   28.120001   65993700.0   \n",
       "2010-02-12   28.059999   27.580000   27.809999   27.930000   81117200.0   \n",
       "...                ...         ...         ...         ...          ...   \n",
       "2019-01-02  101.750000   98.940002   99.550003  101.120003   35329300.0   \n",
       "2019-01-03  100.190002   97.199997  100.099998   97.400002   42579100.0   \n",
       "2019-01-04  102.510002   98.930000   99.720001  101.930000   44060600.0   \n",
       "2019-01-07  103.269997  100.980003  101.639999  102.059998   35656100.0   \n",
       "2019-01-08  103.970001  101.709999  103.040001  102.800003   31514400.0   \n",
       "2019-01-09  104.879997  103.239998  103.860001  104.269997   32280800.0   \n",
       "2019-01-10  103.750000  102.379997  103.220001  103.599998   30067600.0   \n",
       "2019-01-11  103.440002  101.639999  103.190002  102.800003   28314200.0   \n",
       "2019-01-14  102.870003  101.260002  101.900002  102.050003   28437100.0   \n",
       "2019-01-15  105.050003  101.879997  102.510002  105.010002   31587600.0   \n",
       "2019-01-16  106.260002  104.959999  105.260002  105.379997   29853900.0   \n",
       "2019-01-17  106.629997  104.760002  105.000000  106.120003   28393000.0   \n",
       "2019-01-18  107.900002  105.910004  107.459999  107.709999   37427600.0   \n",
       "2019-01-22  107.099998  104.860001  106.750000  105.680000   32371300.0   \n",
       "2019-01-23  107.040001  105.339996  106.120003  106.709999   25874300.0   \n",
       "2019-01-24  107.000000  105.339996  106.860001  106.199997   23164800.0   \n",
       "2019-01-25  107.879997  106.199997  107.239998  107.169998   31225600.0   \n",
       "2019-01-28  106.480003  104.660004  106.260002  105.080002   29476700.0   \n",
       "2019-01-29  104.970001  102.169998  104.879997  102.940002   31490500.0   \n",
       "2019-01-30  106.379997  104.330002  104.620003  106.379997   49471900.0   \n",
       "2019-01-31  105.220001  103.180000  103.800003  104.430000   55636400.0   \n",
       "2019-02-01  104.099998  102.349998  103.779999  102.779999   35535700.0   \n",
       "2019-02-04  105.800003  102.769997  102.870003  105.739998   31315100.0   \n",
       "2019-02-05  107.269997  105.959999  106.059998  107.220001   27325400.0   \n",
       "2019-02-06  107.000000  105.529999  107.000000  106.029999   20609800.0   \n",
       "2019-02-07  105.589996  104.290001  105.190002  105.269997   29760700.0   \n",
       "2019-02-08  105.779999  104.260002  104.389999  105.669998   21461100.0   \n",
       "2019-02-11  106.580002  104.970001  106.199997  105.250000   18914100.0   \n",
       "2019-02-12  107.139999  105.480003  106.139999  106.889999   25021300.0   \n",
       "2019-02-13  107.779999  106.950203  107.500000  107.220001    6004158.0   \n",
       "\n",
       "             Adj Close  \n",
       "Date                    \n",
       "2009-12-31   24.345514  \n",
       "2010-01-04   24.720928  \n",
       "2010-01-05   24.728914  \n",
       "2010-01-06   24.577150  \n",
       "2010-01-07   24.321552  \n",
       "2010-01-08   24.489288  \n",
       "2010-01-11   24.177786  \n",
       "2010-01-12   24.018032  \n",
       "2010-01-13   24.241684  \n",
       "2010-01-14   24.728914  \n",
       "2010-01-15   24.649038  \n",
       "2010-01-19   24.840738  \n",
       "2010-01-20   24.433378  \n",
       "2010-01-21   23.970112  \n",
       "2010-01-22   23.131437  \n",
       "2010-01-25   23.418983  \n",
       "2010-01-26   23.562756  \n",
       "2010-01-27   23.698549  \n",
       "2010-01-28   23.291180  \n",
       "2010-01-29   22.508421  \n",
       "2010-02-01   22.692129  \n",
       "2010-02-02   22.732069  \n",
       "2010-02-03   22.867855  \n",
       "2010-02-04   22.236853  \n",
       "2010-02-05   22.380629  \n",
       "2010-02-08   22.141001  \n",
       "2010-02-09   22.372641  \n",
       "2010-02-10   22.356657  \n",
       "2010-02-11   22.460506  \n",
       "2010-02-12   22.308741  \n",
       "...                ...  \n",
       "2019-01-02  101.120003  \n",
       "2019-01-03   97.400002  \n",
       "2019-01-04  101.930000  \n",
       "2019-01-07  102.059998  \n",
       "2019-01-08  102.800003  \n",
       "2019-01-09  104.269997  \n",
       "2019-01-10  103.599998  \n",
       "2019-01-11  102.800003  \n",
       "2019-01-14  102.050003  \n",
       "2019-01-15  105.010002  \n",
       "2019-01-16  105.379997  \n",
       "2019-01-17  106.120003  \n",
       "2019-01-18  107.709999  \n",
       "2019-01-22  105.680000  \n",
       "2019-01-23  106.709999  \n",
       "2019-01-24  106.199997  \n",
       "2019-01-25  107.169998  \n",
       "2019-01-28  105.080002  \n",
       "2019-01-29  102.940002  \n",
       "2019-01-30  106.379997  \n",
       "2019-01-31  104.430000  \n",
       "2019-02-01  102.779999  \n",
       "2019-02-04  105.739998  \n",
       "2019-02-05  107.220001  \n",
       "2019-02-06  106.029999  \n",
       "2019-02-07  105.269997  \n",
       "2019-02-08  105.669998  \n",
       "2019-02-11  105.250000  \n",
       "2019-02-12  106.889999  \n",
       "2019-02-13  107.220001  \n",
       "\n",
       "[2295 rows x 6 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "company = \"MSFT\" # Stock market symbol of microsoft\n",
    "start = '2010-1-1'\n",
    "end = '2019-2-13'\n",
    "\n",
    "stocks = data.DataReader(name=company,data_source=\"yahoo\",start=start,end=end)\n",
    "stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3.09899998e+01, 3.04799995e+01, 3.09799995e+01, 3.04799995e+01,\n",
       "        3.19297000e+07, 2.43455143e+01],\n",
       "       [3.11000004e+01, 3.05900002e+01, 3.06200008e+01, 3.09500008e+01,\n",
       "        3.84091000e+07, 2.47209282e+01],\n",
       "       [3.11000004e+01, 3.06399994e+01, 3.08500004e+01, 3.09599991e+01,\n",
       "        4.97496000e+07, 2.47289143e+01],\n",
       "       ...,\n",
       "       [1.06580002e+02, 1.04970001e+02, 1.06199997e+02, 1.05250000e+02,\n",
       "        1.89141000e+07, 1.05250000e+02],\n",
       "       [1.07139999e+02, 1.05480003e+02, 1.06139999e+02, 1.06889999e+02,\n",
       "        2.50213000e+07, 1.06889999e+02],\n",
       "       [1.07779999e+02, 1.06950203e+02, 1.07500000e+02, 1.07220001e+02,\n",
       "        6.00415800e+06, 1.07220001e+02]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['High', 'Low', 'Open', 'Close', 'Volume', 'Adj Close'], dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2009-12-31', '2010-01-04', '2010-01-05', '2010-01-06',\n",
       "               '2010-01-07', '2010-01-08', '2010-01-11', '2010-01-12',\n",
       "               '2010-01-13', '2010-01-14',\n",
       "               ...\n",
       "               '2019-01-31', '2019-02-01', '2019-02-04', '2019-02-05',\n",
       "               '2019-02-06', '2019-02-07', '2019-02-08', '2019-02-11',\n",
       "               '2019-02-12', '2019-02-13'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2295, freq=None)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2009-12-31 00:00:00')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.index[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[DatetimeIndex(['2009-12-31', '2010-01-04', '2010-01-05', '2010-01-06',\n",
       "                '2010-01-07', '2010-01-08', '2010-01-11', '2010-01-12',\n",
       "                '2010-01-13', '2010-01-14',\n",
       "                ...\n",
       "                '2019-01-31', '2019-02-01', '2019-02-04', '2019-02-05',\n",
       "                '2019-02-06', '2019-02-07', '2019-02-08', '2019-02-11',\n",
       "                '2019-02-12', '2019-02-13'],\n",
       "               dtype='datetime64[ns]', name='Date', length=2295, freq=None),\n",
       " Index(['High', 'Low', 'Open', 'Close', 'Volume', 'Adj Close'], dtype='object')]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.axes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecting from a dataframe with a DateTimeIndex"
   ]
  },
  {
   "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>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</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>2009-12-31</th>\n",
       "      <td>30.99</td>\n",
       "      <td>30.480000</td>\n",
       "      <td>30.980000</td>\n",
       "      <td>30.480000</td>\n",
       "      <td>31929700.0</td>\n",
       "      <td>24.345514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>31.10</td>\n",
       "      <td>30.590000</td>\n",
       "      <td>30.620001</td>\n",
       "      <td>30.950001</td>\n",
       "      <td>38409100.0</td>\n",
       "      <td>24.720928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>31.10</td>\n",
       "      <td>30.639999</td>\n",
       "      <td>30.850000</td>\n",
       "      <td>30.959999</td>\n",
       "      <td>49749600.0</td>\n",
       "      <td>24.728914</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             High        Low       Open      Close      Volume  Adj Close\n",
       "Date                                                                     \n",
       "2009-12-31  30.99  30.480000  30.980000  30.480000  31929700.0  24.345514\n",
       "2010-01-04  31.10  30.590000  30.620001  30.950001  38409100.0  24.720928\n",
       "2010-01-05  31.10  30.639999  30.850000  30.959999  49749600.0  24.728914"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks = data.DataReader(name=company,data_source=\"yahoo\",start=start,end=end)\n",
    "stocks.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "High         3.813000e+01\n",
       "Low          3.749000e+01\n",
       "Open         3.792000e+01\n",
       "Close        3.778000e+01\n",
       "Volume       2.971750e+07\n",
       "Adj Close    3.375268e+01\n",
       "Name: 2014-03-03 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.loc[\"2014-3-3\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'2016-1-1'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: an integer is required",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   2655\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2656\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2657\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine._date_check_type\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: '2016-1-1'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: an integer is required",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\datetimes.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   1008\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1009\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mIndex\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1010\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   2657\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2658\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2659\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine._date_check_type\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: '2016-1-1'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 1451606400000000000",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   2655\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2656\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2657\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: Timestamp('2016-01-01 00:00:00')",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 1451606400000000000",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\datetimes.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   1021\u001b[0m                     \u001b[0mstamp\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mstamp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtz_localize\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtz\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1022\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mIndex\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstamp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1023\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   2657\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2658\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2659\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: Timestamp('2016-01-01 00:00:00')",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-11-d5cb090ff6ae>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mstocks\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"2016-1-1\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;31m# Gives error because that day is not business day so stock market was not open on that day\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   1498\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1499\u001b[0m             \u001b[0mmaybe_callable\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_if_callable\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1500\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmaybe_callable\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1501\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1502\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_is_scalar_access\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[1;34m(self, key, axis)\u001b[0m\n\u001b[0;32m   1911\u001b[0m         \u001b[1;31m# fall thru to straight lookup\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1912\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1913\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_label\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1914\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1915\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_get_label\u001b[1;34m(self, label, axis)\u001b[0m\n\u001b[0;32m    139\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mIndexingError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'no slices here, handle elsewhere'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    140\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 141\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_xs\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    142\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    143\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_get_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36mxs\u001b[1;34m(self, key, axis, level, drop_level)\u001b[0m\n\u001b[0;32m   3583\u001b[0m                                                       drop_level=drop_level)\n\u001b[0;32m   3584\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3585\u001b[1;33m             \u001b[0mloc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3586\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3587\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\datetimes.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   1022\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mIndex\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstamp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1023\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1024\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1025\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1026\u001b[0m                 \u001b[1;31m# list-like tolerance size must match target index size\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: '2016-1-1'"
     ]
    }
   ],
   "source": [
    "stocks.loc[\"2016-1-1\"]\n",
    "\n",
    "# Gives error because that day is not business day so stock market was not open on that day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "stocks.loc['2011-1-1':'2012-1-1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "birthdays = pd.date_range(start='1997-05-16',end='2018-12-31',freq=pd.DateOffset(years = 1))\n",
    "# To get all my bdays betwwen 1997 and 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = stocks.index.isin(birthdays)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks[mask]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Timestamp object attributes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks = data.DataReader(name=company,data_source=\"yahoo\",start=start,end=end)\n",
    "stocks.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "someday = stocks.index[500]\n",
    "someday"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "someday.day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "someday.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "someday.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "someday.hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "someday.weekday_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.insert(0,\"Day of week\",stocks.index.weekday_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.insert(1,\"Start of month\",stocks.index.is_month_start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks[stocks[\"Start of month\"]]\n",
    "#Gives stock value in every month start"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## .truncate() method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks = data.DataReader(name=company,data_source=\"yahoo\",start=start,end=end)\n",
    "stocks.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.truncate(before=\"2011-2-5\",after=\"2011-2-28\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## pd.DateOffset object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks = data.DataReader(name=\"GOOG\",data_source=\"yahoo\",start=dt.date(2000,1,1),end=dt.datetime.now())\n",
    "stocks.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.index + pd.DateOffset(days=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.index + pd.DateOffset(weeks=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.index - pd.DateOffset(weeks=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks.index - pd.DateOffset(years=1,month=3,days=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks = data.DataReader(name=\"GOOG\",data_source=\"yahoo\",start=dt.date(2000,1,1),end=dt.datetime.now())\n",
    "stocks.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-31', '2010-01-31', '2010-01-31', '2010-01-31',\n",
       "               '2010-01-31', '2010-01-31', '2010-01-31', '2010-01-31',\n",
       "               '2010-01-31', '2010-01-31',\n",
       "               ...\n",
       "               '2019-02-28', '2019-02-28', '2019-02-28', '2019-02-28',\n",
       "               '2019-02-28', '2019-02-28', '2019-02-28', '2019-02-28',\n",
       "               '2019-02-28', '2019-02-28'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2295, freq=None)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.index + MonthEnd()\n",
    "#Month end works because we already imported\n",
    "#from pandas.tseries.offsets import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-01', '2010-02-01', '2010-02-01', '2010-02-01',\n",
       "               '2010-02-01', '2010-02-01', '2010-02-01', '2010-02-01',\n",
       "               '2010-02-01', '2010-02-01',\n",
       "               ...\n",
       "               '2019-02-01', '2019-03-01', '2019-03-01', '2019-03-01',\n",
       "               '2019-03-01', '2019-03-01', '2019-03-01', '2019-03-01',\n",
       "               '2019-03-01', '2019-03-01'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2295, freq=None)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.index + MonthBegin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-29', '2010-01-29', '2010-01-29', '2010-01-29',\n",
       "               '2010-01-29', '2010-01-29', '2010-01-29', '2010-01-29',\n",
       "               '2010-01-29', '2010-01-29',\n",
       "               ...\n",
       "               '2019-02-28', '2019-02-28', '2019-02-28', '2019-02-28',\n",
       "               '2019-02-28', '2019-02-28', '2019-02-28', '2019-02-28',\n",
       "               '2019-02-28', '2019-02-28'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2295, freq=None)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.index + BMonthEnd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-03-31', '2010-03-31', '2010-03-31', '2010-03-31',\n",
       "               '2010-03-31', '2010-03-31', '2010-03-31', '2010-03-31',\n",
       "               '2010-03-31', '2010-03-31',\n",
       "               ...\n",
       "               '2019-03-31', '2019-03-31', '2019-03-31', '2019-03-31',\n",
       "               '2019-03-31', '2019-03-31', '2019-03-31', '2019-03-31',\n",
       "               '2019-03-31', '2019-03-31'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2295, freq=None)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.index + QuarterEnd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2009-09-30', '2009-12-31', '2009-12-31', '2009-12-31',\n",
       "               '2009-12-31', '2009-12-31', '2009-12-31', '2009-12-31',\n",
       "               '2009-12-31', '2009-12-31',\n",
       "               ...\n",
       "               '2018-12-31', '2018-12-31', '2018-12-31', '2018-12-31',\n",
       "               '2018-12-31', '2018-12-31', '2018-12-31', '2018-12-31',\n",
       "               '2018-12-31', '2018-12-31'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2295, freq=None)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.index - QuarterEnd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-12-31', '2010-12-31', '2010-12-31', '2010-12-31',\n",
       "               '2010-12-31', '2010-12-31', '2010-12-31', '2010-12-31',\n",
       "               '2010-12-31', '2010-12-31',\n",
       "               ...\n",
       "               '2019-12-31', '2019-12-31', '2019-12-31', '2019-12-31',\n",
       "               '2019-12-31', '2019-12-31', '2019-12-31', '2019-12-31',\n",
       "               '2019-12-31', '2019-12-31'],\n",
       "              dtype='datetime64[ns]', name='Date', length=2295, freq=None)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks.index + YearEnd()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The timeDelta object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "timeA = pd.Timestamp('2016-3-31')\n",
    "timeB = pd.Timestamp('2016-3-20')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('11 days 00:00:00')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "timeA - timeB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas._libs.tslibs.timedeltas.Timedelta"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(timeA - timeB)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas._libs.tslibs.timestamps.Timestamp"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(timeA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('-11 days +00:00:00')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "timeB - timeA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('38 days 05:05:00')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Timedelta( weeks=5,days = 3, minutes =5,hours = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('14 days 06:12:00')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Timedelta(\"14 days 6 hours 12 minutes\")\n",
    "# weeks dont work if given in string"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## timeDelta in dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "shipping = pd.read_csv('ecommerce.csv',index_col = \"ID\",parse_dates = [\"order_date\",\"delivery_date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>order_date</th>\n",
       "      <th>delivery_date</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1998-05-24</td>\n",
       "      <td>1999-02-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1992-04-22</td>\n",
       "      <td>1998-03-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1991-02-10</td>\n",
       "      <td>1992-08-26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_date delivery_date\n",
       "ID                         \n",
       "1  1998-05-24    1999-02-05\n",
       "2  1992-04-22    1998-03-06\n",
       "4  1991-02-10    1992-08-26"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shipping.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "shipping['delivery_time'] = shipping[\"delivery_date\"] - shipping['order_date']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>order_date</th>\n",
       "      <th>delivery_date</th>\n",
       "      <th>delivery_time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1998-05-24</td>\n",
       "      <td>1999-02-05</td>\n",
       "      <td>257 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1992-04-22</td>\n",
       "      <td>1998-03-06</td>\n",
       "      <td>2144 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1991-02-10</td>\n",
       "      <td>1992-08-26</td>\n",
       "      <td>563 days</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_date delivery_date delivery_time\n",
       "ID                                       \n",
       "1  1998-05-24    1999-02-05      257 days\n",
       "2  1992-04-22    1998-03-06     2144 days\n",
       "4  1991-02-10    1992-08-26      563 days"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shipping.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "shipping['twice_as_long'] = shipping['delivery_date'] + shipping['delivery_time']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>order_date</th>\n",
       "      <th>delivery_date</th>\n",
       "      <th>delivery_time</th>\n",
       "      <th>twice_as_long</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1998-05-24</td>\n",
       "      <td>1999-02-05</td>\n",
       "      <td>257 days</td>\n",
       "      <td>1999-10-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1992-04-22</td>\n",
       "      <td>1998-03-06</td>\n",
       "      <td>2144 days</td>\n",
       "      <td>2004-01-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1991-02-10</td>\n",
       "      <td>1992-08-26</td>\n",
       "      <td>563 days</td>\n",
       "      <td>1994-03-12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_date delivery_date delivery_time twice_as_long\n",
       "ID                                                     \n",
       "1  1998-05-24    1999-02-05      257 days    1999-10-20\n",
       "2  1992-04-22    1998-03-06     2144 days    2004-01-18\n",
       "4  1991-02-10    1992-08-26      563 days    1994-03-12"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shipping.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "order_date        datetime64[ns]\n",
       "delivery_date     datetime64[ns]\n",
       "delivery_time    timedelta64[ns]\n",
       "twice_as_long     datetime64[ns]\n",
       "dtype: object"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shipping.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = shipping['delivery_time'] > '365 days'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "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>order_date</th>\n",
       "      <th>delivery_date</th>\n",
       "      <th>delivery_time</th>\n",
       "      <th>twice_as_long</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1992-04-22</td>\n",
       "      <td>1998-03-06</td>\n",
       "      <td>2144 days</td>\n",
       "      <td>2004-01-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1991-02-10</td>\n",
       "      <td>1992-08-26</td>\n",
       "      <td>563 days</td>\n",
       "      <td>1994-03-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1992-07-21</td>\n",
       "      <td>1997-11-20</td>\n",
       "      <td>1948 days</td>\n",
       "      <td>2003-03-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1993-09-02</td>\n",
       "      <td>1998-06-10</td>\n",
       "      <td>1742 days</td>\n",
       "      <td>2003-03-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1990-01-25</td>\n",
       "      <td>1994-10-02</td>\n",
       "      <td>1711 days</td>\n",
       "      <td>1999-06-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1992-02-23</td>\n",
       "      <td>1998-12-30</td>\n",
       "      <td>2502 days</td>\n",
       "      <td>2005-11-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1996-07-12</td>\n",
       "      <td>1997-07-14</td>\n",
       "      <td>367 days</td>\n",
       "      <td>1998-07-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1995-06-18</td>\n",
       "      <td>1997-10-13</td>\n",
       "      <td>848 days</td>\n",
       "      <td>2000-02-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1992-10-17</td>\n",
       "      <td>1998-10-06</td>\n",
       "      <td>2180 days</td>\n",
       "      <td>2004-09-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1992-05-30</td>\n",
       "      <td>1999-08-15</td>\n",
       "      <td>2633 days</td>\n",
       "      <td>2006-10-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1996-04-11</td>\n",
       "      <td>1998-05-04</td>\n",
       "      <td>753 days</td>\n",
       "      <td>2000-05-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1990-01-20</td>\n",
       "      <td>1998-07-24</td>\n",
       "      <td>3107 days</td>\n",
       "      <td>2007-01-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1994-09-21</td>\n",
       "      <td>1996-10-12</td>\n",
       "      <td>752 days</td>\n",
       "      <td>1998-11-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1993-09-10</td>\n",
       "      <td>1996-04-28</td>\n",
       "      <td>961 days</td>\n",
       "      <td>1998-12-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1990-05-15</td>\n",
       "      <td>1994-02-14</td>\n",
       "      <td>1371 days</td>\n",
       "      <td>1997-11-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>1990-03-26</td>\n",
       "      <td>1993-01-25</td>\n",
       "      <td>1036 days</td>\n",
       "      <td>1995-11-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1992-02-06</td>\n",
       "      <td>1996-05-10</td>\n",
       "      <td>1555 days</td>\n",
       "      <td>2000-08-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>1991-05-03</td>\n",
       "      <td>1999-07-17</td>\n",
       "      <td>2997 days</td>\n",
       "      <td>2007-09-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>1994-09-02</td>\n",
       "      <td>1997-05-14</td>\n",
       "      <td>985 days</td>\n",
       "      <td>2000-01-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>1995-11-29</td>\n",
       "      <td>1998-06-23</td>\n",
       "      <td>937 days</td>\n",
       "      <td>2001-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>1996-08-07</td>\n",
       "      <td>1998-04-04</td>\n",
       "      <td>605 days</td>\n",
       "      <td>1999-11-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>1993-02-14</td>\n",
       "      <td>1995-08-06</td>\n",
       "      <td>903 days</td>\n",
       "      <td>1998-01-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>1990-12-22</td>\n",
       "      <td>1995-09-02</td>\n",
       "      <td>1715 days</td>\n",
       "      <td>2000-05-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>1990-11-25</td>\n",
       "      <td>1998-05-14</td>\n",
       "      <td>2727 days</td>\n",
       "      <td>2005-10-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>1992-09-08</td>\n",
       "      <td>1998-12-29</td>\n",
       "      <td>2303 days</td>\n",
       "      <td>2005-04-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>1990-05-04</td>\n",
       "      <td>1993-02-04</td>\n",
       "      <td>1007 days</td>\n",
       "      <td>1995-11-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>1994-02-16</td>\n",
       "      <td>1999-11-06</td>\n",
       "      <td>2089 days</td>\n",
       "      <td>2005-07-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>1990-11-25</td>\n",
       "      <td>1998-04-06</td>\n",
       "      <td>2689 days</td>\n",
       "      <td>2005-08-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>1991-10-01</td>\n",
       "      <td>1993-05-19</td>\n",
       "      <td>596 days</td>\n",
       "      <td>1995-01-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>1990-06-25</td>\n",
       "      <td>1996-12-18</td>\n",
       "      <td>2368 days</td>\n",
       "      <td>2003-06-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>907</th>\n",
       "      <td>1994-08-11</td>\n",
       "      <td>1998-09-28</td>\n",
       "      <td>1509 days</td>\n",
       "      <td>2002-11-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>908</th>\n",
       "      <td>1993-11-04</td>\n",
       "      <td>1997-02-26</td>\n",
       "      <td>1210 days</td>\n",
       "      <td>2000-06-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>909</th>\n",
       "      <td>1991-01-19</td>\n",
       "      <td>1998-08-22</td>\n",
       "      <td>2772 days</td>\n",
       "      <td>2006-03-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>916</th>\n",
       "      <td>1994-12-03</td>\n",
       "      <td>1997-03-26</td>\n",
       "      <td>844 days</td>\n",
       "      <td>1999-07-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>918</th>\n",
       "      <td>1994-12-29</td>\n",
       "      <td>1996-07-29</td>\n",
       "      <td>578 days</td>\n",
       "      <td>1998-02-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>919</th>\n",
       "      <td>1992-01-25</td>\n",
       "      <td>1993-06-01</td>\n",
       "      <td>493 days</td>\n",
       "      <td>1994-10-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>922</th>\n",
       "      <td>1996-07-06</td>\n",
       "      <td>1998-12-05</td>\n",
       "      <td>882 days</td>\n",
       "      <td>2001-05-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>924</th>\n",
       "      <td>1991-03-17</td>\n",
       "      <td>1996-05-13</td>\n",
       "      <td>1884 days</td>\n",
       "      <td>2001-07-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>926</th>\n",
       "      <td>1990-10-31</td>\n",
       "      <td>1994-04-12</td>\n",
       "      <td>1259 days</td>\n",
       "      <td>1997-09-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>935</th>\n",
       "      <td>1990-09-26</td>\n",
       "      <td>1998-03-07</td>\n",
       "      <td>2719 days</td>\n",
       "      <td>2005-08-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>938</th>\n",
       "      <td>1993-03-24</td>\n",
       "      <td>1995-07-15</td>\n",
       "      <td>843 days</td>\n",
       "      <td>1997-11-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>942</th>\n",
       "      <td>1992-04-14</td>\n",
       "      <td>1997-03-03</td>\n",
       "      <td>1784 days</td>\n",
       "      <td>2002-01-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>943</th>\n",
       "      <td>1991-01-30</td>\n",
       "      <td>1999-12-02</td>\n",
       "      <td>3228 days</td>\n",
       "      <td>2008-10-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945</th>\n",
       "      <td>1992-10-27</td>\n",
       "      <td>1994-11-03</td>\n",
       "      <td>737 days</td>\n",
       "      <td>1996-11-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
       "      <td>1991-07-02</td>\n",
       "      <td>1996-02-23</td>\n",
       "      <td>1697 days</td>\n",
       "      <td>2000-10-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>1991-06-18</td>\n",
       "      <td>1999-06-11</td>\n",
       "      <td>2915 days</td>\n",
       "      <td>2007-06-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>951</th>\n",
       "      <td>1991-10-02</td>\n",
       "      <td>1994-04-18</td>\n",
       "      <td>929 days</td>\n",
       "      <td>1996-11-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>953</th>\n",
       "      <td>1991-09-26</td>\n",
       "      <td>1994-05-08</td>\n",
       "      <td>955 days</td>\n",
       "      <td>1996-12-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>956</th>\n",
       "      <td>1995-08-23</td>\n",
       "      <td>1999-01-10</td>\n",
       "      <td>1236 days</td>\n",
       "      <td>2002-05-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>957</th>\n",
       "      <td>1994-10-01</td>\n",
       "      <td>1999-07-25</td>\n",
       "      <td>1758 days</td>\n",
       "      <td>2004-05-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>958</th>\n",
       "      <td>1990-04-26</td>\n",
       "      <td>1997-06-29</td>\n",
       "      <td>2621 days</td>\n",
       "      <td>2004-09-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>972</th>\n",
       "      <td>1990-02-07</td>\n",
       "      <td>1995-11-05</td>\n",
       "      <td>2097 days</td>\n",
       "      <td>2001-08-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>1997-01-31</td>\n",
       "      <td>1998-03-04</td>\n",
       "      <td>397 days</td>\n",
       "      <td>1999-04-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>1994-12-30</td>\n",
       "      <td>1997-07-29</td>\n",
       "      <td>942 days</td>\n",
       "      <td>2000-02-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>984</th>\n",
       "      <td>1991-07-25</td>\n",
       "      <td>1999-02-09</td>\n",
       "      <td>2756 days</td>\n",
       "      <td>2006-08-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>1990-12-10</td>\n",
       "      <td>1992-12-16</td>\n",
       "      <td>737 days</td>\n",
       "      <td>1994-12-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990</th>\n",
       "      <td>1991-06-24</td>\n",
       "      <td>1996-02-02</td>\n",
       "      <td>1684 days</td>\n",
       "      <td>2000-09-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>1991-09-09</td>\n",
       "      <td>1998-03-30</td>\n",
       "      <td>2394 days</td>\n",
       "      <td>2004-10-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>1990-11-16</td>\n",
       "      <td>1998-04-27</td>\n",
       "      <td>2719 days</td>\n",
       "      <td>2005-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>1990-01-04</td>\n",
       "      <td>1991-10-03</td>\n",
       "      <td>637 days</td>\n",
       "      <td>1993-07-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>394 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    order_date delivery_date delivery_time twice_as_long\n",
       "ID                                                      \n",
       "2   1992-04-22    1998-03-06     2144 days    2004-01-18\n",
       "4   1991-02-10    1992-08-26      563 days    1994-03-12\n",
       "5   1992-07-21    1997-11-20     1948 days    2003-03-22\n",
       "7   1993-09-02    1998-06-10     1742 days    2003-03-18\n",
       "9   1990-01-25    1994-10-02     1711 days    1999-06-09\n",
       "10  1992-02-23    1998-12-30     2502 days    2005-11-05\n",
       "11  1996-07-12    1997-07-14      367 days    1998-07-16\n",
       "18  1995-06-18    1997-10-13      848 days    2000-02-08\n",
       "20  1992-10-17    1998-10-06     2180 days    2004-09-24\n",
       "23  1992-05-30    1999-08-15     2633 days    2006-10-30\n",
       "26  1996-04-11    1998-05-04      753 days    2000-05-26\n",
       "32  1990-01-20    1998-07-24     3107 days    2007-01-25\n",
       "33  1994-09-21    1996-10-12      752 days    1998-11-03\n",
       "35  1993-09-10    1996-04-28      961 days    1998-12-15\n",
       "36  1990-05-15    1994-02-14     1371 days    1997-11-16\n",
       "39  1990-03-26    1993-01-25     1036 days    1995-11-27\n",
       "41  1992-02-06    1996-05-10     1555 days    2000-08-12\n",
       "50  1991-05-03    1999-07-17     2997 days    2007-09-30\n",
       "52  1994-09-02    1997-05-14      985 days    2000-01-24\n",
       "53  1995-11-29    1998-06-23      937 days    2001-01-15\n",
       "54  1996-08-07    1998-04-04      605 days    1999-11-30\n",
       "60  1993-02-14    1995-08-06      903 days    1998-01-25\n",
       "63  1990-12-22    1995-09-02     1715 days    2000-05-13\n",
       "64  1990-11-25    1998-05-14     2727 days    2005-10-31\n",
       "66  1992-09-08    1998-12-29     2303 days    2005-04-19\n",
       "67  1990-05-04    1993-02-04     1007 days    1995-11-08\n",
       "70  1994-02-16    1999-11-06     2089 days    2005-07-26\n",
       "71  1990-11-25    1998-04-06     2689 days    2005-08-16\n",
       "73  1991-10-01    1993-05-19      596 days    1995-01-05\n",
       "75  1990-06-25    1996-12-18     2368 days    2003-06-13\n",
       "..         ...           ...           ...           ...\n",
       "907 1994-08-11    1998-09-28     1509 days    2002-11-15\n",
       "908 1993-11-04    1997-02-26     1210 days    2000-06-20\n",
       "909 1991-01-19    1998-08-22     2772 days    2006-03-25\n",
       "916 1994-12-03    1997-03-26      844 days    1999-07-18\n",
       "918 1994-12-29    1996-07-29      578 days    1998-02-27\n",
       "919 1992-01-25    1993-06-01      493 days    1994-10-07\n",
       "922 1996-07-06    1998-12-05      882 days    2001-05-05\n",
       "924 1991-03-17    1996-05-13     1884 days    2001-07-10\n",
       "926 1990-10-31    1994-04-12     1259 days    1997-09-22\n",
       "935 1990-09-26    1998-03-07     2719 days    2005-08-16\n",
       "938 1993-03-24    1995-07-15      843 days    1997-11-04\n",
       "942 1992-04-14    1997-03-03     1784 days    2002-01-20\n",
       "943 1991-01-30    1999-12-02     3228 days    2008-10-03\n",
       "945 1992-10-27    1994-11-03      737 days    1996-11-09\n",
       "946 1991-07-02    1996-02-23     1697 days    2000-10-16\n",
       "947 1991-06-18    1999-06-11     2915 days    2007-06-04\n",
       "951 1991-10-02    1994-04-18      929 days    1996-11-02\n",
       "953 1991-09-26    1994-05-08      955 days    1996-12-18\n",
       "956 1995-08-23    1999-01-10     1236 days    2002-05-30\n",
       "957 1994-10-01    1999-07-25     1758 days    2004-05-17\n",
       "958 1990-04-26    1997-06-29     2621 days    2004-09-01\n",
       "972 1990-02-07    1995-11-05     2097 days    2001-08-02\n",
       "981 1997-01-31    1998-03-04      397 days    1999-04-05\n",
       "983 1994-12-30    1997-07-29      942 days    2000-02-26\n",
       "984 1991-07-25    1999-02-09     2756 days    2006-08-27\n",
       "986 1990-12-10    1992-12-16      737 days    1994-12-23\n",
       "990 1991-06-24    1996-02-02     1684 days    2000-09-12\n",
       "991 1991-09-09    1998-03-30     2394 days    2004-10-18\n",
       "993 1990-11-16    1998-04-27     2719 days    2005-10-06\n",
       "997 1990-01-04    1991-10-03      637 days    1993-07-01\n",
       "\n",
       "[394 rows x 4 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shipping[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('3583 days 00:00:00')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shipping['delivery_time'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('8 days 00:00:00')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shipping['delivery_time'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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