Algorithmic Trading and Stocks Essential Training.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2020-05-11    2930.32\n",
       "2020-05-12    2870.12\n",
       "2020-05-13    2820.00\n",
       "2020-05-14    2852.50\n",
       "2020-05-15    2863.70\n",
       "dtype: float64"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# fredapi S&P500 example\n",
    "from fredapi import Fred\n",
    "fred = Fred(api_key='88db5f8c39fa70709e3ac1602b48882d')\n",
    "data = fred.get_series('SP500')\n",
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2518.000000\n",
       "mean     2030.057220\n",
       "std       599.043807\n",
       "min      1022.580000\n",
       "25%      1432.630000\n",
       "50%      2038.615000\n",
       "75%      2548.537500\n",
       "max      3386.150000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 10y S&P500 index stats\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1112167f0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PFtHhIWQ+MIdLT+4N4OzeWVEnAPzts91Abd/7H2akuh3/1bSB9a5dUu4+r8+/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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11084a320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 10y S&P500 plot\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "data.plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "      <th>frequency_short</th>\n",
       "      <th>id</th>\n",
       "      <th>last_updated</th>\n",
       "      <th>notes</th>\n",
       "      <th>observation_end</th>\n",
       "      <th>observation_start</th>\n",
       "      <th>popularity</th>\n",
       "      <th>realtime_end</th>\n",
       "      <th>realtime_start</th>\n",
       "      <th>seasonal_adjustment</th>\n",
       "      <th>seasonal_adjustment_short</th>\n",
       "      <th>title</th>\n",
       "      <th>units</th>\n",
       "      <th>units_short</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>series id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GASREGW</th>\n",
       "      <td>Weekly, Ending Monday</td>\n",
       "      <td>W</td>\n",
       "      <td>GASREGW</td>\n",
       "      <td>2020-05-11 23:11:02</td>\n",
       "      <td>Weighted average based on sampling of approxim...</td>\n",
       "      <td>2020-05-11</td>\n",
       "      <td>1990-08-20</td>\n",
       "      <td>54</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>US Regular All Formulations Gas Price</td>\n",
       "      <td>Dollars per Gallon</td>\n",
       "      <td>$ per Gallon</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       frequency frequency_short       id        last_updated  \\\n",
       "series id                                                                       \n",
       "GASREGW    Weekly, Ending Monday               W  GASREGW 2020-05-11 23:11:02   \n",
       "\n",
       "                                                       notes observation_end  \\\n",
       "series id                                                                      \n",
       "GASREGW    Weighted average based on sampling of approxim...      2020-05-11   \n",
       "\n",
       "          observation_start popularity realtime_end realtime_start  \\\n",
       "series id                                                            \n",
       "GASREGW          1990-08-20         54   2020-05-18     2020-05-18   \n",
       "\n",
       "               seasonal_adjustment seasonal_adjustment_short  \\\n",
       "series id                                                      \n",
       "GASREGW    Not Seasonally Adjusted                       NSA   \n",
       "\n",
       "                                           title               units  \\\n",
       "series id                                                              \n",
       "GASREGW    US Regular All Formulations Gas Price  Dollars per Gallon   \n",
       "\n",
       "            units_short  \n",
       "series id                \n",
       "GASREGW    $ per Gallon  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# search for GASREGW indicator\n",
    "fred.search('GASREGW')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2000-01-03    1.272\n",
       "2000-01-10    1.264\n",
       "2000-01-17    1.277\n",
       "2000-01-24    1.315\n",
       "2000-01-31    1.316\n",
       "2000-02-07    1.325\n",
       "2000-02-14    1.356\n",
       "2000-02-21    1.406\n",
       "2000-02-28    1.421\n",
       "2000-03-06    1.501\n",
       "2000-03-13    1.527\n",
       "2000-03-20    1.529\n",
       "2000-03-27    1.508\n",
       "2000-04-03    1.503\n",
       "2000-04-10    1.475\n",
       "2000-04-17    1.444\n",
       "2000-04-24    1.437\n",
       "2000-05-01    1.420\n",
       "2000-05-08    1.455\n",
       "2000-05-15    1.492\n",
       "2000-05-22    1.527\n",
       "2000-05-29    1.540\n",
       "2000-06-05    1.563\n",
       "2000-06-12    1.631\n",
       "2000-06-19    1.681\n",
       "2000-06-26    1.658\n",
       "2000-07-03    1.625\n",
       "2000-07-10    1.593\n",
       "2000-07-17    1.546\n",
       "2000-07-24    1.520\n",
       "              ...  \n",
       "2019-06-10    2.732\n",
       "2019-06-17    2.670\n",
       "2019-06-24    2.654\n",
       "2019-07-01    2.713\n",
       "2019-07-08    2.743\n",
       "2019-07-15    2.779\n",
       "2019-07-22    2.750\n",
       "2019-07-29    2.715\n",
       "2019-08-05    2.688\n",
       "2019-08-12    2.624\n",
       "2019-08-19    2.598\n",
       "2019-08-26    2.574\n",
       "2019-09-02    2.563\n",
       "2019-09-09    2.550\n",
       "2019-09-16    2.552\n",
       "2019-09-23    2.654\n",
       "2019-09-30    2.642\n",
       "2019-10-07    2.645\n",
       "2019-10-14    2.629\n",
       "2019-10-21    2.638\n",
       "2019-10-28    2.596\n",
       "2019-11-04    2.605\n",
       "2019-11-11    2.615\n",
       "2019-11-18    2.592\n",
       "2019-11-25    2.579\n",
       "2019-12-02    2.575\n",
       "2019-12-09    2.561\n",
       "2019-12-16    2.536\n",
       "2019-12-23    2.532\n",
       "2019-12-30    2.571\n",
       "Length: 1044, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get GASREGW series\n",
    "start_date = '2000-01-01'\n",
    "end_date = '2020-01-01'\n",
    "fred.get_series('GASREGW', observation_start=start_date, observation_end=end_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# get all indicators\n",
    "GASREGW = fred.get_series('GASREGW', observation_start=start_date, observation_end=end_date)\n",
    "DBAA = fred.get_series('DBAA', observation_start=start_date, observation_end=end_date)\n",
    "ICSA = fred.get_series('ICSA', observation_start=start_date, observation_end=end_date)\n",
    "DCOILWTICO = fred.get_series('DCOILWTICO', observation_start=start_date, observation_end=end_date)\n",
    "ALTSALES = fred.get_series('ALTSALES', observation_start=start_date, observation_end=end_date)\n",
    "INDPRO = fred.get_series('INDPRO', observation_start=start_date, observation_end=end_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GDP    16569.591\n",
       "Name: 2013-01-01 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# alternative library\n",
    "import pandas_datareader.data as web\n",
    "\n",
    "start = '2000-01-01'\n",
    "end = '2020-01-01'\n",
    "gdp = web.DataReader('GDP', 'fred', start, end)\n",
    "gdp.loc['2013-01-01']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GASREGW</th>\n",
       "      <th>DBAA</th>\n",
       "      <th>ICSA</th>\n",
       "      <th>DCOILWTICO</th>\n",
       "      <th>ALTSALES</th>\n",
       "      <th>INDPRO</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>2000-01-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>286000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.114</td>\n",
       "      <td>94.1758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-03</th>\n",
       "      <td>1.272</td>\n",
       "      <td>8.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-05</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.79</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-07</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.79</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>298000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-10</th>\n",
       "      <td>1.264</td>\n",
       "      <td>8.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-11</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.69</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-13</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-14</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-15</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>289000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-17</th>\n",
       "      <td>1.277</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-18</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.47</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.98</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-19</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-21</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>284000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-24</th>\n",
       "      <td>1.315</td>\n",
       "      <td>8.36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>285000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-31</th>\n",
       "      <td>1.316</td>\n",
       "      <td>8.36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.28</td>\n",
       "      <td>18.879</td>\n",
       "      <td>94.4557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-02</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.52</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>2019-11-29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>206000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.647</td>\n",
       "      <td>109.6357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-02</th>\n",
       "      <td>2.575</td>\n",
       "      <td>3.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>56.15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-05</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.89</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.91</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-07</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>237000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-09</th>\n",
       "      <td>2.561</td>\n",
       "      <td>3.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-11</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.92</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-13</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-14</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>229000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-16</th>\n",
       "      <td>2.536</td>\n",
       "      <td>3.89</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-17</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-18</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-19</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-21</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>218000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23</th>\n",
       "      <td>2.532</td>\n",
       "      <td>3.89</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60.51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61.17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61.76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>220000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-30</th>\n",
       "      <td>2.571</td>\n",
       "      <td>3.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61.66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.925</td>\n",
       "      <td>109.1337</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6297 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            GASREGW  DBAA      ICSA  DCOILWTICO  ALTSALES    INDPRO\n",
       "DATE                                                               \n",
       "2000-01-01      NaN   NaN  286000.0         NaN    18.114   94.1758\n",
       "2000-01-03    1.272  8.27       NaN         NaN       NaN       NaN\n",
       "2000-01-04      NaN  8.21       NaN       25.56       NaN       NaN\n",
       "2000-01-05      NaN  8.29       NaN       24.65       NaN       NaN\n",
       "2000-01-06      NaN  8.24       NaN       24.79       NaN       NaN\n",
       "2000-01-07      NaN  8.22       NaN       24.79       NaN       NaN\n",
       "2000-01-08      NaN   NaN  298000.0         NaN       NaN       NaN\n",
       "2000-01-10    1.264  8.27       NaN       24.71       NaN       NaN\n",
       "2000-01-11      NaN  8.36       NaN       25.69       NaN       NaN\n",
       "2000-01-12      NaN  8.40       NaN       26.30       NaN       NaN\n",
       "2000-01-13      NaN  8.38       NaN       26.63       NaN       NaN\n",
       "2000-01-14      NaN  8.42       NaN       28.01       NaN       NaN\n",
       "2000-01-15      NaN   NaN  289000.0         NaN       NaN       NaN\n",
       "2000-01-17    1.277   NaN       NaN         NaN       NaN       NaN\n",
       "2000-01-18      NaN  8.47       NaN       28.98       NaN       NaN\n",
       "2000-01-19      NaN  8.43       NaN       29.11       NaN       NaN\n",
       "2000-01-20      NaN  8.45       NaN       29.67       NaN       NaN\n",
       "2000-01-21      NaN  8.42       NaN       29.71       NaN       NaN\n",
       "2000-01-22      NaN   NaN  284000.0         NaN       NaN       NaN\n",
       "2000-01-24    1.315  8.36       NaN       29.25       NaN       NaN\n",
       "2000-01-25      NaN  8.33       NaN       30.28       NaN       NaN\n",
       "2000-01-26      NaN  8.28       NaN       27.66       NaN       NaN\n",
       "2000-01-27      NaN  8.23       NaN       27.22       NaN       NaN\n",
       "2000-01-28      NaN  8.26       NaN       27.27       NaN       NaN\n",
       "2000-01-29      NaN   NaN  285000.0         NaN       NaN       NaN\n",
       "2000-01-31    1.316  8.36       NaN       27.65       NaN       NaN\n",
       "2000-02-01      NaN  8.27       NaN       28.28    18.879   94.4557\n",
       "2000-02-02      NaN  8.22       NaN       27.52       NaN       NaN\n",
       "2000-02-03      NaN  8.13       NaN       28.26       NaN       NaN\n",
       "2000-02-04      NaN  8.13       NaN       28.67       NaN       NaN\n",
       "...             ...   ...       ...         ...       ...       ...\n",
       "2019-11-29      NaN  3.86       NaN       58.12       NaN       NaN\n",
       "2019-11-30      NaN   NaN  206000.0         NaN       NaN       NaN\n",
       "2019-12-01      NaN   NaN       NaN         NaN    16.647  109.6357\n",
       "2019-12-02    2.575  3.94       NaN       55.97       NaN       NaN\n",
       "2019-12-03      NaN  3.83       NaN       56.15       NaN       NaN\n",
       "2019-12-04      NaN  3.88       NaN       58.46       NaN       NaN\n",
       "2019-12-05      NaN  3.89       NaN       58.42       NaN       NaN\n",
       "2019-12-06      NaN  3.91       NaN       59.20       NaN       NaN\n",
       "2019-12-07      NaN   NaN  237000.0         NaN       NaN       NaN\n",
       "2019-12-09    2.561  3.88       NaN       58.99       NaN       NaN\n",
       "2019-12-10      NaN  3.86       NaN       59.22       NaN       NaN\n",
       "2019-12-11      NaN  3.83       NaN       58.74       NaN       NaN\n",
       "2019-12-12      NaN  3.92       NaN       59.18       NaN       NaN\n",
       "2019-12-13      NaN  3.84       NaN       60.11       NaN       NaN\n",
       "2019-12-14      NaN   NaN  229000.0         NaN       NaN       NaN\n",
       "2019-12-16    2.536  3.89       NaN       60.21       NaN       NaN\n",
       "2019-12-17      NaN  3.88       NaN       60.88       NaN       NaN\n",
       "2019-12-18      NaN  3.90       NaN       60.93       NaN       NaN\n",
       "2019-12-19      NaN  3.88       NaN       61.30       NaN       NaN\n",
       "2019-12-20      NaN  3.88       NaN       60.43       NaN       NaN\n",
       "2019-12-21      NaN   NaN  218000.0         NaN       NaN       NaN\n",
       "2019-12-23    2.532  3.89       NaN       60.51       NaN       NaN\n",
       "2019-12-24      NaN  3.87       NaN       61.17       NaN       NaN\n",
       "2019-12-25      NaN   NaN       NaN         NaN       NaN       NaN\n",
       "2019-12-26      NaN  3.87       NaN       61.72       NaN       NaN\n",
       "2019-12-27      NaN  3.84       NaN       61.76       NaN       NaN\n",
       "2019-12-28      NaN   NaN  220000.0         NaN       NaN       NaN\n",
       "2019-12-30    2.571  3.87       NaN       61.66       NaN       NaN\n",
       "2019-12-31      NaN  3.90       NaN       61.14       NaN       NaN\n",
       "2020-01-01      NaN   NaN       NaN         NaN    16.925  109.1337\n",
       "\n",
       "[6297 rows x 6 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get all indicators in a single dataframe\n",
    "indicators = ['GASREGW', 'DBAA', 'ICSA', 'DCOILWTICO', 'ALTSALES', 'INDPRO']\n",
    "web.DataReader(indicators, 'fred', start, end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "      <th>frequency_short</th>\n",
       "      <th>id</th>\n",
       "      <th>last_updated</th>\n",
       "      <th>notes</th>\n",
       "      <th>observation_end</th>\n",
       "      <th>observation_start</th>\n",
       "      <th>popularity</th>\n",
       "      <th>realtime_end</th>\n",
       "      <th>realtime_start</th>\n",
       "      <th>seasonal_adjustment</th>\n",
       "      <th>seasonal_adjustment_short</th>\n",
       "      <th>title</th>\n",
       "      <th>units</th>\n",
       "      <th>units_short</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>series id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SP500</th>\n",
       "      <td>Daily, Close</td>\n",
       "      <td>D</td>\n",
       "      <td>SP500</td>\n",
       "      <td>2020-05-16 00:10:58</td>\n",
       "      <td>The observations for the S&amp;P 500 represent the...</td>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>2010-05-17</td>\n",
       "      <td>88</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P 500</td>\n",
       "      <td>Index</td>\n",
       "      <td>Index</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VXVCLS</th>\n",
       "      <td>Daily, Close</td>\n",
       "      <td>D</td>\n",
       "      <td>VXVCLS</td>\n",
       "      <td>2020-05-18 13:36:05</td>\n",
       "      <td>Copyright, 2016, Chicago Board Options Exchang...</td>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>2007-12-04</td>\n",
       "      <td>57</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>CBOE S&amp;P 500 3-Month Volatility Index</td>\n",
       "      <td>Index</td>\n",
       "      <td>Index</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VXOCLS</th>\n",
       "      <td>Daily, Close</td>\n",
       "      <td>D</td>\n",
       "      <td>VXOCLS</td>\n",
       "      <td>2020-05-18 13:36:07</td>\n",
       "      <td>Copyright, 2016, Chicago Board Options Exchang...</td>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>1986-01-02</td>\n",
       "      <td>46</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>CBOE S&amp;P 100 Volatility Index: VXO</td>\n",
       "      <td>Index</td>\n",
       "      <td>Index</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CSUSHPINSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>CSUSHPINSA</td>\n",
       "      <td>2020-04-28 13:31:01</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>88</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller U.S. National Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CSUSHPISA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>CSUSHPISA</td>\n",
       "      <td>2020-04-28 13:31:12</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>77</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Seasonally Adjusted</td>\n",
       "      <td>SA</td>\n",
       "      <td>S&amp;P/Case-Shiller U.S. National Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPCS20RSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>SPCS20RSA</td>\n",
       "      <td>2020-04-28 13:31:05</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>2000-01-01</td>\n",
       "      <td>83</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Seasonally Adjusted</td>\n",
       "      <td>SA</td>\n",
       "      <td>S&amp;P/Case-Shiller 20-City Composite Home Price ...</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAMLH0A0HYM2</th>\n",
       "      <td>Daily, Close</td>\n",
       "      <td>D</td>\n",
       "      <td>BAMLH0A0HYM2</td>\n",
       "      <td>2020-05-18 12:46:02</td>\n",
       "      <td>The ICE BofA Option-Adjusted Spreads (OASs) ar...</td>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>1996-12-31</td>\n",
       "      <td>100</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>ICE BofA US High Yield Index Option-Adjusted S...</td>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPCS20RNSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>SPCS20RNSA</td>\n",
       "      <td>2020-04-28 13:31:37</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>2000-01-01</td>\n",
       "      <td>36</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller 20-City Composite Home Price ...</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BKTPAAA641N</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>BKTPAAA641N</td>\n",
       "      <td>2020-02-21 21:43:03</td>\n",
       "      <td>Transaction Types Institutions have been resol...</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>1934-01-01</td>\n",
       "      <td>2</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Failures and Assistance Transactions of all In...</td>\n",
       "      <td>Number of Institutions</td>\n",
       "      <td>Number of Institutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DJIA</th>\n",
       "      <td>Daily</td>\n",
       "      <td>D</td>\n",
       "      <td>DJIA</td>\n",
       "      <td>2020-05-16 00:01:02</td>\n",
       "      <td>The observations for the Dow Jones Industrial ...</td>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>2010-05-17</td>\n",
       "      <td>80</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Dow Jones Industrial Average</td>\n",
       "      <td>Index</td>\n",
       "      <td>Index</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFXRSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>SFXRSA</td>\n",
       "      <td>2020-04-28 13:32:01</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>71</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Seasonally Adjusted</td>\n",
       "      <td>SA</td>\n",
       "      <td>S&amp;P/Case-Shiller CA-San Francisco Home Price I...</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MEHOINUSA672N</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>MEHOINUSA672N</td>\n",
       "      <td>2019-09-10 19:32:02</td>\n",
       "      <td>Household data are collected as of March.  As ...</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>1984-01-01</td>\n",
       "      <td>87</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Real Median Household Income in the United States</td>\n",
       "      <td>2018 CPI-U-RS Adjusted Dollars</td>\n",
       "      <td>2018 CPI-U-RS Adjusted $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LXXRSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>LXXRSA</td>\n",
       "      <td>2020-04-28 13:32:02</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>69</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Seasonally Adjusted</td>\n",
       "      <td>SA</td>\n",
       "      <td>S&amp;P/Case-Shiller CA-Los Angeles Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFXRNSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>SFXRNSA</td>\n",
       "      <td>2020-04-28 13:32:11</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>22</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller CA-San Francisco Home Price I...</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAMLH0A0HYM2EY</th>\n",
       "      <td>Daily, Close</td>\n",
       "      <td>D</td>\n",
       "      <td>BAMLH0A0HYM2EY</td>\n",
       "      <td>2020-05-18 12:43:01</td>\n",
       "      <td>This data represents the effective yield of th...</td>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>1996-12-31</td>\n",
       "      <td>84</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>ICE BofA US High Yield Index Effective Yield</td>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LXXRNSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>LXXRNSA</td>\n",
       "      <td>2020-04-28 13:32:11</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller CA-Los Angeles Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NYXRSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>NYXRSA</td>\n",
       "      <td>2020-04-28 13:31:13</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>66</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Seasonally Adjusted</td>\n",
       "      <td>SA</td>\n",
       "      <td>S&amp;P/Case-Shiller NY-New York Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAMLC0A0CM</th>\n",
       "      <td>Daily, Close</td>\n",
       "      <td>D</td>\n",
       "      <td>BAMLC0A0CM</td>\n",
       "      <td>2020-05-18 12:46:25</td>\n",
       "      <td>The ICE BofA Option-Adjusted Spreads (OASs) ar...</td>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>1996-12-31</td>\n",
       "      <td>82</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>ICE BofA US Corporate Index Option-Adjusted Sp...</td>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEXRNSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>SEXRNSA</td>\n",
       "      <td>2020-04-28 13:31:16</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>63</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller WA-Seattle Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NYXRNSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>NYXRNSA</td>\n",
       "      <td>2020-04-28 13:32:11</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller NY-New York Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEXRSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>SEXRSA</td>\n",
       "      <td>2020-04-28 13:31:34</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>37</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Seasonally Adjusted</td>\n",
       "      <td>SA</td>\n",
       "      <td>S&amp;P/Case-Shiller WA-Seattle Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DDDM01USA156NWDB</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>DDDM01USA156NWDB</td>\n",
       "      <td>2019-10-21 19:50:02</td>\n",
       "      <td>Total value of all listed shares in a stock ma...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1996-01-01</td>\n",
       "      <td>78</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Stock Market Capitalization to GDP for United ...</td>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STLFSI</th>\n",
       "      <td>Weekly, Ending Friday</td>\n",
       "      <td>W</td>\n",
       "      <td>STLFSI</td>\n",
       "      <td>2020-03-19 14:00:02</td>\n",
       "      <td>The methodology for the St. Louis Fed's Financ...</td>\n",
       "      <td>2020-03-13</td>\n",
       "      <td>1993-12-31</td>\n",
       "      <td>77</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>St. Louis Fed Financial Stress Index (DISCONTI...</td>\n",
       "      <td>Index</td>\n",
       "      <td>Index</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOXRSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>BOXRSA</td>\n",
       "      <td>2020-04-28 13:31:20</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>60</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Seasonally Adjusted</td>\n",
       "      <td>SA</td>\n",
       "      <td>S&amp;P/Case-Shiller MA-Boston Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHXRSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>CHXRSA</td>\n",
       "      <td>2020-04-28 13:32:05</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>60</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Seasonally Adjusted</td>\n",
       "      <td>SA</td>\n",
       "      <td>S&amp;P/Case-Shiller IL-Chicago Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SDXRSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>SDXRSA</td>\n",
       "      <td>2020-04-28 13:31:17</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>59</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Seasonally Adjusted</td>\n",
       "      <td>SA</td>\n",
       "      <td>S&amp;P/Case-Shiller CA-San Diego Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOXRNSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>BOXRNSA</td>\n",
       "      <td>2020-04-28 13:31:50</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>19</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller MA-Boston Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DAXRNSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>DAXRNSA</td>\n",
       "      <td>2020-04-28 13:31:22</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>2000-01-01</td>\n",
       "      <td>55</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller TX-Dallas Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHXRNSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>CHXRNSA</td>\n",
       "      <td>2020-04-28 13:31:47</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>16</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller IL-Chicago Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SDXRNSA</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>SDXRNSA</td>\n",
       "      <td>2020-04-28 13:31:49</td>\n",
       "      <td>For more information regarding the index, plea...</td>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>1987-01-01</td>\n",
       "      <td>15</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>S&amp;P/Case-Shiller CA-San Diego Home Price Index</td>\n",
       "      <td>Index Jan 2000=100</td>\n",
       "      <td>Index Jan 2000 = 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CGDPESITA666NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>CGDPESITA666NRUG</td>\n",
       "      <td>2019-06-11 18:17:02</td>\n",
       "      <td>Source ID: cgdpe  When using these data in you...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1950-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Expenditure-side Real GDP at Current Purchasin...</td>\n",
       "      <td>Millions of 2011 U.S. Dollars</td>\n",
       "      <td>Mil. of 2011 U.S. $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PLCCPPCNA670NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>PLCCPPCNA670NRUG</td>\n",
       "      <td>2019-06-11 18:12:38</td>\n",
       "      <td>Source ID: pl_c  When using these data in your...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1952-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Price Level of Household Consumption for China</td>\n",
       "      <td>Price Level of USA Output-side GDP in 2011=1</td>\n",
       "      <td>Price Level of USA Output-side GDP in 2011=1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGDPNAUYA666NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>RGDPNAUYA666NRUG</td>\n",
       "      <td>2019-06-11 18:11:01</td>\n",
       "      <td>Source ID: rgdpna  When using these data in yo...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1950-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Real GDP at Constant National Prices for Uruguay</td>\n",
       "      <td>Millions of 2011 U.S. Dollars</td>\n",
       "      <td>Mil. of 2011 U.S. $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CTFPPPNLA669NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>CTFPPPNLA669NRUG</td>\n",
       "      <td>2019-06-11 20:33:09</td>\n",
       "      <td>Source ID: ctfp  When using these data in your...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1954-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Total Factor Productivity Level at Current Pur...</td>\n",
       "      <td>Index USA = 1</td>\n",
       "      <td>Index USA = 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RKNANPECA666NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>RKNANPECA666NRUG</td>\n",
       "      <td>2019-06-10 21:26:04</td>\n",
       "      <td>Source ID: rkna  When using these data in your...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1950-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Capital Stock at Constant National Prices for ...</td>\n",
       "      <td>Millions of 2011 U.S. Dollars</td>\n",
       "      <td>Mil. of 2011 U.S. $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EMVTRADEPOLEMV</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>EMVTRADEPOLEMV</td>\n",
       "      <td>2020-05-04 15:32:05</td>\n",
       "      <td>The Equity Market Volatility tracker moves wit...</td>\n",
       "      <td>2020-04-01</td>\n",
       "      <td>1985-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Equity Market Volatility Tracker: Trade Policy</td>\n",
       "      <td>Index</td>\n",
       "      <td>Index</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XRNCUSEGA618NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>XRNCUSEGA618NRUG</td>\n",
       "      <td>2019-06-11 18:12:59</td>\n",
       "      <td>Source ID: xr  When using these data in your r...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1950-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Exchange Rate (market+estimated) for Egypt</td>\n",
       "      <td>National Currency Units per US Dollar</td>\n",
       "      <td>National Currency Units per US $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CTFPPPFRA669NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>CTFPPPFRA669NRUG</td>\n",
       "      <td>2019-06-11 20:33:07</td>\n",
       "      <td>Source ID: ctfp  When using these data in your...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1954-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Total Factor Productivity Level at Current Pur...</td>\n",
       "      <td>Index USA = 1</td>\n",
       "      <td>Index USA = 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XRNCUSZWA618NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>XRNCUSZWA618NRUG</td>\n",
       "      <td>2019-06-11 18:12:35</td>\n",
       "      <td>Source ID: xr  When using these data in your r...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1954-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Exchange Rate (market+estimated) for Zimbabwe</td>\n",
       "      <td>National Currency Units per US Dollar</td>\n",
       "      <td>National Currency Units per US $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GCT1501CA</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>GCT1501CA</td>\n",
       "      <td>2019-10-21 16:23:03</td>\n",
       "      <td>Estimate of educational attainment for populat...</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>2006-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>High School Graduate or Higher for California</td>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M0415BUS000NYM267NNBR</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>M0415BUS000NYM267NNBR</td>\n",
       "      <td>2012-08-16 20:16:06</td>\n",
       "      <td>Series Has Been Subdivided Into Two Variables:...</td>\n",
       "      <td>1955-07-01</td>\n",
       "      <td>1911-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Wholesale Price of Copper, Electrolyte for New...</td>\n",
       "      <td>Cents per Pound</td>\n",
       "      <td>Cents Per Pound</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGDPNAAMA666NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>RGDPNAAMA666NRUG</td>\n",
       "      <td>2019-06-11 18:12:37</td>\n",
       "      <td>Source ID: rgdpna  When using these data in yo...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Real GDP at Constant National Prices for Armenia</td>\n",
       "      <td>Millions of 2011 U.S. Dollars</td>\n",
       "      <td>Mil. of 2011 U.S. $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q5APBM770A</th>\n",
       "      <td>Quarterly, End of Quarter</td>\n",
       "      <td>Q</td>\n",
       "      <td>Q5APBM770A</td>\n",
       "      <td>2020-03-01 19:01:17</td>\n",
       "      <td>Credit is provided by domestic banks, all othe...</td>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>1997-07-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Credit to Private Non-Financial Sector by Bank...</td>\n",
       "      <td>Percentage of GDP</td>\n",
       "      <td>Percentage of GDP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M0553BM576NNBR</th>\n",
       "      <td>Monthly, End of Month</td>\n",
       "      <td>M</td>\n",
       "      <td>M0553BM576NNBR</td>\n",
       "      <td>2012-08-17 15:47:54</td>\n",
       "      <td>Series Is Presented Here As Two Variables--(1)...</td>\n",
       "      <td>1956-02-01</td>\n",
       "      <td>1938-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Crude Rubber Stocks, U.S.-- Natural</td>\n",
       "      <td>Thousands of Long Tons</td>\n",
       "      <td>Thous. Of Long Tons</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MEHOINUSAZA646N</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>MEHOINUSAZA646N</td>\n",
       "      <td>2019-09-10 19:32:09</td>\n",
       "      <td>Household data are collected as of March.  As ...</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>1984-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Median Household Income in Arizona</td>\n",
       "      <td>Current Dollars</td>\n",
       "      <td>Current $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CTFPPPIDA669NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>CTFPPPIDA669NRUG</td>\n",
       "      <td>2019-06-11 20:33:07</td>\n",
       "      <td>Source ID: ctfp  When using these data in your...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1964-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Total Factor Productivity Level at Current Pur...</td>\n",
       "      <td>Index USA = 1</td>\n",
       "      <td>Index USA = 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RKNANPNGA666NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>RKNANPNGA666NRUG</td>\n",
       "      <td>2019-06-10 21:26:03</td>\n",
       "      <td>Source ID: rkna  When using these data in your...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1950-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Capital Stock at Constant National Prices for ...</td>\n",
       "      <td>Millions of 2011 U.S. Dollars</td>\n",
       "      <td>Mil. of 2011 U.S. $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GCT1502GA</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>GCT1502GA</td>\n",
       "      <td>2019-10-21 16:22:04</td>\n",
       "      <td>Estimate of educational attainment for populat...</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>2006-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Bachelor's Degree or Higher for Georgia</td>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MEHOINUSMDA646N</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>MEHOINUSMDA646N</td>\n",
       "      <td>2019-09-10 19:32:09</td>\n",
       "      <td>Household data are collected as of March.  As ...</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>1984-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Median Household Income in Maryland</td>\n",
       "      <td>Current Dollars</td>\n",
       "      <td>Current $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RKNANPVEA666NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>RKNANPVEA666NRUG</td>\n",
       "      <td>2019-06-10 21:26:04</td>\n",
       "      <td>Source ID: rkna  When using these data in your...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1950-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Capital Stock at Constant National Prices for ...</td>\n",
       "      <td>Millions of 2011 U.S. Dollars</td>\n",
       "      <td>Mil. of 2011 U.S. $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GCT1502OR</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>GCT1502OR</td>\n",
       "      <td>2019-10-21 16:23:05</td>\n",
       "      <td>Estimate of educational attainment for populat...</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>2006-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Bachelor's Degree or Higher for Oregon</td>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RTFPNASKA632NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>RTFPNASKA632NRUG</td>\n",
       "      <td>2019-06-11 20:33:30</td>\n",
       "      <td>Source ID: rtfpna  When using these data in yo...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1994-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Total Factor Productivity at Constant National...</td>\n",
       "      <td>Index 2011=1</td>\n",
       "      <td>Index 2011=1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1318CM156NNBR</th>\n",
       "      <td>Monthly</td>\n",
       "      <td>M</td>\n",
       "      <td>M1318CM156NNBR</td>\n",
       "      <td>2012-08-20 13:16:20</td>\n",
       "      <td>Source: Derived By NBER By Subtracting Series ...</td>\n",
       "      <td>1939-09-01</td>\n",
       "      <td>1876-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Excess of Paris Open Market Rate Over London D...</td>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XRNCUSKRA618NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>XRNCUSKRA618NRUG</td>\n",
       "      <td>2019-06-11 18:11:02</td>\n",
       "      <td>Source ID: xr  When using these data in your r...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1953-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Exchange Rate (market+estimated) for Republic ...</td>\n",
       "      <td>National Currency Units per US Dollar</td>\n",
       "      <td>National Currency Units per US $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RTFPNASIA632NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>RTFPNASIA632NRUG</td>\n",
       "      <td>2019-06-11 20:33:30</td>\n",
       "      <td>Source ID: rtfpna  When using these data in yo...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1994-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Total Factor Productivity at Constant National...</td>\n",
       "      <td>Index 2011=1</td>\n",
       "      <td>Index 2011=1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HCIYISHNA066NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>HCIYISHNA066NRUG</td>\n",
       "      <td>2019-06-11 18:13:06</td>\n",
       "      <td>Index of human capital per person, based on ye...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1950-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Index of Human Capital per Person for Honduras</td>\n",
       "      <td>Index</td>\n",
       "      <td>Index</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LABSHPSEA156NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>LABSHPSEA156NRUG</td>\n",
       "      <td>2019-06-11 18:12:46</td>\n",
       "      <td>Source ID: labsh  When using these data in you...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1950-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Share of Labour Compensation in GDP at Current...</td>\n",
       "      <td>Ratio</td>\n",
       "      <td>Ratio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGDPNAMNA666NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>RGDPNAMNA666NRUG</td>\n",
       "      <td>2019-06-11 18:13:59</td>\n",
       "      <td>Source ID: rgdpna  When using these data in yo...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1970-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Real GDP at Constant National Prices for Mongolia</td>\n",
       "      <td>Millions of 2011 U.S. Dollars</td>\n",
       "      <td>Mil. of 2011 U.S. $</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EMPENGRUA148NRUG</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>EMPENGRUA148NRUG</td>\n",
       "      <td>2019-06-11 18:15:05</td>\n",
       "      <td>Source ID: emp  When using these data in your ...</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Number of Persons Engaged for Russian Federation</td>\n",
       "      <td>Millions of Persons</td>\n",
       "      <td>Mil. of Persons</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HC01ESTVC1721067</th>\n",
       "      <td>Annual</td>\n",
       "      <td>A</td>\n",
       "      <td>HC01ESTVC1721067</td>\n",
       "      <td>2019-12-30 21:18:45</td>\n",
       "      <td>Estimate of educational attainment for populat...</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>2020-05-18</td>\n",
       "      <td>Not Seasonally Adjusted</td>\n",
       "      <td>NSA</td>\n",
       "      <td>Bachelor's Degree or Higher (5-year estimate) ...</td>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       frequency frequency_short  \\\n",
       "series id                                                          \n",
       "SP500                               Daily, Close               D   \n",
       "VXVCLS                              Daily, Close               D   \n",
       "VXOCLS                              Daily, Close               D   \n",
       "CSUSHPINSA                               Monthly               M   \n",
       "CSUSHPISA                                Monthly               M   \n",
       "SPCS20RSA                                Monthly               M   \n",
       "BAMLH0A0HYM2                        Daily, Close               D   \n",
       "SPCS20RNSA                               Monthly               M   \n",
       "BKTPAAA641N                               Annual               A   \n",
       "DJIA                                       Daily               D   \n",
       "SFXRSA                                   Monthly               M   \n",
       "MEHOINUSA672N                             Annual               A   \n",
       "LXXRSA                                   Monthly               M   \n",
       "SFXRNSA                                  Monthly               M   \n",
       "BAMLH0A0HYM2EY                      Daily, Close               D   \n",
       "LXXRNSA                                  Monthly               M   \n",
       "NYXRSA                                   Monthly               M   \n",
       "BAMLC0A0CM                          Daily, Close               D   \n",
       "SEXRNSA                                  Monthly               M   \n",
       "NYXRNSA                                  Monthly               M   \n",
       "SEXRSA                                   Monthly               M   \n",
       "DDDM01USA156NWDB                          Annual               A   \n",
       "STLFSI                     Weekly, Ending Friday               W   \n",
       "BOXRSA                                   Monthly               M   \n",
       "CHXRSA                                   Monthly               M   \n",
       "SDXRSA                                   Monthly               M   \n",
       "BOXRNSA                                  Monthly               M   \n",
       "DAXRNSA                                  Monthly               M   \n",
       "CHXRNSA                                  Monthly               M   \n",
       "SDXRNSA                                  Monthly               M   \n",
       "...                                          ...             ...   \n",
       "CGDPESITA666NRUG                          Annual               A   \n",
       "PLCCPPCNA670NRUG                          Annual               A   \n",
       "RGDPNAUYA666NRUG                          Annual               A   \n",
       "CTFPPPNLA669NRUG                          Annual               A   \n",
       "RKNANPECA666NRUG                          Annual               A   \n",
       "EMVTRADEPOLEMV                           Monthly               M   \n",
       "XRNCUSEGA618NRUG                          Annual               A   \n",
       "CTFPPPFRA669NRUG                          Annual               A   \n",
       "XRNCUSZWA618NRUG                          Annual               A   \n",
       "GCT1501CA                                 Annual               A   \n",
       "M0415BUS000NYM267NNBR                    Monthly               M   \n",
       "RGDPNAAMA666NRUG                          Annual               A   \n",
       "Q5APBM770A             Quarterly, End of Quarter               Q   \n",
       "M0553BM576NNBR             Monthly, End of Month               M   \n",
       "MEHOINUSAZA646N                           Annual               A   \n",
       "CTFPPPIDA669NRUG                          Annual               A   \n",
       "RKNANPNGA666NRUG                          Annual               A   \n",
       "GCT1502GA                                 Annual               A   \n",
       "MEHOINUSMDA646N                           Annual               A   \n",
       "RKNANPVEA666NRUG                          Annual               A   \n",
       "GCT1502OR                                 Annual               A   \n",
       "RTFPNASKA632NRUG                          Annual               A   \n",
       "M1318CM156NNBR                           Monthly               M   \n",
       "XRNCUSKRA618NRUG                          Annual               A   \n",
       "RTFPNASIA632NRUG                          Annual               A   \n",
       "HCIYISHNA066NRUG                          Annual               A   \n",
       "LABSHPSEA156NRUG                          Annual               A   \n",
       "RGDPNAMNA666NRUG                          Annual               A   \n",
       "EMPENGRUA148NRUG                          Annual               A   \n",
       "HC01ESTVC1721067                          Annual               A   \n",
       "\n",
       "                                          id        last_updated  \\\n",
       "series id                                                          \n",
       "SP500                                  SP500 2020-05-16 00:10:58   \n",
       "VXVCLS                                VXVCLS 2020-05-18 13:36:05   \n",
       "VXOCLS                                VXOCLS 2020-05-18 13:36:07   \n",
       "CSUSHPINSA                        CSUSHPINSA 2020-04-28 13:31:01   \n",
       "CSUSHPISA                          CSUSHPISA 2020-04-28 13:31:12   \n",
       "SPCS20RSA                          SPCS20RSA 2020-04-28 13:31:05   \n",
       "BAMLH0A0HYM2                    BAMLH0A0HYM2 2020-05-18 12:46:02   \n",
       "SPCS20RNSA                        SPCS20RNSA 2020-04-28 13:31:37   \n",
       "BKTPAAA641N                      BKTPAAA641N 2020-02-21 21:43:03   \n",
       "DJIA                                    DJIA 2020-05-16 00:01:02   \n",
       "SFXRSA                                SFXRSA 2020-04-28 13:32:01   \n",
       "MEHOINUSA672N                  MEHOINUSA672N 2019-09-10 19:32:02   \n",
       "LXXRSA                                LXXRSA 2020-04-28 13:32:02   \n",
       "SFXRNSA                              SFXRNSA 2020-04-28 13:32:11   \n",
       "BAMLH0A0HYM2EY                BAMLH0A0HYM2EY 2020-05-18 12:43:01   \n",
       "LXXRNSA                              LXXRNSA 2020-04-28 13:32:11   \n",
       "NYXRSA                                NYXRSA 2020-04-28 13:31:13   \n",
       "BAMLC0A0CM                        BAMLC0A0CM 2020-05-18 12:46:25   \n",
       "SEXRNSA                              SEXRNSA 2020-04-28 13:31:16   \n",
       "NYXRNSA                              NYXRNSA 2020-04-28 13:32:11   \n",
       "SEXRSA                                SEXRSA 2020-04-28 13:31:34   \n",
       "DDDM01USA156NWDB            DDDM01USA156NWDB 2019-10-21 19:50:02   \n",
       "STLFSI                                STLFSI 2020-03-19 14:00:02   \n",
       "BOXRSA                                BOXRSA 2020-04-28 13:31:20   \n",
       "CHXRSA                                CHXRSA 2020-04-28 13:32:05   \n",
       "SDXRSA                                SDXRSA 2020-04-28 13:31:17   \n",
       "BOXRNSA                              BOXRNSA 2020-04-28 13:31:50   \n",
       "DAXRNSA                              DAXRNSA 2020-04-28 13:31:22   \n",
       "CHXRNSA                              CHXRNSA 2020-04-28 13:31:47   \n",
       "SDXRNSA                              SDXRNSA 2020-04-28 13:31:49   \n",
       "...                                      ...                 ...   \n",
       "CGDPESITA666NRUG            CGDPESITA666NRUG 2019-06-11 18:17:02   \n",
       "PLCCPPCNA670NRUG            PLCCPPCNA670NRUG 2019-06-11 18:12:38   \n",
       "RGDPNAUYA666NRUG            RGDPNAUYA666NRUG 2019-06-11 18:11:01   \n",
       "CTFPPPNLA669NRUG            CTFPPPNLA669NRUG 2019-06-11 20:33:09   \n",
       "RKNANPECA666NRUG            RKNANPECA666NRUG 2019-06-10 21:26:04   \n",
       "EMVTRADEPOLEMV                EMVTRADEPOLEMV 2020-05-04 15:32:05   \n",
       "XRNCUSEGA618NRUG            XRNCUSEGA618NRUG 2019-06-11 18:12:59   \n",
       "CTFPPPFRA669NRUG            CTFPPPFRA669NRUG 2019-06-11 20:33:07   \n",
       "XRNCUSZWA618NRUG            XRNCUSZWA618NRUG 2019-06-11 18:12:35   \n",
       "GCT1501CA                          GCT1501CA 2019-10-21 16:23:03   \n",
       "M0415BUS000NYM267NNBR  M0415BUS000NYM267NNBR 2012-08-16 20:16:06   \n",
       "RGDPNAAMA666NRUG            RGDPNAAMA666NRUG 2019-06-11 18:12:37   \n",
       "Q5APBM770A                        Q5APBM770A 2020-03-01 19:01:17   \n",
       "M0553BM576NNBR                M0553BM576NNBR 2012-08-17 15:47:54   \n",
       "MEHOINUSAZA646N              MEHOINUSAZA646N 2019-09-10 19:32:09   \n",
       "CTFPPPIDA669NRUG            CTFPPPIDA669NRUG 2019-06-11 20:33:07   \n",
       "RKNANPNGA666NRUG            RKNANPNGA666NRUG 2019-06-10 21:26:03   \n",
       "GCT1502GA                          GCT1502GA 2019-10-21 16:22:04   \n",
       "MEHOINUSMDA646N              MEHOINUSMDA646N 2019-09-10 19:32:09   \n",
       "RKNANPVEA666NRUG            RKNANPVEA666NRUG 2019-06-10 21:26:04   \n",
       "GCT1502OR                          GCT1502OR 2019-10-21 16:23:05   \n",
       "RTFPNASKA632NRUG            RTFPNASKA632NRUG 2019-06-11 20:33:30   \n",
       "M1318CM156NNBR                M1318CM156NNBR 2012-08-20 13:16:20   \n",
       "XRNCUSKRA618NRUG            XRNCUSKRA618NRUG 2019-06-11 18:11:02   \n",
       "RTFPNASIA632NRUG            RTFPNASIA632NRUG 2019-06-11 20:33:30   \n",
       "HCIYISHNA066NRUG            HCIYISHNA066NRUG 2019-06-11 18:13:06   \n",
       "LABSHPSEA156NRUG            LABSHPSEA156NRUG 2019-06-11 18:12:46   \n",
       "RGDPNAMNA666NRUG            RGDPNAMNA666NRUG 2019-06-11 18:13:59   \n",
       "EMPENGRUA148NRUG            EMPENGRUA148NRUG 2019-06-11 18:15:05   \n",
       "HC01ESTVC1721067            HC01ESTVC1721067 2019-12-30 21:18:45   \n",
       "\n",
       "                                                                   notes  \\\n",
       "series id                                                                  \n",
       "SP500                  The observations for the S&P 500 represent the...   \n",
       "VXVCLS                 Copyright, 2016, Chicago Board Options Exchang...   \n",
       "VXOCLS                 Copyright, 2016, Chicago Board Options Exchang...   \n",
       "CSUSHPINSA             For more information regarding the index, plea...   \n",
       "CSUSHPISA              For more information regarding the index, plea...   \n",
       "SPCS20RSA              For more information regarding the index, plea...   \n",
       "BAMLH0A0HYM2           The ICE BofA Option-Adjusted Spreads (OASs) ar...   \n",
       "SPCS20RNSA             For more information regarding the index, plea...   \n",
       "BKTPAAA641N            Transaction Types Institutions have been resol...   \n",
       "DJIA                   The observations for the Dow Jones Industrial ...   \n",
       "SFXRSA                 For more information regarding the index, plea...   \n",
       "MEHOINUSA672N          Household data are collected as of March.  As ...   \n",
       "LXXRSA                 For more information regarding the index, plea...   \n",
       "SFXRNSA                For more information regarding the index, plea...   \n",
       "BAMLH0A0HYM2EY         This data represents the effective yield of th...   \n",
       "LXXRNSA                For more information regarding the index, plea...   \n",
       "NYXRSA                 For more information regarding the index, plea...   \n",
       "BAMLC0A0CM             The ICE BofA Option-Adjusted Spreads (OASs) ar...   \n",
       "SEXRNSA                For more information regarding the index, plea...   \n",
       "NYXRNSA                For more information regarding the index, plea...   \n",
       "SEXRSA                 For more information regarding the index, plea...   \n",
       "DDDM01USA156NWDB       Total value of all listed shares in a stock ma...   \n",
       "STLFSI                 The methodology for the St. Louis Fed's Financ...   \n",
       "BOXRSA                 For more information regarding the index, plea...   \n",
       "CHXRSA                 For more information regarding the index, plea...   \n",
       "SDXRSA                 For more information regarding the index, plea...   \n",
       "BOXRNSA                For more information regarding the index, plea...   \n",
       "DAXRNSA                For more information regarding the index, plea...   \n",
       "CHXRNSA                For more information regarding the index, plea...   \n",
       "SDXRNSA                For more information regarding the index, plea...   \n",
       "...                                                                  ...   \n",
       "CGDPESITA666NRUG       Source ID: cgdpe  When using these data in you...   \n",
       "PLCCPPCNA670NRUG       Source ID: pl_c  When using these data in your...   \n",
       "RGDPNAUYA666NRUG       Source ID: rgdpna  When using these data in yo...   \n",
       "CTFPPPNLA669NRUG       Source ID: ctfp  When using these data in your...   \n",
       "RKNANPECA666NRUG       Source ID: rkna  When using these data in your...   \n",
       "EMVTRADEPOLEMV         The Equity Market Volatility tracker moves wit...   \n",
       "XRNCUSEGA618NRUG       Source ID: xr  When using these data in your r...   \n",
       "CTFPPPFRA669NRUG       Source ID: ctfp  When using these data in your...   \n",
       "XRNCUSZWA618NRUG       Source ID: xr  When using these data in your r...   \n",
       "GCT1501CA              Estimate of educational attainment for populat...   \n",
       "M0415BUS000NYM267NNBR  Series Has Been Subdivided Into Two Variables:...   \n",
       "RGDPNAAMA666NRUG       Source ID: rgdpna  When using these data in yo...   \n",
       "Q5APBM770A             Credit is provided by domestic banks, all othe...   \n",
       "M0553BM576NNBR         Series Is Presented Here As Two Variables--(1)...   \n",
       "MEHOINUSAZA646N        Household data are collected as of March.  As ...   \n",
       "CTFPPPIDA669NRUG       Source ID: ctfp  When using these data in your...   \n",
       "RKNANPNGA666NRUG       Source ID: rkna  When using these data in your...   \n",
       "GCT1502GA              Estimate of educational attainment for populat...   \n",
       "MEHOINUSMDA646N        Household data are collected as of March.  As ...   \n",
       "RKNANPVEA666NRUG       Source ID: rkna  When using these data in your...   \n",
       "GCT1502OR              Estimate of educational attainment for populat...   \n",
       "RTFPNASKA632NRUG       Source ID: rtfpna  When using these data in yo...   \n",
       "M1318CM156NNBR         Source: Derived By NBER By Subtracting Series ...   \n",
       "XRNCUSKRA618NRUG       Source ID: xr  When using these data in your r...   \n",
       "RTFPNASIA632NRUG       Source ID: rtfpna  When using these data in yo...   \n",
       "HCIYISHNA066NRUG       Index of human capital per person, based on ye...   \n",
       "LABSHPSEA156NRUG       Source ID: labsh  When using these data in you...   \n",
       "RGDPNAMNA666NRUG       Source ID: rgdpna  When using these data in yo...   \n",
       "EMPENGRUA148NRUG       Source ID: emp  When using these data in your ...   \n",
       "HC01ESTVC1721067       Estimate of educational attainment for populat...   \n",
       "\n",
       "                      observation_end observation_start popularity  \\\n",
       "series id                                                            \n",
       "SP500                      2020-05-15        2010-05-17         88   \n",
       "VXVCLS                     2020-05-15        2007-12-04         57   \n",
       "VXOCLS                     2020-05-15        1986-01-02         46   \n",
       "CSUSHPINSA                 2020-02-01        1987-01-01         88   \n",
       "CSUSHPISA                  2020-02-01        1987-01-01         77   \n",
       "SPCS20RSA                  2020-02-01        2000-01-01         83   \n",
       "BAMLH0A0HYM2               2020-05-15        1996-12-31        100   \n",
       "SPCS20RNSA                 2020-02-01        2000-01-01         36   \n",
       "BKTPAAA641N                2020-01-01        1934-01-01          2   \n",
       "DJIA                       2020-05-15        2010-05-17         80   \n",
       "SFXRSA                     2020-02-01        1987-01-01         71   \n",
       "MEHOINUSA672N              2018-01-01        1984-01-01         87   \n",
       "LXXRSA                     2020-02-01        1987-01-01         69   \n",
       "SFXRNSA                    2020-02-01        1987-01-01         22   \n",
       "BAMLH0A0HYM2EY             2020-05-15        1996-12-31         84   \n",
       "LXXRNSA                    2020-02-01        1987-01-01         30   \n",
       "NYXRSA                     2020-02-01        1987-01-01         66   \n",
       "BAMLC0A0CM                 2020-05-15        1996-12-31         82   \n",
       "SEXRNSA                    2020-02-01        1990-01-01         63   \n",
       "NYXRNSA                    2020-02-01        1987-01-01         18   \n",
       "SEXRSA                     2020-02-01        1990-01-01         37   \n",
       "DDDM01USA156NWDB           2017-01-01        1996-01-01         78   \n",
       "STLFSI                     2020-03-13        1993-12-31         77   \n",
       "BOXRSA                     2020-02-01        1987-01-01         60   \n",
       "CHXRSA                     2020-02-01        1987-01-01         60   \n",
       "SDXRSA                     2020-02-01        1987-01-01         59   \n",
       "BOXRNSA                    2020-02-01        1987-01-01         19   \n",
       "DAXRNSA                    2020-02-01        2000-01-01         55   \n",
       "CHXRNSA                    2020-02-01        1987-01-01         16   \n",
       "SDXRNSA                    2020-02-01        1987-01-01         15   \n",
       "...                               ...               ...        ...   \n",
       "CGDPESITA666NRUG           2017-01-01        1950-01-01          4   \n",
       "PLCCPPCNA670NRUG           2017-01-01        1952-01-01          4   \n",
       "RGDPNAUYA666NRUG           2017-01-01        1950-01-01          4   \n",
       "CTFPPPNLA669NRUG           2017-01-01        1954-01-01          4   \n",
       "RKNANPECA666NRUG           2017-01-01        1950-01-01          4   \n",
       "EMVTRADEPOLEMV             2020-04-01        1985-01-01          4   \n",
       "XRNCUSEGA618NRUG           2017-01-01        1950-01-01          4   \n",
       "CTFPPPFRA669NRUG           2017-01-01        1954-01-01          4   \n",
       "XRNCUSZWA618NRUG           2017-01-01        1954-01-01          4   \n",
       "GCT1501CA                  2018-01-01        2006-01-01          4   \n",
       "M0415BUS000NYM267NNBR      1955-07-01        1911-01-01          4   \n",
       "RGDPNAAMA666NRUG           2017-01-01        1990-01-01          4   \n",
       "Q5APBM770A                 2019-07-01        1997-07-01          4   \n",
       "M0553BM576NNBR             1956-02-01        1938-01-01          4   \n",
       "MEHOINUSAZA646N            2018-01-01        1984-01-01          4   \n",
       "CTFPPPIDA669NRUG           2017-01-01        1964-01-01          4   \n",
       "RKNANPNGA666NRUG           2017-01-01        1950-01-01          4   \n",
       "GCT1502GA                  2018-01-01        2006-01-01          4   \n",
       "MEHOINUSMDA646N            2018-01-01        1984-01-01          4   \n",
       "RKNANPVEA666NRUG           2017-01-01        1950-01-01          4   \n",
       "GCT1502OR                  2018-01-01        2006-01-01          4   \n",
       "RTFPNASKA632NRUG           2017-01-01        1994-01-01          4   \n",
       "M1318CM156NNBR             1939-09-01        1876-01-01          4   \n",
       "XRNCUSKRA618NRUG           2017-01-01        1953-01-01          4   \n",
       "RTFPNASIA632NRUG           2017-01-01        1994-01-01          4   \n",
       "HCIYISHNA066NRUG           2017-01-01        1950-01-01          4   \n",
       "LABSHPSEA156NRUG           2017-01-01        1950-01-01          4   \n",
       "RGDPNAMNA666NRUG           2017-01-01        1970-01-01          4   \n",
       "EMPENGRUA148NRUG           2017-01-01        1990-01-01          4   \n",
       "HC01ESTVC1721067           2018-01-01        2010-01-01          4   \n",
       "\n",
       "                      realtime_end realtime_start      seasonal_adjustment  \\\n",
       "series id                                                                    \n",
       "SP500                   2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "VXVCLS                  2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "VXOCLS                  2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "CSUSHPINSA              2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "CSUSHPISA               2020-05-18     2020-05-18      Seasonally Adjusted   \n",
       "SPCS20RSA               2020-05-18     2020-05-18      Seasonally Adjusted   \n",
       "BAMLH0A0HYM2            2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "SPCS20RNSA              2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "BKTPAAA641N             2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "DJIA                    2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "SFXRSA                  2020-05-18     2020-05-18      Seasonally Adjusted   \n",
       "MEHOINUSA672N           2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "LXXRSA                  2020-05-18     2020-05-18      Seasonally Adjusted   \n",
       "SFXRNSA                 2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "BAMLH0A0HYM2EY          2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "LXXRNSA                 2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "NYXRSA                  2020-05-18     2020-05-18      Seasonally Adjusted   \n",
       "BAMLC0A0CM              2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "SEXRNSA                 2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "NYXRNSA                 2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "SEXRSA                  2020-05-18     2020-05-18      Seasonally Adjusted   \n",
       "DDDM01USA156NWDB        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "STLFSI                  2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "BOXRSA                  2020-05-18     2020-05-18      Seasonally Adjusted   \n",
       "CHXRSA                  2020-05-18     2020-05-18      Seasonally Adjusted   \n",
       "SDXRSA                  2020-05-18     2020-05-18      Seasonally Adjusted   \n",
       "BOXRNSA                 2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "DAXRNSA                 2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "CHXRNSA                 2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "SDXRNSA                 2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "...                            ...            ...                      ...   \n",
       "CGDPESITA666NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "PLCCPPCNA670NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "RGDPNAUYA666NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "CTFPPPNLA669NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "RKNANPECA666NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "EMVTRADEPOLEMV          2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "XRNCUSEGA618NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "CTFPPPFRA669NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "XRNCUSZWA618NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "GCT1501CA               2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "M0415BUS000NYM267NNBR   2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "RGDPNAAMA666NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "Q5APBM770A              2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "M0553BM576NNBR          2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "MEHOINUSAZA646N         2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "CTFPPPIDA669NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "RKNANPNGA666NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "GCT1502GA               2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "MEHOINUSMDA646N         2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "RKNANPVEA666NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "GCT1502OR               2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "RTFPNASKA632NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "M1318CM156NNBR          2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "XRNCUSKRA618NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "RTFPNASIA632NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "HCIYISHNA066NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "LABSHPSEA156NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "RGDPNAMNA666NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "EMPENGRUA148NRUG        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "HC01ESTVC1721067        2020-05-18     2020-05-18  Not Seasonally Adjusted   \n",
       "\n",
       "                      seasonal_adjustment_short  \\\n",
       "series id                                         \n",
       "SP500                                       NSA   \n",
       "VXVCLS                                      NSA   \n",
       "VXOCLS                                      NSA   \n",
       "CSUSHPINSA                                  NSA   \n",
       "CSUSHPISA                                    SA   \n",
       "SPCS20RSA                                    SA   \n",
       "BAMLH0A0HYM2                                NSA   \n",
       "SPCS20RNSA                                  NSA   \n",
       "BKTPAAA641N                                 NSA   \n",
       "DJIA                                        NSA   \n",
       "SFXRSA                                       SA   \n",
       "MEHOINUSA672N                               NSA   \n",
       "LXXRSA                                       SA   \n",
       "SFXRNSA                                     NSA   \n",
       "BAMLH0A0HYM2EY                              NSA   \n",
       "LXXRNSA                                     NSA   \n",
       "NYXRSA                                       SA   \n",
       "BAMLC0A0CM                                  NSA   \n",
       "SEXRNSA                                     NSA   \n",
       "NYXRNSA                                     NSA   \n",
       "SEXRSA                                       SA   \n",
       "DDDM01USA156NWDB                            NSA   \n",
       "STLFSI                                      NSA   \n",
       "BOXRSA                                       SA   \n",
       "CHXRSA                                       SA   \n",
       "SDXRSA                                       SA   \n",
       "BOXRNSA                                     NSA   \n",
       "DAXRNSA                                     NSA   \n",
       "CHXRNSA                                     NSA   \n",
       "SDXRNSA                                     NSA   \n",
       "...                                         ...   \n",
       "CGDPESITA666NRUG                            NSA   \n",
       "PLCCPPCNA670NRUG                            NSA   \n",
       "RGDPNAUYA666NRUG                            NSA   \n",
       "CTFPPPNLA669NRUG                            NSA   \n",
       "RKNANPECA666NRUG                            NSA   \n",
       "EMVTRADEPOLEMV                              NSA   \n",
       "XRNCUSEGA618NRUG                            NSA   \n",
       "CTFPPPFRA669NRUG                            NSA   \n",
       "XRNCUSZWA618NRUG                            NSA   \n",
       "GCT1501CA                                   NSA   \n",
       "M0415BUS000NYM267NNBR                       NSA   \n",
       "RGDPNAAMA666NRUG                            NSA   \n",
       "Q5APBM770A                                  NSA   \n",
       "M0553BM576NNBR                              NSA   \n",
       "MEHOINUSAZA646N                             NSA   \n",
       "CTFPPPIDA669NRUG                            NSA   \n",
       "RKNANPNGA666NRUG                            NSA   \n",
       "GCT1502GA                                   NSA   \n",
       "MEHOINUSMDA646N                             NSA   \n",
       "RKNANPVEA666NRUG                            NSA   \n",
       "GCT1502OR                                   NSA   \n",
       "RTFPNASKA632NRUG                            NSA   \n",
       "M1318CM156NNBR                              NSA   \n",
       "XRNCUSKRA618NRUG                            NSA   \n",
       "RTFPNASIA632NRUG                            NSA   \n",
       "HCIYISHNA066NRUG                            NSA   \n",
       "LABSHPSEA156NRUG                            NSA   \n",
       "RGDPNAMNA666NRUG                            NSA   \n",
       "EMPENGRUA148NRUG                            NSA   \n",
       "HC01ESTVC1721067                            NSA   \n",
       "\n",
       "                                                                   title  \\\n",
       "series id                                                                  \n",
       "SP500                                                            S&P 500   \n",
       "VXVCLS                             CBOE S&P 500 3-Month Volatility Index   \n",
       "VXOCLS                                CBOE S&P 100 Volatility Index: VXO   \n",
       "CSUSHPINSA               S&P/Case-Shiller U.S. National Home Price Index   \n",
       "CSUSHPISA                S&P/Case-Shiller U.S. National Home Price Index   \n",
       "SPCS20RSA              S&P/Case-Shiller 20-City Composite Home Price ...   \n",
       "BAMLH0A0HYM2           ICE BofA US High Yield Index Option-Adjusted S...   \n",
       "SPCS20RNSA             S&P/Case-Shiller 20-City Composite Home Price ...   \n",
       "BKTPAAA641N            Failures and Assistance Transactions of all In...   \n",
       "DJIA                                        Dow Jones Industrial Average   \n",
       "SFXRSA                 S&P/Case-Shiller CA-San Francisco Home Price I...   \n",
       "MEHOINUSA672N          Real Median Household Income in the United States   \n",
       "LXXRSA                  S&P/Case-Shiller CA-Los Angeles Home Price Index   \n",
       "SFXRNSA                S&P/Case-Shiller CA-San Francisco Home Price I...   \n",
       "BAMLH0A0HYM2EY              ICE BofA US High Yield Index Effective Yield   \n",
       "LXXRNSA                 S&P/Case-Shiller CA-Los Angeles Home Price Index   \n",
       "NYXRSA                     S&P/Case-Shiller NY-New York Home Price Index   \n",
       "BAMLC0A0CM             ICE BofA US Corporate Index Option-Adjusted Sp...   \n",
       "SEXRNSA                     S&P/Case-Shiller WA-Seattle Home Price Index   \n",
       "NYXRNSA                    S&P/Case-Shiller NY-New York Home Price Index   \n",
       "SEXRSA                      S&P/Case-Shiller WA-Seattle Home Price Index   \n",
       "DDDM01USA156NWDB       Stock Market Capitalization to GDP for United ...   \n",
       "STLFSI                 St. Louis Fed Financial Stress Index (DISCONTI...   \n",
       "BOXRSA                       S&P/Case-Shiller MA-Boston Home Price Index   \n",
       "CHXRSA                      S&P/Case-Shiller IL-Chicago Home Price Index   \n",
       "SDXRSA                    S&P/Case-Shiller CA-San Diego Home Price Index   \n",
       "BOXRNSA                      S&P/Case-Shiller MA-Boston Home Price Index   \n",
       "DAXRNSA                      S&P/Case-Shiller TX-Dallas Home Price Index   \n",
       "CHXRNSA                     S&P/Case-Shiller IL-Chicago Home Price Index   \n",
       "SDXRNSA                   S&P/Case-Shiller CA-San Diego Home Price Index   \n",
       "...                                                                  ...   \n",
       "CGDPESITA666NRUG       Expenditure-side Real GDP at Current Purchasin...   \n",
       "PLCCPPCNA670NRUG          Price Level of Household Consumption for China   \n",
       "RGDPNAUYA666NRUG        Real GDP at Constant National Prices for Uruguay   \n",
       "CTFPPPNLA669NRUG       Total Factor Productivity Level at Current Pur...   \n",
       "RKNANPECA666NRUG       Capital Stock at Constant National Prices for ...   \n",
       "EMVTRADEPOLEMV            Equity Market Volatility Tracker: Trade Policy   \n",
       "XRNCUSEGA618NRUG              Exchange Rate (market+estimated) for Egypt   \n",
       "CTFPPPFRA669NRUG       Total Factor Productivity Level at Current Pur...   \n",
       "XRNCUSZWA618NRUG           Exchange Rate (market+estimated) for Zimbabwe   \n",
       "GCT1501CA                  High School Graduate or Higher for California   \n",
       "M0415BUS000NYM267NNBR  Wholesale Price of Copper, Electrolyte for New...   \n",
       "RGDPNAAMA666NRUG        Real GDP at Constant National Prices for Armenia   \n",
       "Q5APBM770A             Credit to Private Non-Financial Sector by Bank...   \n",
       "M0553BM576NNBR                       Crude Rubber Stocks, U.S.-- Natural   \n",
       "MEHOINUSAZA646N                       Median Household Income in Arizona   \n",
       "CTFPPPIDA669NRUG       Total Factor Productivity Level at Current Pur...   \n",
       "RKNANPNGA666NRUG       Capital Stock at Constant National Prices for ...   \n",
       "GCT1502GA                        Bachelor's Degree or Higher for Georgia   \n",
       "MEHOINUSMDA646N                      Median Household Income in Maryland   \n",
       "RKNANPVEA666NRUG       Capital Stock at Constant National Prices for ...   \n",
       "GCT1502OR                         Bachelor's Degree or Higher for Oregon   \n",
       "RTFPNASKA632NRUG       Total Factor Productivity at Constant National...   \n",
       "M1318CM156NNBR         Excess of Paris Open Market Rate Over London D...   \n",
       "XRNCUSKRA618NRUG       Exchange Rate (market+estimated) for Republic ...   \n",
       "RTFPNASIA632NRUG       Total Factor Productivity at Constant National...   \n",
       "HCIYISHNA066NRUG          Index of Human Capital per Person for Honduras   \n",
       "LABSHPSEA156NRUG       Share of Labour Compensation in GDP at Current...   \n",
       "RGDPNAMNA666NRUG       Real GDP at Constant National Prices for Mongolia   \n",
       "EMPENGRUA148NRUG        Number of Persons Engaged for Russian Federation   \n",
       "HC01ESTVC1721067       Bachelor's Degree or Higher (5-year estimate) ...   \n",
       "\n",
       "                                                              units  \\\n",
       "series id                                                             \n",
       "SP500                                                         Index   \n",
       "VXVCLS                                                        Index   \n",
       "VXOCLS                                                        Index   \n",
       "CSUSHPINSA                                       Index Jan 2000=100   \n",
       "CSUSHPISA                                        Index Jan 2000=100   \n",
       "SPCS20RSA                                        Index Jan 2000=100   \n",
       "BAMLH0A0HYM2                                                Percent   \n",
       "SPCS20RNSA                                       Index Jan 2000=100   \n",
       "BKTPAAA641N                                  Number of Institutions   \n",
       "DJIA                                                          Index   \n",
       "SFXRSA                                           Index Jan 2000=100   \n",
       "MEHOINUSA672N                        2018 CPI-U-RS Adjusted Dollars   \n",
       "LXXRSA                                           Index Jan 2000=100   \n",
       "SFXRNSA                                          Index Jan 2000=100   \n",
       "BAMLH0A0HYM2EY                                              Percent   \n",
       "LXXRNSA                                          Index Jan 2000=100   \n",
       "NYXRSA                                           Index Jan 2000=100   \n",
       "BAMLC0A0CM                                                  Percent   \n",
       "SEXRNSA                                          Index Jan 2000=100   \n",
       "NYXRNSA                                          Index Jan 2000=100   \n",
       "SEXRSA                                           Index Jan 2000=100   \n",
       "DDDM01USA156NWDB                                            Percent   \n",
       "STLFSI                                                        Index   \n",
       "BOXRSA                                           Index Jan 2000=100   \n",
       "CHXRSA                                           Index Jan 2000=100   \n",
       "SDXRSA                                           Index Jan 2000=100   \n",
       "BOXRNSA                                          Index Jan 2000=100   \n",
       "DAXRNSA                                          Index Jan 2000=100   \n",
       "CHXRNSA                                          Index Jan 2000=100   \n",
       "SDXRNSA                                          Index Jan 2000=100   \n",
       "...                                                             ...   \n",
       "CGDPESITA666NRUG                      Millions of 2011 U.S. Dollars   \n",
       "PLCCPPCNA670NRUG       Price Level of USA Output-side GDP in 2011=1   \n",
       "RGDPNAUYA666NRUG                      Millions of 2011 U.S. Dollars   \n",
       "CTFPPPNLA669NRUG                                      Index USA = 1   \n",
       "RKNANPECA666NRUG                      Millions of 2011 U.S. Dollars   \n",
       "EMVTRADEPOLEMV                                                Index   \n",
       "XRNCUSEGA618NRUG              National Currency Units per US Dollar   \n",
       "CTFPPPFRA669NRUG                                      Index USA = 1   \n",
       "XRNCUSZWA618NRUG              National Currency Units per US Dollar   \n",
       "GCT1501CA                                                   Percent   \n",
       "M0415BUS000NYM267NNBR                               Cents per Pound   \n",
       "RGDPNAAMA666NRUG                      Millions of 2011 U.S. Dollars   \n",
       "Q5APBM770A                                        Percentage of GDP   \n",
       "M0553BM576NNBR                               Thousands of Long Tons   \n",
       "MEHOINUSAZA646N                                     Current Dollars   \n",
       "CTFPPPIDA669NRUG                                      Index USA = 1   \n",
       "RKNANPNGA666NRUG                      Millions of 2011 U.S. Dollars   \n",
       "GCT1502GA                                                   Percent   \n",
       "MEHOINUSMDA646N                                     Current Dollars   \n",
       "RKNANPVEA666NRUG                      Millions of 2011 U.S. Dollars   \n",
       "GCT1502OR                                                   Percent   \n",
       "RTFPNASKA632NRUG                                       Index 2011=1   \n",
       "M1318CM156NNBR                                              Percent   \n",
       "XRNCUSKRA618NRUG              National Currency Units per US Dollar   \n",
       "RTFPNASIA632NRUG                                       Index 2011=1   \n",
       "HCIYISHNA066NRUG                                              Index   \n",
       "LABSHPSEA156NRUG                                              Ratio   \n",
       "RGDPNAMNA666NRUG                      Millions of 2011 U.S. Dollars   \n",
       "EMPENGRUA148NRUG                                Millions of Persons   \n",
       "HC01ESTVC1721067                                            Percent   \n",
       "\n",
       "                                                        units_short  \n",
       "series id                                                            \n",
       "SP500                                                         Index  \n",
       "VXVCLS                                                        Index  \n",
       "VXOCLS                                                        Index  \n",
       "CSUSHPINSA                                       Index Jan 2000=100  \n",
       "CSUSHPISA                                        Index Jan 2000=100  \n",
       "SPCS20RSA                                        Index Jan 2000=100  \n",
       "BAMLH0A0HYM2                                                      %  \n",
       "SPCS20RNSA                                       Index Jan 2000=100  \n",
       "BKTPAAA641N                                  Number of Institutions  \n",
       "DJIA                                                          Index  \n",
       "SFXRSA                                           Index Jan 2000=100  \n",
       "MEHOINUSA672N                              2018 CPI-U-RS Adjusted $  \n",
       "LXXRSA                                         Index Jan 2000 = 100  \n",
       "SFXRNSA                                        Index Jan 2000 = 100  \n",
       "BAMLH0A0HYM2EY                                                    %  \n",
       "LXXRNSA                                        Index Jan 2000 = 100  \n",
       "NYXRSA                                         Index Jan 2000 = 100  \n",
       "BAMLC0A0CM                                                        %  \n",
       "SEXRNSA                                        Index Jan 2000 = 100  \n",
       "NYXRNSA                                        Index Jan 2000 = 100  \n",
       "SEXRSA                                         Index Jan 2000 = 100  \n",
       "DDDM01USA156NWDB                                                  %  \n",
       "STLFSI                                                        Index  \n",
       "BOXRSA                                         Index Jan 2000 = 100  \n",
       "CHXRSA                                         Index Jan 2000 = 100  \n",
       "SDXRSA                                         Index Jan 2000 = 100  \n",
       "BOXRNSA                                        Index Jan 2000 = 100  \n",
       "DAXRNSA                                        Index Jan 2000 = 100  \n",
       "CHXRNSA                                        Index Jan 2000 = 100  \n",
       "SDXRNSA                                        Index Jan 2000 = 100  \n",
       "...                                                             ...  \n",
       "CGDPESITA666NRUG                                Mil. of 2011 U.S. $  \n",
       "PLCCPPCNA670NRUG       Price Level of USA Output-side GDP in 2011=1  \n",
       "RGDPNAUYA666NRUG                                Mil. of 2011 U.S. $  \n",
       "CTFPPPNLA669NRUG                                      Index USA = 1  \n",
       "RKNANPECA666NRUG                                Mil. of 2011 U.S. $  \n",
       "EMVTRADEPOLEMV                                                Index  \n",
       "XRNCUSEGA618NRUG                   National Currency Units per US $  \n",
       "CTFPPPFRA669NRUG                                      Index USA = 1  \n",
       "XRNCUSZWA618NRUG                   National Currency Units per US $  \n",
       "GCT1501CA                                                         %  \n",
       "M0415BUS000NYM267NNBR                               Cents Per Pound  \n",
       "RGDPNAAMA666NRUG                                Mil. of 2011 U.S. $  \n",
       "Q5APBM770A                                        Percentage of GDP  \n",
       "M0553BM576NNBR                                  Thous. Of Long Tons  \n",
       "MEHOINUSAZA646N                                           Current $  \n",
       "CTFPPPIDA669NRUG                                      Index USA = 1  \n",
       "RKNANPNGA666NRUG                                Mil. of 2011 U.S. $  \n",
       "GCT1502GA                                                         %  \n",
       "MEHOINUSMDA646N                                           Current $  \n",
       "RKNANPVEA666NRUG                                Mil. of 2011 U.S. $  \n",
       "GCT1502OR                                                         %  \n",
       "RTFPNASKA632NRUG                                       Index 2011=1  \n",
       "M1318CM156NNBR                                                    %  \n",
       "XRNCUSKRA618NRUG                   National Currency Units per US $  \n",
       "RTFPNASIA632NRUG                                       Index 2011=1  \n",
       "HCIYISHNA066NRUG                                              Index  \n",
       "LABSHPSEA156NRUG                                              Ratio  \n",
       "RGDPNAMNA666NRUG                                Mil. of 2011 U.S. $  \n",
       "EMPENGRUA148NRUG                                    Mil. of Persons  \n",
       "HC01ESTVC1721067                                                  %  \n",
       "\n",
       "[1000 rows x 15 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# search for VIX indicator\n",
    "fred.search('s&p')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Design an algorithm\n",
    "e.g. Mean Reversion algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>VIX</th>\n",
       "      <th>SPY</th>\n",
       "      <th>Short Vol Ret</th>\n",
       "      <th>Long Vol Ret</th>\n",
       "      <th>L-S Port.</th>\n",
       "      <th>Moving Avg. VIX</th>\n",
       "      <th>Buy Column</th>\n",
       "      <th>L-S Mean Reversion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1563</th>\n",
       "      <td>2017-02-16</td>\n",
       "      <td>11.76</td>\n",
       "      <td>234.720001</td>\n",
       "      <td>-0.005169</td>\n",
       "      <td>-0.007594</td>\n",
       "      <td>-0.006382</td>\n",
       "      <td>13.227921</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1564</th>\n",
       "      <td>2017-02-17</td>\n",
       "      <td>11.49</td>\n",
       "      <td>235.089996</td>\n",
       "      <td>-0.002286</td>\n",
       "      <td>-0.001650</td>\n",
       "      <td>-0.001968</td>\n",
       "      <td>13.220000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1565</th>\n",
       "      <td>2017-02-21</td>\n",
       "      <td>11.57</td>\n",
       "      <td>236.490005</td>\n",
       "      <td>-0.012543</td>\n",
       "      <td>-0.010219</td>\n",
       "      <td>-0.011381</td>\n",
       "      <td>13.190990</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1566</th>\n",
       "      <td>2017-02-22</td>\n",
       "      <td>11.74</td>\n",
       "      <td>236.279999</td>\n",
       "      <td>-0.004505</td>\n",
       "      <td>-0.002126</td>\n",
       "      <td>-0.003315</td>\n",
       "      <td>13.177525</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1567</th>\n",
       "      <td>2017-02-23</td>\n",
       "      <td>11.71</td>\n",
       "      <td>236.440002</td>\n",
       "      <td>-0.024664</td>\n",
       "      <td>-0.027845</td>\n",
       "      <td>-0.026255</td>\n",
       "      <td>13.170792</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date    VIX         SPY  Short Vol Ret  Long Vol Ret  L-S Port.  \\\n",
       "1563 2017-02-16  11.76  234.720001      -0.005169     -0.007594  -0.006382   \n",
       "1564 2017-02-17  11.49  235.089996      -0.002286     -0.001650  -0.001968   \n",
       "1565 2017-02-21  11.57  236.490005      -0.012543     -0.010219  -0.011381   \n",
       "1566 2017-02-22  11.74  236.279999      -0.004505     -0.002126  -0.003315   \n",
       "1567 2017-02-23  11.71  236.440002      -0.024664     -0.027845  -0.026255   \n",
       "\n",
       "      Moving Avg. VIX  Buy Column  L-S Mean Reversion  \n",
       "1563        13.227921         NaN                 NaN  \n",
       "1564        13.220000         NaN                 NaN  \n",
       "1565        13.190990         NaN                 NaN  \n",
       "1566        13.177525         NaN                 NaN  \n",
       "1567        13.170792         NaN                 NaN  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# excel 03_02\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "df_0302 = pd.read_excel('./03_02_Begin.xlsx', skip_footer=6)\n",
    "df_0302.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1568 entries, 0 to 1567\n",
      "Data columns (total 9 columns):\n",
      "Date                  1568 non-null datetime64[ns]\n",
      "VIX                   1568 non-null float64\n",
      "SPY                   1568 non-null float64\n",
      "Short Vol Ret         1568 non-null float64\n",
      "Long Vol Ret          1568 non-null float64\n",
      "L-S Port.             1568 non-null float64\n",
      "Moving Avg. VIX       1568 non-null float64\n",
      "Buy Column            0 non-null float64\n",
      "L-S Mean Reversion    0 non-null float64\n",
      "dtypes: datetime64[ns](1), float64(8)\n",
      "memory usage: 110.3 KB\n"
     ]
    }
   ],
   "source": [
    "df_0302.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>VIX</th>\n",
       "      <th>SPY</th>\n",
       "      <th>Short Vol Ret</th>\n",
       "      <th>Long Vol Ret</th>\n",
       "      <th>L-S Port.</th>\n",
       "      <th>Moving Avg. VIX</th>\n",
       "      <th>Buy Column</th>\n",
       "      <th>L-S Mean Reversion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-12-01</td>\n",
       "      <td>21.360001</td>\n",
       "      <td>106.369315</td>\n",
       "      <td>0.047474</td>\n",
       "      <td>0.024066</td>\n",
       "      <td>0.035770</td>\n",
       "      <td>21.360001</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-12-02</td>\n",
       "      <td>19.389999</td>\n",
       "      <td>107.731780</td>\n",
       "      <td>0.077529</td>\n",
       "      <td>0.065597</td>\n",
       "      <td>0.071563</td>\n",
       "      <td>20.375000</td>\n",
       "      <td>True</td>\n",
       "      <td>0.065597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-12-03</td>\n",
       "      <td>18.010000</td>\n",
       "      <td>108.021856</td>\n",
       "      <td>0.046410</td>\n",
       "      <td>0.058683</td>\n",
       "      <td>0.052546</td>\n",
       "      <td>19.586667</td>\n",
       "      <td>True</td>\n",
       "      <td>0.058683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-12-06</td>\n",
       "      <td>18.020000</td>\n",
       "      <td>107.907587</td>\n",
       "      <td>0.018160</td>\n",
       "      <td>0.019111</td>\n",
       "      <td>0.018635</td>\n",
       "      <td>19.195000</td>\n",
       "      <td>True</td>\n",
       "      <td>0.019111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-12-07</td>\n",
       "      <td>17.990000</td>\n",
       "      <td>107.969117</td>\n",
       "      <td>0.009864</td>\n",
       "      <td>0.009421</td>\n",
       "      <td>0.009642</td>\n",
       "      <td>18.954000</td>\n",
       "      <td>True</td>\n",
       "      <td>0.009421</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date        VIX         SPY  Short Vol Ret  Long Vol Ret  L-S Port.  \\\n",
       "0 2010-12-01  21.360001  106.369315       0.047474      0.024066   0.035770   \n",
       "1 2010-12-02  19.389999  107.731780       0.077529      0.065597   0.071563   \n",
       "2 2010-12-03  18.010000  108.021856       0.046410      0.058683   0.052546   \n",
       "3 2010-12-06  18.020000  107.907587       0.018160      0.019111   0.018635   \n",
       "4 2010-12-07  17.990000  107.969117       0.009864      0.009421   0.009642   \n",
       "\n",
       "   Moving Avg. VIX  Buy Column  L-S Mean Reversion  \n",
       "0        21.360001       False            0.000000  \n",
       "1        20.375000        True            0.065597  \n",
       "2        19.586667        True            0.058683  \n",
       "3        19.195000        True            0.019111  \n",
       "4        18.954000        True            0.009421  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_0302['Buy Column'] = df_0302['VIX'] < df_0302['Moving Avg. VIX'] \n",
    "df_0302['L-S Mean Reversion'] = df_0302['Buy Column'] * df_0302['Long Vol Ret'] \n",
    "df_0302.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_3543d1a8_992b_11ea_8136_a8206605054f\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >Short Vol Ret</th> \n",
       "        <th class=\"col_heading level0 col1\" >Long Vol Ret</th> \n",
       "        <th class=\"col_heading level0 col2\" >L-S Port.</th> \n",
       "        <th class=\"col_heading level0 col3\" >L-S Mean Reversion</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_3543d1a8_992b_11ea_8136_a8206605054flevel0_row0\" class=\"row_heading level0 row0\" >mean</th> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow0_col0\" class=\"data row0 col0\" >0.25%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow0_col1\" class=\"data row0 col1\" >0.21%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow0_col2\" class=\"data row0 col2\" >0.23%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow0_col3\" class=\"data row0 col3\" >0.60%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3543d1a8_992b_11ea_8136_a8206605054flevel0_row1\" class=\"row_heading level0 row1\" >std</th> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow1_col0\" class=\"data row1 col0\" >4.03%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow1_col1\" class=\"data row1 col1\" >4.04%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow1_col2\" class=\"data row1 col2\" >4.03%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow1_col3\" class=\"data row1 col3\" >2.40%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3543d1a8_992b_11ea_8136_a8206605054flevel0_row2\" class=\"row_heading level0 row2\" >min</th> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow2_col0\" class=\"data row2 col0\" >-23.66%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow2_col1\" class=\"data row2 col1\" >-26.79%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow2_col2\" class=\"data row2 col2\" >-25.22%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow2_col3\" class=\"data row2 col3\" >-9.81%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3543d1a8_992b_11ea_8136_a8206605054flevel0_row3\" class=\"row_heading level0 row3\" >5%</th> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow3_col0\" class=\"data row3 col0\" >-6.87%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow3_col1\" class=\"data row3 col1\" >-6.86%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow3_col2\" class=\"data row3 col2\" >-6.78%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow3_col3\" class=\"data row3 col3\" >-2.92%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3543d1a8_992b_11ea_8136_a8206605054flevel0_row4\" class=\"row_heading level0 row4\" >50%</th> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow4_col0\" class=\"data row4 col0\" >0.56%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow4_col1\" class=\"data row4 col1\" >0.52%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow4_col2\" class=\"data row4 col2\" >0.53%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow4_col3\" class=\"data row4 col3\" >0.00%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3543d1a8_992b_11ea_8136_a8206605054flevel0_row5\" class=\"row_heading level0 row5\" >95%</th> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow5_col0\" class=\"data row5 col0\" >6.37%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow5_col1\" class=\"data row5 col1\" >6.31%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow5_col2\" class=\"data row5 col2\" >6.34%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow5_col3\" class=\"data row5 col3\" >4.93%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3543d1a8_992b_11ea_8136_a8206605054flevel0_row6\" class=\"row_heading level0 row6\" >max</th> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow6_col0\" class=\"data row6 col0\" >13.28%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow6_col1\" class=\"data row6 col1\" >13.18%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow6_col2\" class=\"data row6 col2\" >13.23%</td> \n",
       "        <td id=\"T_3543d1a8_992b_11ea_8136_a8206605054frow6_col3\" class=\"data row6 col3\" >13.18%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x118a86cf8>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_0302.iloc[:,[3,4,5,8]].describe(percentiles=[.05, .95])[1:].style.format(\"{:.2%}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test algorithm accuracy\n",
    "e.g. 1990-2017 VIX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Stand Dev.</th>\n",
       "      <th>Moving Avg</th>\n",
       "      <th>Buy</th>\n",
       "      <th>1 Day Return</th>\n",
       "      <th>1 Day Long Only</th>\n",
       "      <th>1 Day Short Only</th>\n",
       "      <th>Big Buy</th>\n",
       "      <th>Big Buy Ret.</th>\n",
       "      <th>Big Buy Cap Used Ret</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6836</th>\n",
       "      <td>2017-02-16</td>\n",
       "      <td>12.02</td>\n",
       "      <td>12.86</td>\n",
       "      <td>11.69</td>\n",
       "      <td>11.76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.2373</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.017544</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6837</th>\n",
       "      <td>2017-02-17</td>\n",
       "      <td>11.84</td>\n",
       "      <td>12.26</td>\n",
       "      <td>11.37</td>\n",
       "      <td>11.49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.2072</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.022959</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6838</th>\n",
       "      <td>2017-02-21</td>\n",
       "      <td>12.05</td>\n",
       "      <td>12.09</td>\n",
       "      <td>11.50</td>\n",
       "      <td>11.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.1919</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.006963</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6839</th>\n",
       "      <td>2017-02-22</td>\n",
       "      <td>11.48</td>\n",
       "      <td>12.07</td>\n",
       "      <td>11.44</td>\n",
       "      <td>11.74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.1854</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.014693</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6840</th>\n",
       "      <td>2017-02-23</td>\n",
       "      <td>11.66</td>\n",
       "      <td>12.46</td>\n",
       "      <td>11.54</td>\n",
       "      <td>11.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.1623</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.002555</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date   Open   High    Low  Adj Close  Stand Dev.  Moving Avg  Buy  \\\n",
       "6836 2017-02-16  12.02  12.86  11.69      11.76         NaN     13.2373  1.0   \n",
       "6837 2017-02-17  11.84  12.26  11.37      11.49         NaN     13.2072  1.0   \n",
       "6838 2017-02-21  12.05  12.09  11.50      11.57         NaN     13.1919  1.0   \n",
       "6839 2017-02-22  11.48  12.07  11.44      11.74         NaN     13.1854  1.0   \n",
       "6840 2017-02-23  11.66  12.46  11.54      11.71         NaN     13.1623  1.0   \n",
       "\n",
       "      1 Day Return  1 Day Long Only  1 Day Short Only  Big Buy  Big Buy Ret.  \\\n",
       "6836     -0.017544              NaN               NaN      NaN           NaN   \n",
       "6837     -0.022959              NaN               NaN      NaN           NaN   \n",
       "6838      0.006963              NaN               NaN      NaN           NaN   \n",
       "6839      0.014693              NaN               NaN      NaN           NaN   \n",
       "6840     -0.002555              NaN               NaN      NaN           NaN   \n",
       "\n",
       "      Big Buy Cap Used Ret  \n",
       "6836                   NaN  \n",
       "6837                   NaN  \n",
       "6838                   NaN  \n",
       "6839                   NaN  \n",
       "6840                   NaN  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# excel 03_03\n",
    "df_0303 = pd.read_excel('./03_03_Begin.xlsx', skip_footer=3)\n",
    "df_0303.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6841 entries, 0 to 6840\n",
      "Data columns (total 14 columns):\n",
      "Date                    6841 non-null datetime64[ns]\n",
      "Open                    6841 non-null float64\n",
      "High                    6841 non-null float64\n",
      "Low                     6841 non-null float64\n",
      "Adj Close               6841 non-null float64\n",
      "Stand Dev.              0 non-null float64\n",
      "Moving Avg              6741 non-null float64\n",
      "Buy                     6741 non-null float64\n",
      "1 Day Return            6740 non-null float64\n",
      "1 Day Long Only         2 non-null float64\n",
      "1 Day Short Only        1 non-null float64\n",
      "Big Buy                 2 non-null float64\n",
      "Big Buy Ret.            1 non-null float64\n",
      "Big Buy Cap Used Ret    1 non-null float64\n",
      "dtypes: datetime64[ns](1), float64(13)\n",
      "memory usage: 748.3 KB\n"
     ]
    }
   ],
   "source": [
    "df_0303.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pd.DataFrame.set_index?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1195b91d0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KP2pT7dO16LViQkx7sJuNZ92r2HH5jag1kyLcqb2FqBZ6bW0tTz75JACqqnLe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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1194fd4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import style\n",
    "style.use('ggplot')\n",
    "df_0303.set_index(['Date']).iloc[:,1:6].plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Stand Dev.</th>\n",
       "      <th>Moving Avg</th>\n",
       "      <th>Buy</th>\n",
       "      <th>1 Day Return</th>\n",
       "      <th>1 Day Long Only</th>\n",
       "      <th>1 Day Short Only</th>\n",
       "      <th>Big Buy</th>\n",
       "      <th>Big Buy Ret.</th>\n",
       "      <th>Big Buy Cap Used Ret</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>1990-05-22</td>\n",
       "      <td>17.840000</td>\n",
       "      <td>17.840000</td>\n",
       "      <td>17.840000</td>\n",
       "      <td>17.840000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>1990-05-23</td>\n",
       "      <td>17.180000</td>\n",
       "      <td>17.180000</td>\n",
       "      <td>17.180000</td>\n",
       "      <td>17.180000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>1990-05-24</td>\n",
       "      <td>17.700001</td>\n",
       "      <td>17.700001</td>\n",
       "      <td>17.700001</td>\n",
       "      <td>17.700001</td>\n",
       "      <td>2.612414</td>\n",
       "      <td>21.3510</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>1990-05-25</td>\n",
       "      <td>17.320000</td>\n",
       "      <td>17.320000</td>\n",
       "      <td>17.320000</td>\n",
       "      <td>17.320000</td>\n",
       "      <td>2.605507</td>\n",
       "      <td>21.3423</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.021469</td>\n",
       "      <td>-0.021469</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>-0.021469</td>\n",
       "      <td>-0.021469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>1990-05-29</td>\n",
       "      <td>18.750000</td>\n",
       "      <td>18.750000</td>\n",
       "      <td>18.750000</td>\n",
       "      <td>18.750000</td>\n",
       "      <td>2.617592</td>\n",
       "      <td>21.3376</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.082564</td>\n",
       "      <td>0.082564</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.082564</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>1990-05-30</td>\n",
       "      <td>17.440001</td>\n",
       "      <td>17.440001</td>\n",
       "      <td>17.440001</td>\n",
       "      <td>17.440001</td>\n",
       "      <td>2.621860</td>\n",
       "      <td>21.3109</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.069867</td>\n",
       "      <td>-0.069867</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>1990-05-31</td>\n",
       "      <td>17.370001</td>\n",
       "      <td>17.370001</td>\n",
       "      <td>17.370001</td>\n",
       "      <td>17.370001</td>\n",
       "      <td>2.647953</td>\n",
       "      <td>21.2820</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.004014</td>\n",
       "      <td>-0.004014</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>-0.004014</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>1990-06-01</td>\n",
       "      <td>17.090000</td>\n",
       "      <td>17.090000</td>\n",
       "      <td>17.090000</td>\n",
       "      <td>17.090000</td>\n",
       "      <td>2.675169</td>\n",
       "      <td>21.2309</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.016120</td>\n",
       "      <td>-0.016120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>-0.016120</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>1990-06-04</td>\n",
       "      <td>18.389999</td>\n",
       "      <td>18.389999</td>\n",
       "      <td>18.389999</td>\n",
       "      <td>18.389999</td>\n",
       "      <td>2.706083</td>\n",
       "      <td>21.1904</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.076068</td>\n",
       "      <td>0.076068</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>0.076068</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>1990-06-05</td>\n",
       "      <td>18.969999</td>\n",
       "      <td>18.969999</td>\n",
       "      <td>18.969999</td>\n",
       "      <td>18.969999</td>\n",
       "      <td>2.718085</td>\n",
       "      <td>21.1796</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.031539</td>\n",
       "      <td>0.031539</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.031539</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date       Open       High        Low  Adj Close  Stand Dev.  \\\n",
       "98  1990-05-22  17.840000  17.840000  17.840000  17.840000         NaN   \n",
       "99  1990-05-23  17.180000  17.180000  17.180000  17.180000         NaN   \n",
       "100 1990-05-24  17.700001  17.700001  17.700001  17.700001    2.612414   \n",
       "101 1990-05-25  17.320000  17.320000  17.320000  17.320000    2.605507   \n",
       "102 1990-05-29  18.750000  18.750000  18.750000  18.750000    2.617592   \n",
       "103 1990-05-30  17.440001  17.440001  17.440001  17.440001    2.621860   \n",
       "104 1990-05-31  17.370001  17.370001  17.370001  17.370001    2.647953   \n",
       "105 1990-06-01  17.090000  17.090000  17.090000  17.090000    2.675169   \n",
       "106 1990-06-04  18.389999  18.389999  18.389999  18.389999    2.706083   \n",
       "107 1990-06-05  18.969999  18.969999  18.969999  18.969999    2.718085   \n",
       "\n",
       "     Moving Avg  Buy  1 Day Return  1 Day Long Only  1 Day Short Only  \\\n",
       "98          NaN  NaN           NaN              NaN               NaN   \n",
       "99          NaN  NaN           NaN              NaN               NaN   \n",
       "100     21.3510  1.0           NaN              NaN               NaN   \n",
       "101     21.3423  1.0     -0.021469        -0.021469               0.0   \n",
       "102     21.3376  1.0      0.082564         0.082564              -0.0   \n",
       "103     21.3109  1.0     -0.069867        -0.069867               0.0   \n",
       "104     21.2820  1.0     -0.004014        -0.004014               0.0   \n",
       "105     21.2309  1.0     -0.016120        -0.016120               0.0   \n",
       "106     21.1904  1.0      0.076068         0.076068              -0.0   \n",
       "107     21.1796  1.0      0.031539         0.031539              -0.0   \n",
       "\n",
       "     Big Buy  Big Buy Ret.  Big Buy Cap Used Ret  \n",
       "98     False           NaN                   NaN  \n",
       "99     False           NaN                   NaN  \n",
       "100     True           NaN                   NaN  \n",
       "101     True     -0.021469             -0.021469  \n",
       "102    False      0.082564                   NaN  \n",
       "103     True     -0.000000                   NaN  \n",
       "104     True     -0.004014                   NaN  \n",
       "105     True     -0.016120                   NaN  \n",
       "106     True      0.076068                   NaN  \n",
       "107    False      0.031539                   NaN  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_0303['Stand Dev.'] = df_0303['Adj Close'].rolling(100).std().shift(1)\n",
    "df_0303['Big Buy'] = df_0303['Adj Close'] + df_0303['Stand Dev.'] < df_0303['Moving Avg']\n",
    "df_0303['Big Buy Ret.'] = (df_0303['Big Buy'].shift(1) * df_0303['1 Day Return']).astype('float')\n",
    "df_0303[98:].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algorithm profitability and trading decisions\n",
    "e.g."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
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       "      <th>Stand Dev.</th>\n",
       "      <th>Moving Avg</th>\n",
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       "      <th>Big Buy</th>\n",
       "      <th>Big Buy Ret.</th>\n",
       "      <th>Big Buy Cap Used Ret</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6831</th>\n",
       "      <td>2017-02-09</td>\n",
       "      <td>11.44</td>\n",
       "      <td>11.53</td>\n",
       "      <td>10.74</td>\n",
       "      <td>10.88</td>\n",
       "      <td>2.253511</td>\n",
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       "      <th>6832</th>\n",
       "      <td>2017-02-10</td>\n",
       "      <td>10.85</td>\n",
       "      <td>10.95</td>\n",
       "      <td>10.55</td>\n",
       "      <td>10.85</td>\n",
       "      <td>2.258767</td>\n",
       "      <td>13.3172</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6833</th>\n",
       "      <td>2017-02-13</td>\n",
       "      <td>11.36</td>\n",
       "      <td>11.40</td>\n",
       "      <td>11.07</td>\n",
       "      <td>11.07</td>\n",
       "      <td>2.261917</td>\n",
       "      <td>13.2687</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.020276</td>\n",
       "      <td>0.020276</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.020276</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6834</th>\n",
       "      <td>2017-02-14</td>\n",
       "      <td>11.17</td>\n",
       "      <td>11.34</td>\n",
       "      <td>10.73</td>\n",
       "      <td>10.74</td>\n",
       "      <td>2.257536</td>\n",
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       "      <td>-0.029810</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6835</th>\n",
       "      <td>2017-02-15</td>\n",
       "      <td>10.84</td>\n",
       "      <td>12.01</td>\n",
       "      <td>10.80</td>\n",
       "      <td>11.97</td>\n",
       "      <td>2.271649</td>\n",
       "      <td>13.2426</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.114525</td>\n",
       "      <td>0.114525</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.114525</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6836</th>\n",
       "      <td>2017-02-16</td>\n",
       "      <td>12.02</td>\n",
       "      <td>12.86</td>\n",
       "      <td>11.69</td>\n",
       "      <td>11.76</td>\n",
       "      <td>2.271926</td>\n",
       "      <td>13.2373</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.017544</td>\n",
       "      <td>-0.017544</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6837</th>\n",
       "      <td>2017-02-17</td>\n",
       "      <td>11.84</td>\n",
       "      <td>12.26</td>\n",
       "      <td>11.37</td>\n",
       "      <td>11.49</td>\n",
       "      <td>2.274787</td>\n",
       "      <td>13.2072</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.022959</td>\n",
       "      <td>-0.022959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6838</th>\n",
       "      <td>2017-02-21</td>\n",
       "      <td>12.05</td>\n",
       "      <td>12.09</td>\n",
       "      <td>11.50</td>\n",
       "      <td>11.57</td>\n",
       "      <td>2.277822</td>\n",
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       "    <tr>\n",
       "      <th>6839</th>\n",
       "      <td>2017-02-22</td>\n",
       "      <td>11.48</td>\n",
       "      <td>12.07</td>\n",
       "      <td>11.44</td>\n",
       "      <td>11.74</td>\n",
       "      <td>2.283681</td>\n",
       "      <td>13.1854</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.014693</td>\n",
       "      <td>0.014693</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6840</th>\n",
       "      <td>2017-02-23</td>\n",
       "      <td>11.66</td>\n",
       "      <td>12.46</td>\n",
       "      <td>11.54</td>\n",
       "      <td>11.71</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date   Open   High    Low  Adj Close  Stand Dev.  Moving Avg  Buy  \\\n",
       "6831 2017-02-09  11.44  11.53  10.74      10.88    2.253511     13.3640  1.0   \n",
       "6832 2017-02-10  10.85  10.95  10.55      10.85    2.258767     13.3172  1.0   \n",
       "6833 2017-02-13  11.36  11.40  11.07      11.07    2.261917     13.2687  1.0   \n",
       "6834 2017-02-14  11.17  11.34  10.73      10.74    2.257536     13.2431  1.0   \n",
       "6835 2017-02-15  10.84  12.01  10.80      11.97    2.271649     13.2426  1.0   \n",
       "6836 2017-02-16  12.02  12.86  11.69      11.76    2.271926     13.2373  1.0   \n",
       "6837 2017-02-17  11.84  12.26  11.37      11.49    2.274787     13.2072  1.0   \n",
       "6838 2017-02-21  12.05  12.09  11.50      11.57    2.277822     13.1919  1.0   \n",
       "6839 2017-02-22  11.48  12.07  11.44      11.74    2.283681     13.1854  1.0   \n",
       "6840 2017-02-23  11.66  12.46  11.54      11.71    2.286909     13.1623  1.0   \n",
       "\n",
       "      1 Day Return  1 Day Long Only  1 Day Short Only  Big Buy  Big Buy Ret.  \\\n",
       "6831     -0.049782        -0.049782               0.0     True     -0.000000   \n",
       "6832     -0.002757        -0.002757               0.0     True     -0.002757   \n",
       "6833      0.020276         0.020276              -0.0    False      0.020276   \n",
       "6834     -0.029810        -0.029810               0.0     True     -0.000000   \n",
       "6835      0.114525         0.114525              -0.0    False      0.114525   \n",
       "6836     -0.017544        -0.017544               0.0    False     -0.000000   \n",
       "6837     -0.022959        -0.022959               0.0    False     -0.000000   \n",
       "6838      0.006963         0.006963              -0.0    False      0.000000   \n",
       "6839      0.014693         0.014693              -0.0    False      0.000000   \n",
       "6840     -0.002555        -0.002555               0.0    False     -0.000000   \n",
       "\n",
       "      Big Buy Cap Used Ret  \n",
       "6831                   NaN  \n",
       "6832                   NaN  \n",
       "6833                   NaN  \n",
       "6834                   NaN  \n",
       "6835                   NaN  \n",
       "6836                   NaN  \n",
       "6837                   NaN  \n",
       "6838                   NaN  \n",
       "6839                   NaN  \n",
       "6840                   NaN  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_0304 = df_0303\n",
    "df_0304.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Adj Close</th>\n",
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       "      <th>1 Day Return</th>\n",
       "      <th>1 Day Long Only</th>\n",
       "      <th>1 Day Short Only</th>\n",
       "      <th>Big Buy</th>\n",
       "      <th>Big Buy Ret.</th>\n",
       "      <th>Big Buy Cap Used Ret</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6831</th>\n",
       "      <td>2017-02-09</td>\n",
       "      <td>11.44</td>\n",
       "      <td>11.53</td>\n",
       "      <td>10.74</td>\n",
       "      <td>10.88</td>\n",
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       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6832</th>\n",
       "      <td>2017-02-10</td>\n",
       "      <td>10.85</td>\n",
       "      <td>10.95</td>\n",
       "      <td>10.55</td>\n",
       "      <td>10.85</td>\n",
       "      <td>2.258767</td>\n",
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       "      <td>-0.002757</td>\n",
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       "    <tr>\n",
       "      <th>6833</th>\n",
       "      <td>2017-02-13</td>\n",
       "      <td>11.36</td>\n",
       "      <td>11.40</td>\n",
       "      <td>11.07</td>\n",
       "      <td>11.07</td>\n",
       "      <td>2.261917</td>\n",
       "      <td>13.2687</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.020276</td>\n",
       "      <td>0.020276</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.020276</td>\n",
       "      <td>0.020276</td>\n",
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       "    <tr>\n",
       "      <th>6834</th>\n",
       "      <td>2017-02-14</td>\n",
       "      <td>11.17</td>\n",
       "      <td>11.34</td>\n",
       "      <td>10.73</td>\n",
       "      <td>10.74</td>\n",
       "      <td>2.257536</td>\n",
       "      <td>13.2431</td>\n",
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       "      <td>-0.029810</td>\n",
       "      <td>-0.029810</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6835</th>\n",
       "      <td>2017-02-15</td>\n",
       "      <td>10.84</td>\n",
       "      <td>12.01</td>\n",
       "      <td>10.80</td>\n",
       "      <td>11.97</td>\n",
       "      <td>2.271649</td>\n",
       "      <td>13.2426</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.114525</td>\n",
       "      <td>0.114525</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.114525</td>\n",
       "      <td>0.114525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6836</th>\n",
       "      <td>2017-02-16</td>\n",
       "      <td>12.02</td>\n",
       "      <td>12.86</td>\n",
       "      <td>11.69</td>\n",
       "      <td>11.76</td>\n",
       "      <td>2.271926</td>\n",
       "      <td>13.2373</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.017544</td>\n",
       "      <td>-0.017544</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6837</th>\n",
       "      <td>2017-02-17</td>\n",
       "      <td>11.84</td>\n",
       "      <td>12.26</td>\n",
       "      <td>11.37</td>\n",
       "      <td>11.49</td>\n",
       "      <td>2.274787</td>\n",
       "      <td>13.2072</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.022959</td>\n",
       "      <td>-0.022959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6838</th>\n",
       "      <td>2017-02-21</td>\n",
       "      <td>12.05</td>\n",
       "      <td>12.09</td>\n",
       "      <td>11.50</td>\n",
       "      <td>11.57</td>\n",
       "      <td>2.277822</td>\n",
       "      <td>13.1919</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>0.006963</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6839</th>\n",
       "      <td>2017-02-22</td>\n",
       "      <td>11.48</td>\n",
       "      <td>12.07</td>\n",
       "      <td>11.44</td>\n",
       "      <td>11.74</td>\n",
       "      <td>2.283681</td>\n",
       "      <td>13.1854</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.014693</td>\n",
       "      <td>0.014693</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6840</th>\n",
       "      <td>2017-02-23</td>\n",
       "      <td>11.66</td>\n",
       "      <td>12.46</td>\n",
       "      <td>11.54</td>\n",
       "      <td>11.71</td>\n",
       "      <td>2.286909</td>\n",
       "      <td>13.1623</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.002555</td>\n",
       "      <td>-0.002555</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date   Open   High    Low  Adj Close  Stand Dev.  Moving Avg  Buy  \\\n",
       "6831 2017-02-09  11.44  11.53  10.74      10.88    2.253511     13.3640  1.0   \n",
       "6832 2017-02-10  10.85  10.95  10.55      10.85    2.258767     13.3172  1.0   \n",
       "6833 2017-02-13  11.36  11.40  11.07      11.07    2.261917     13.2687  1.0   \n",
       "6834 2017-02-14  11.17  11.34  10.73      10.74    2.257536     13.2431  1.0   \n",
       "6835 2017-02-15  10.84  12.01  10.80      11.97    2.271649     13.2426  1.0   \n",
       "6836 2017-02-16  12.02  12.86  11.69      11.76    2.271926     13.2373  1.0   \n",
       "6837 2017-02-17  11.84  12.26  11.37      11.49    2.274787     13.2072  1.0   \n",
       "6838 2017-02-21  12.05  12.09  11.50      11.57    2.277822     13.1919  1.0   \n",
       "6839 2017-02-22  11.48  12.07  11.44      11.74    2.283681     13.1854  1.0   \n",
       "6840 2017-02-23  11.66  12.46  11.54      11.71    2.286909     13.1623  1.0   \n",
       "\n",
       "      1 Day Return  1 Day Long Only  1 Day Short Only  Big Buy  Big Buy Ret.  \\\n",
       "6831     -0.049782        -0.049782               0.0     True     -0.000000   \n",
       "6832     -0.002757        -0.002757               0.0     True     -0.002757   \n",
       "6833      0.020276         0.020276              -0.0    False      0.020276   \n",
       "6834     -0.029810        -0.029810               0.0     True     -0.000000   \n",
       "6835      0.114525         0.114525              -0.0    False      0.114525   \n",
       "6836     -0.017544        -0.017544               0.0    False     -0.000000   \n",
       "6837     -0.022959        -0.022959               0.0    False     -0.000000   \n",
       "6838      0.006963         0.006963              -0.0    False      0.000000   \n",
       "6839      0.014693         0.014693              -0.0    False      0.000000   \n",
       "6840     -0.002555        -0.002555               0.0    False     -0.000000   \n",
       "\n",
       "      Big Buy Cap Used Ret  \n",
       "6831                   NaN  \n",
       "6832             -0.002757  \n",
       "6833              0.020276  \n",
       "6834                   NaN  \n",
       "6835              0.114525  \n",
       "6836                   NaN  \n",
       "6837                   NaN  \n",
       "6838                   NaN  \n",
       "6839                   NaN  \n",
       "6840                   NaN  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_0304['1 Day Long Only'] = df_0304['Buy'] * df_0304['1 Day Return']\n",
    "df_0304['1 Day Short Only'] = (df_0304['Buy'] == False) * -df_0304['1 Day Return']\n",
    "df_0304['Big Buy Cap Used Ret'] = df_0304['Big Buy Ret.'].apply(lambda x: x if x != 0 else None) \n",
    "df_0304.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Open                    19.698297\n",
       "High                    20.413364\n",
       "Low                     19.025005\n",
       "Adj Close               19.632292\n",
       "Stand Dev.               3.060204\n",
       "Moving Avg              19.666610\n",
       "Buy                      0.599021\n",
       "1 Day Return             0.005619\n",
       "1 Day Long Only          0.002576\n",
       "1 Day Short Only        -0.003043\n",
       "Big Buy                  0.242070\n",
       "Big Buy Ret.             0.002903\n",
       "Big Buy Cap Used Ret     0.011907\n",
       "dtype: float64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_0304.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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