{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from trader_factory import build_active_trader_IB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IBridgePy.IbridgepyTools import symbol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = build_active_trader_IB('DU1868499')  # Build an active trader to get connected to Interactive Brokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist = t.request_historical_data(symbol('SPY'), '1 day', '1 Y')  # Get historical data. Return is a pandas.DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-12-17</th>\n",
       "      <td>319.92</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.48</td>\n",
       "      <td>319.57</td>\n",
       "      <td>290316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-18</th>\n",
       "      <td>320.01</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.53</td>\n",
       "      <td>319.59</td>\n",
       "      <td>276219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-19</th>\n",
       "      <td>319.79</td>\n",
       "      <td>320.98</td>\n",
       "      <td>319.75</td>\n",
       "      <td>320.90</td>\n",
       "      <td>344693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-20</th>\n",
       "      <td>320.46</td>\n",
       "      <td>321.45</td>\n",
       "      <td>320.37</td>\n",
       "      <td>320.73</td>\n",
       "      <td>521812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23</th>\n",
       "      <td>321.59</td>\n",
       "      <td>321.65</td>\n",
       "      <td>321.06</td>\n",
       "      <td>321.22</td>\n",
       "      <td>257147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-09</th>\n",
       "      <td>370.88</td>\n",
       "      <td>371.05</td>\n",
       "      <td>365.95</td>\n",
       "      <td>366.85</td>\n",
       "      <td>499276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-10</th>\n",
       "      <td>365.37</td>\n",
       "      <td>367.86</td>\n",
       "      <td>364.43</td>\n",
       "      <td>366.73</td>\n",
       "      <td>344586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-11</th>\n",
       "      <td>364.90</td>\n",
       "      <td>366.58</td>\n",
       "      <td>363.26</td>\n",
       "      <td>366.30</td>\n",
       "      <td>365387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-14</th>\n",
       "      <td>368.62</td>\n",
       "      <td>369.80</td>\n",
       "      <td>364.47</td>\n",
       "      <td>364.66</td>\n",
       "      <td>437356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-15</th>\n",
       "      <td>367.40</td>\n",
       "      <td>369.59</td>\n",
       "      <td>365.92</td>\n",
       "      <td>369.59</td>\n",
       "      <td>348842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low   close  volume\n",
       "2019-12-17  319.92  320.25  319.48  319.57  290316\n",
       "2019-12-18  320.01  320.25  319.53  319.59  276219\n",
       "2019-12-19  319.79  320.98  319.75  320.90  344693\n",
       "2019-12-20  320.46  321.45  320.37  320.73  521812\n",
       "2019-12-23  321.59  321.65  321.06  321.22  257147\n",
       "...            ...     ...     ...     ...     ...\n",
       "2020-12-09  370.88  371.05  365.95  366.85  499276\n",
       "2020-12-10  365.37  367.86  364.43  366.73  344586\n",
       "2020-12-11  364.90  366.58  363.26  366.30  365387\n",
       "2020-12-14  368.62  369.80  364.47  364.66  437356\n",
       "2020-12-15  367.40  369.59  365.92  369.59  348842\n",
       "\n",
       "[252 rows x 5 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist  # print hist to show it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['open', 'high', 'low', 'close', 'volume'], dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist.columns  # print column names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([2019-12-17, 2019-12-18, 2019-12-19, 2019-12-20, 2019-12-23, 2019-12-24,\n",
       "       2019-12-26, 2019-12-27, 2019-12-30, 2019-12-31,\n",
       "       ...\n",
       "       2020-12-02, 2020-12-03, 2020-12-04, 2020-12-07, 2020-12-08, 2020-12-09,\n",
       "       2020-12-10, 2020-12-11, 2020-12-14, 2020-12-15],\n",
       "      dtype='object', length=252)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist.index  # print index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2019-12-17    319.92\n",
       "2019-12-18    320.01\n",
       "2019-12-19    319.79\n",
       "2019-12-20    320.46\n",
       "2019-12-23    321.59\n",
       "               ...  \n",
       "2020-12-09    370.88\n",
       "2020-12-10    365.37\n",
       "2020-12-11    364.90\n",
       "2020-12-14    368.62\n",
       "2020-12-15    367.40\n",
       "Name: open, Length: 252, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist['open']  # print out a column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "open         319.92\n",
       "high         320.25\n",
       "low          319.48\n",
       "close        319.57\n",
       "volume    290316.00\n",
       "Name: 2019-12-17, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist.iloc[0]  # print out 1st row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "open         367.40\n",
       "high         369.59\n",
       "low          365.92\n",
       "close        369.59\n",
       "volume    348842.00\n",
       "Name: 2020-12-15, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist.iloc[-1]  # print out the last row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "319.92"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist.iloc[0]['open']  # print out open price of the 1st row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(hist.index[-1])  # print out the data type of index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "open         367.40\n",
       "high         369.59\n",
       "low          365.92\n",
       "close        369.59\n",
       "volume    348842.00\n",
       "Name: 2020-12-15, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import datetime as dt\n",
    "hist.loc[dt.date(2020,12,15)]  # print out the prices of Dec 15th 2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist['close_yesterday'] = hist['close'].shift(1)  # add a new column, call it \"close_yesterday\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>close_yesterday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-12-17</th>\n",
       "      <td>319.92</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.48</td>\n",
       "      <td>319.57</td>\n",
       "      <td>290316</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-18</th>\n",
       "      <td>320.01</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.53</td>\n",
       "      <td>319.59</td>\n",
       "      <td>276219</td>\n",
       "      <td>319.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-19</th>\n",
       "      <td>319.79</td>\n",
       "      <td>320.98</td>\n",
       "      <td>319.75</td>\n",
       "      <td>320.90</td>\n",
       "      <td>344693</td>\n",
       "      <td>319.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-20</th>\n",
       "      <td>320.46</td>\n",
       "      <td>321.45</td>\n",
       "      <td>320.37</td>\n",
       "      <td>320.73</td>\n",
       "      <td>521812</td>\n",
       "      <td>320.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23</th>\n",
       "      <td>321.59</td>\n",
       "      <td>321.65</td>\n",
       "      <td>321.06</td>\n",
       "      <td>321.22</td>\n",
       "      <td>257147</td>\n",
       "      <td>320.73</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>2020-12-09</th>\n",
       "      <td>370.88</td>\n",
       "      <td>371.05</td>\n",
       "      <td>365.95</td>\n",
       "      <td>366.85</td>\n",
       "      <td>499276</td>\n",
       "      <td>370.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-10</th>\n",
       "      <td>365.37</td>\n",
       "      <td>367.86</td>\n",
       "      <td>364.43</td>\n",
       "      <td>366.73</td>\n",
       "      <td>344586</td>\n",
       "      <td>366.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-11</th>\n",
       "      <td>364.90</td>\n",
       "      <td>366.58</td>\n",
       "      <td>363.26</td>\n",
       "      <td>366.30</td>\n",
       "      <td>365387</td>\n",
       "      <td>366.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-14</th>\n",
       "      <td>368.62</td>\n",
       "      <td>369.80</td>\n",
       "      <td>364.47</td>\n",
       "      <td>364.66</td>\n",
       "      <td>437356</td>\n",
       "      <td>366.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-15</th>\n",
       "      <td>367.40</td>\n",
       "      <td>369.59</td>\n",
       "      <td>365.92</td>\n",
       "      <td>369.59</td>\n",
       "      <td>348842</td>\n",
       "      <td>364.66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low   close  volume  close_yesterday\n",
       "2019-12-17  319.92  320.25  319.48  319.57  290316              NaN\n",
       "2019-12-18  320.01  320.25  319.53  319.59  276219           319.57\n",
       "2019-12-19  319.79  320.98  319.75  320.90  344693           319.59\n",
       "2019-12-20  320.46  321.45  320.37  320.73  521812           320.90\n",
       "2019-12-23  321.59  321.65  321.06  321.22  257147           320.73\n",
       "...            ...     ...     ...     ...     ...              ...\n",
       "2020-12-09  370.88  371.05  365.95  366.85  499276           370.17\n",
       "2020-12-10  365.37  367.86  364.43  366.73  344586           366.85\n",
       "2020-12-11  364.90  366.58  363.26  366.30  365387           366.73\n",
       "2020-12-14  368.62  369.80  364.47  364.66  437356           366.30\n",
       "2020-12-15  367.40  369.59  365.92  369.59  348842           364.66\n",
       "\n",
       "[252 rows x 6 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist['yield_yesterday'] = (hist['close'] - hist['close_yesterday']) / hist['close_yesterday']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>close_yesterday</th>\n",
       "      <th>yield_yesterday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-12-17</th>\n",
       "      <td>319.92</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.48</td>\n",
       "      <td>319.57</td>\n",
       "      <td>290316</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-18</th>\n",
       "      <td>320.01</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.53</td>\n",
       "      <td>319.59</td>\n",
       "      <td>276219</td>\n",
       "      <td>319.57</td>\n",
       "      <td>0.000063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-19</th>\n",
       "      <td>319.79</td>\n",
       "      <td>320.98</td>\n",
       "      <td>319.75</td>\n",
       "      <td>320.90</td>\n",
       "      <td>344693</td>\n",
       "      <td>319.59</td>\n",
       "      <td>0.004099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-20</th>\n",
       "      <td>320.46</td>\n",
       "      <td>321.45</td>\n",
       "      <td>320.37</td>\n",
       "      <td>320.73</td>\n",
       "      <td>521812</td>\n",
       "      <td>320.90</td>\n",
       "      <td>-0.000530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23</th>\n",
       "      <td>321.59</td>\n",
       "      <td>321.65</td>\n",
       "      <td>321.06</td>\n",
       "      <td>321.22</td>\n",
       "      <td>257147</td>\n",
       "      <td>320.73</td>\n",
       "      <td>0.001528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-09</th>\n",
       "      <td>370.88</td>\n",
       "      <td>371.05</td>\n",
       "      <td>365.95</td>\n",
       "      <td>366.85</td>\n",
       "      <td>499276</td>\n",
       "      <td>370.17</td>\n",
       "      <td>-0.008969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-10</th>\n",
       "      <td>365.37</td>\n",
       "      <td>367.86</td>\n",
       "      <td>364.43</td>\n",
       "      <td>366.73</td>\n",
       "      <td>344586</td>\n",
       "      <td>366.85</td>\n",
       "      <td>-0.000327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-11</th>\n",
       "      <td>364.90</td>\n",
       "      <td>366.58</td>\n",
       "      <td>363.26</td>\n",
       "      <td>366.30</td>\n",
       "      <td>365387</td>\n",
       "      <td>366.73</td>\n",
       "      <td>-0.001173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-14</th>\n",
       "      <td>368.62</td>\n",
       "      <td>369.80</td>\n",
       "      <td>364.47</td>\n",
       "      <td>364.66</td>\n",
       "      <td>437356</td>\n",
       "      <td>366.30</td>\n",
       "      <td>-0.004477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-15</th>\n",
       "      <td>367.40</td>\n",
       "      <td>369.59</td>\n",
       "      <td>365.92</td>\n",
       "      <td>369.59</td>\n",
       "      <td>348842</td>\n",
       "      <td>364.66</td>\n",
       "      <td>0.013519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low   close  volume  close_yesterday  \\\n",
       "2019-12-17  319.92  320.25  319.48  319.57  290316              NaN   \n",
       "2019-12-18  320.01  320.25  319.53  319.59  276219           319.57   \n",
       "2019-12-19  319.79  320.98  319.75  320.90  344693           319.59   \n",
       "2019-12-20  320.46  321.45  320.37  320.73  521812           320.90   \n",
       "2019-12-23  321.59  321.65  321.06  321.22  257147           320.73   \n",
       "...            ...     ...     ...     ...     ...              ...   \n",
       "2020-12-09  370.88  371.05  365.95  366.85  499276           370.17   \n",
       "2020-12-10  365.37  367.86  364.43  366.73  344586           366.85   \n",
       "2020-12-11  364.90  366.58  363.26  366.30  365387           366.73   \n",
       "2020-12-14  368.62  369.80  364.47  364.66  437356           366.30   \n",
       "2020-12-15  367.40  369.59  365.92  369.59  348842           364.66   \n",
       "\n",
       "            yield_yesterday  \n",
       "2019-12-17              NaN  \n",
       "2019-12-18         0.000063  \n",
       "2019-12-19         0.004099  \n",
       "2019-12-20        -0.000530  \n",
       "2019-12-23         0.001528  \n",
       "...                     ...  \n",
       "2020-12-09        -0.008969  \n",
       "2020-12-10        -0.000327  \n",
       "2020-12-11        -0.001173  \n",
       "2020-12-14        -0.004477  \n",
       "2020-12-15         0.013519  \n",
       "\n",
       "[252 rows x 7 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist['yield_tomorrow'] = hist['yield_yesterday'].shift(-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>close_yesterday</th>\n",
       "      <th>yield_yesterday</th>\n",
       "      <th>yield_tomorrow</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-12-17</th>\n",
       "      <td>319.92</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.48</td>\n",
       "      <td>319.57</td>\n",
       "      <td>290316</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-18</th>\n",
       "      <td>320.01</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.53</td>\n",
       "      <td>319.59</td>\n",
       "      <td>276219</td>\n",
       "      <td>319.57</td>\n",
       "      <td>0.000063</td>\n",
       "      <td>0.004099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-19</th>\n",
       "      <td>319.79</td>\n",
       "      <td>320.98</td>\n",
       "      <td>319.75</td>\n",
       "      <td>320.90</td>\n",
       "      <td>344693</td>\n",
       "      <td>319.59</td>\n",
       "      <td>0.004099</td>\n",
       "      <td>-0.000530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-20</th>\n",
       "      <td>320.46</td>\n",
       "      <td>321.45</td>\n",
       "      <td>320.37</td>\n",
       "      <td>320.73</td>\n",
       "      <td>521812</td>\n",
       "      <td>320.90</td>\n",
       "      <td>-0.000530</td>\n",
       "      <td>0.001528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23</th>\n",
       "      <td>321.59</td>\n",
       "      <td>321.65</td>\n",
       "      <td>321.06</td>\n",
       "      <td>321.22</td>\n",
       "      <td>257147</td>\n",
       "      <td>320.73</td>\n",
       "      <td>0.001528</td>\n",
       "      <td>0.000031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-09</th>\n",
       "      <td>370.88</td>\n",
       "      <td>371.05</td>\n",
       "      <td>365.95</td>\n",
       "      <td>366.85</td>\n",
       "      <td>499276</td>\n",
       "      <td>370.17</td>\n",
       "      <td>-0.008969</td>\n",
       "      <td>-0.000327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-10</th>\n",
       "      <td>365.37</td>\n",
       "      <td>367.86</td>\n",
       "      <td>364.43</td>\n",
       "      <td>366.73</td>\n",
       "      <td>344586</td>\n",
       "      <td>366.85</td>\n",
       "      <td>-0.000327</td>\n",
       "      <td>-0.001173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-11</th>\n",
       "      <td>364.90</td>\n",
       "      <td>366.58</td>\n",
       "      <td>363.26</td>\n",
       "      <td>366.30</td>\n",
       "      <td>365387</td>\n",
       "      <td>366.73</td>\n",
       "      <td>-0.001173</td>\n",
       "      <td>-0.004477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-14</th>\n",
       "      <td>368.62</td>\n",
       "      <td>369.80</td>\n",
       "      <td>364.47</td>\n",
       "      <td>364.66</td>\n",
       "      <td>437356</td>\n",
       "      <td>366.30</td>\n",
       "      <td>-0.004477</td>\n",
       "      <td>0.013519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-15</th>\n",
       "      <td>367.40</td>\n",
       "      <td>369.59</td>\n",
       "      <td>365.92</td>\n",
       "      <td>369.59</td>\n",
       "      <td>348842</td>\n",
       "      <td>364.66</td>\n",
       "      <td>0.013519</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low   close  volume  close_yesterday  \\\n",
       "2019-12-17  319.92  320.25  319.48  319.57  290316              NaN   \n",
       "2019-12-18  320.01  320.25  319.53  319.59  276219           319.57   \n",
       "2019-12-19  319.79  320.98  319.75  320.90  344693           319.59   \n",
       "2019-12-20  320.46  321.45  320.37  320.73  521812           320.90   \n",
       "2019-12-23  321.59  321.65  321.06  321.22  257147           320.73   \n",
       "...            ...     ...     ...     ...     ...              ...   \n",
       "2020-12-09  370.88  371.05  365.95  366.85  499276           370.17   \n",
       "2020-12-10  365.37  367.86  364.43  366.73  344586           366.85   \n",
       "2020-12-11  364.90  366.58  363.26  366.30  365387           366.73   \n",
       "2020-12-14  368.62  369.80  364.47  364.66  437356           366.30   \n",
       "2020-12-15  367.40  369.59  365.92  369.59  348842           364.66   \n",
       "\n",
       "            yield_yesterday  yield_tomorrow  \n",
       "2019-12-17              NaN        0.000063  \n",
       "2019-12-18         0.000063        0.004099  \n",
       "2019-12-19         0.004099       -0.000530  \n",
       "2019-12-20        -0.000530        0.001528  \n",
       "2019-12-23         0.001528        0.000031  \n",
       "...                     ...             ...  \n",
       "2020-12-09        -0.008969       -0.000327  \n",
       "2020-12-10        -0.000327       -0.001173  \n",
       "2020-12-11        -0.001173       -0.004477  \n",
       "2020-12-14        -0.004477        0.013519  \n",
       "2020-12-15         0.013519             NaN  \n",
       "\n",
       "[252 rows x 8 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>close_yesterday</th>\n",
       "      <th>yield_yesterday</th>\n",
       "      <th>yield_tomorrow</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-12-18</th>\n",
       "      <td>320.01</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.53</td>\n",
       "      <td>319.59</td>\n",
       "      <td>276219</td>\n",
       "      <td>319.57</td>\n",
       "      <td>0.000063</td>\n",
       "      <td>0.004099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-19</th>\n",
       "      <td>319.79</td>\n",
       "      <td>320.98</td>\n",
       "      <td>319.75</td>\n",
       "      <td>320.90</td>\n",
       "      <td>344693</td>\n",
       "      <td>319.59</td>\n",
       "      <td>0.004099</td>\n",
       "      <td>-0.000530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-20</th>\n",
       "      <td>320.46</td>\n",
       "      <td>321.45</td>\n",
       "      <td>320.37</td>\n",
       "      <td>320.73</td>\n",
       "      <td>521812</td>\n",
       "      <td>320.90</td>\n",
       "      <td>-0.000530</td>\n",
       "      <td>0.001528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23</th>\n",
       "      <td>321.59</td>\n",
       "      <td>321.65</td>\n",
       "      <td>321.06</td>\n",
       "      <td>321.22</td>\n",
       "      <td>257147</td>\n",
       "      <td>320.73</td>\n",
       "      <td>0.001528</td>\n",
       "      <td>0.000031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-24</th>\n",
       "      <td>321.47</td>\n",
       "      <td>321.52</td>\n",
       "      <td>320.90</td>\n",
       "      <td>321.23</td>\n",
       "      <td>122217</td>\n",
       "      <td>321.22</td>\n",
       "      <td>0.000031</td>\n",
       "      <td>0.005323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-08</th>\n",
       "      <td>367.69</td>\n",
       "      <td>370.78</td>\n",
       "      <td>367.67</td>\n",
       "      <td>370.17</td>\n",
       "      <td>269841</td>\n",
       "      <td>369.09</td>\n",
       "      <td>0.002926</td>\n",
       "      <td>-0.008969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-09</th>\n",
       "      <td>370.88</td>\n",
       "      <td>371.05</td>\n",
       "      <td>365.95</td>\n",
       "      <td>366.85</td>\n",
       "      <td>499276</td>\n",
       "      <td>370.17</td>\n",
       "      <td>-0.008969</td>\n",
       "      <td>-0.000327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-10</th>\n",
       "      <td>365.37</td>\n",
       "      <td>367.86</td>\n",
       "      <td>364.43</td>\n",
       "      <td>366.73</td>\n",
       "      <td>344586</td>\n",
       "      <td>366.85</td>\n",
       "      <td>-0.000327</td>\n",
       "      <td>-0.001173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-11</th>\n",
       "      <td>364.90</td>\n",
       "      <td>366.58</td>\n",
       "      <td>363.26</td>\n",
       "      <td>366.30</td>\n",
       "      <td>365387</td>\n",
       "      <td>366.73</td>\n",
       "      <td>-0.001173</td>\n",
       "      <td>-0.004477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-14</th>\n",
       "      <td>368.62</td>\n",
       "      <td>369.80</td>\n",
       "      <td>364.47</td>\n",
       "      <td>364.66</td>\n",
       "      <td>437356</td>\n",
       "      <td>366.30</td>\n",
       "      <td>-0.004477</td>\n",
       "      <td>0.013519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low   close  volume  close_yesterday  \\\n",
       "2019-12-18  320.01  320.25  319.53  319.59  276219           319.57   \n",
       "2019-12-19  319.79  320.98  319.75  320.90  344693           319.59   \n",
       "2019-12-20  320.46  321.45  320.37  320.73  521812           320.90   \n",
       "2019-12-23  321.59  321.65  321.06  321.22  257147           320.73   \n",
       "2019-12-24  321.47  321.52  320.90  321.23  122217           321.22   \n",
       "...            ...     ...     ...     ...     ...              ...   \n",
       "2020-12-08  367.69  370.78  367.67  370.17  269841           369.09   \n",
       "2020-12-09  370.88  371.05  365.95  366.85  499276           370.17   \n",
       "2020-12-10  365.37  367.86  364.43  366.73  344586           366.85   \n",
       "2020-12-11  364.90  366.58  363.26  366.30  365387           366.73   \n",
       "2020-12-14  368.62  369.80  364.47  364.66  437356           366.30   \n",
       "\n",
       "            yield_yesterday  yield_tomorrow  \n",
       "2019-12-18         0.000063        0.004099  \n",
       "2019-12-19         0.004099       -0.000530  \n",
       "2019-12-20        -0.000530        0.001528  \n",
       "2019-12-23         0.001528        0.000031  \n",
       "2019-12-24         0.000031        0.005323  \n",
       "...                     ...             ...  \n",
       "2020-12-08         0.002926       -0.008969  \n",
       "2020-12-09        -0.008969       -0.000327  \n",
       "2020-12-10        -0.000327       -0.001173  \n",
       "2020-12-11        -0.001173       -0.004477  \n",
       "2020-12-14        -0.004477        0.013519  \n",
       "\n",
       "[250 rows x 8 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(250, 8)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.31591508]\n",
      "0.0010464284461400627\n"
     ]
    }
   ],
   "source": [
    "x = hist['yield_yesterday']\n",
    "y = hist['yield_tomorrow']\n",
    "model = LinearRegression()\n",
    "model.fit(hist.loc[:, ['yield_yesterday']], y)\n",
    "print(model.coef_)\n",
    "print(model.intercept_)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "preds = model.predict(hist.loc[:, [\"yield_yesterday\"]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.02665719e-03, -2.48508043e-04,  1.21378763e-03,  5.63784514e-04,\n",
       "        1.03659360e-03, -6.35278692e-04,  1.12468820e-03,  2.78813953e-03,\n",
       "        2.78975596e-04, -1.90797529e-03,  3.43861945e-03, -1.58793310e-04,\n",
       "        1.93470777e-03, -6.37251208e-04, -1.09569876e-03,  1.95553659e-03,\n",
       "       -1.12620910e-03,  1.52807973e-03,  3.32496066e-04, -1.58146443e-03,\n",
       "        6.31317862e-05,  1.66503005e-03,  1.00828597e-03,  6.84118644e-04,\n",
       "        3.85587461e-03,  6.11037121e-03, -2.26408814e-03,  1.30736353e-03,\n",
       "        2.11697876e-05,  6.78280148e-03, -1.30037489e-03, -3.76851814e-03,\n",
       "       -2.60177339e-03, -1.65556545e-05,  2.73014855e-03, -1.31199839e-03,\n",
       "        4.98948031e-04, -9.88936850e-04,  1.38348442e-03,  5.40304485e-04,\n",
       "        1.86054609e-03, -4.64049611e-04,  2.34430029e-03,  4.29980527e-03,\n",
       "        1.15238807e-02,  1.06193157e-02,  2.20843817e-03,  1.52347172e-02,\n",
       "        2.37375811e-03, -1.26347653e-02,  1.00918471e-02, -1.22324428e-02,\n",
       "        1.15479845e-02,  6.26885585e-03,  2.57176692e-02, -1.53005612e-02,\n",
       "        1.64467682e-02,  3.12723025e-02, -2.59599752e-02,  3.56150359e-02,\n",
       "       -1.60104832e-02,  1.70421286e-02,  3.75108905e-04,  1.64277663e-02,\n",
       "        9.12380261e-03, -2.75765120e-02, -3.68287809e-03, -1.73997658e-02,\n",
       "        1.04561502e-02, -9.21314497e-03,  5.75527158e-03,  1.52641391e-02,\n",
       "       -6.24342589e-03,  5.61272668e-03, -2.01724134e-02,  7.24382568e-04,\n",
       "       -9.55834731e-03, -3.76094986e-03,  3.93077172e-03, -8.27080868e-03,\n",
       "        7.75902552e-03, -4.77643432e-04, -7.48814587e-03,  6.61219437e-03,\n",
       "        1.06386509e-02, -5.96516463e-03,  1.06906657e-03, -3.35700302e-03,\n",
       "       -3.50858982e-03,  2.49916457e-03, -7.22377344e-03,  3.98782937e-03,\n",
       "        9.40978204e-03,  1.75061845e-04, -1.87241877e-03,  3.18792623e-03,\n",
       "       -2.76566907e-03, -4.18075375e-03,  9.81612057e-04,  7.34312898e-03,\n",
       "        6.63365225e-03, -2.73423140e-03, -4.05825309e-04, -8.57624685e-03,\n",
       "        4.29125112e-03, -4.32035166e-03,  3.22750113e-03,  4.46481200e-04,\n",
       "       -2.84583694e-03, -3.65406005e-03,  1.62927839e-03, -3.61253357e-04,\n",
       "       -2.30436520e-04, -1.56939596e-03, -3.15784259e-03,  1.87623934e-03,\n",
       "       -7.05031592e-03, -2.77217305e-03,  3.40210709e-03,  2.80922651e-03,\n",
       "        1.92585861e-02, -2.73685981e-03, -1.90284614e-03, -5.03420374e-03,\n",
       "        2.35870350e-03,  9.24790092e-04,  4.22807366e-03, -9.80242935e-04,\n",
       "       -4.07948484e-04,  9.10502170e-03, -2.34034243e-03,  8.54986125e-03,\n",
       "       -3.59674934e-03, -3.00030612e-03, -1.16649336e-03, -6.93281666e-04,\n",
       "       -3.83045935e-03,  4.30472306e-03, -1.36990207e-03,  2.84492026e-03,\n",
       "       -2.17924558e-03,  3.78192536e-03, -3.04750345e-03, -1.85596457e-03,\n",
       "        2.08688202e-03,  1.30561297e-04, -1.50665872e-03,  3.74310155e-04,\n",
       "       -7.51802054e-04,  4.81583677e-03,  3.08105615e-03, -1.25736513e-03,\n",
       "        3.05009750e-03, -2.83894242e-03,  2.17358608e-03, -1.44999889e-03,\n",
       "       -1.14984507e-03, -1.73840265e-04, -9.15717559e-04, -1.06531608e-03,\n",
       "        8.19647664e-04,  1.02186349e-04,  3.65418470e-03, -3.35815678e-03,\n",
       "        1.61751723e-03,  1.03704938e-03,  4.28981830e-05,  3.63944923e-04,\n",
       "        2.36180838e-03,  6.27946287e-05, -7.42351876e-05, -2.15478479e-03,\n",
       "       -5.90716531e-05, -2.12080107e-03,  3.55645411e-04, -9.94190870e-04,\n",
       "        2.19085240e-03, -1.92903921e-03, -3.52296151e-03,  1.19184290e-02,\n",
       "        3.62577504e-03,  9.67813914e-03, -5.19204344e-03,  6.53187229e-03,\n",
       "        8.85580372e-04, -3.11457959e-03, -5.49667943e-04,  2.30017027e-03,\n",
       "        3.82497438e-03,  5.92851294e-03,  4.56243476e-03, -2.17098358e-03,\n",
       "        8.37282718e-03,  2.04353789e-04, -4.06094670e-03, -4.20072371e-03,\n",
       "        2.76690315e-03, -1.34881179e-03, -9.81752206e-04,  4.04585952e-03,\n",
       "       -4.55570810e-03,  5.53745102e-03, -4.45258600e-03, -1.75338238e-03,\n",
       "       -1.77473419e-03, -4.03590149e-03,  3.10812773e-03,  3.03144308e-03,\n",
       "        1.43686182e-03,  1.23734116e-03,  5.84942195e-03, -2.19042322e-04,\n",
       "        1.64443882e-03, -6.86481854e-04, -2.61482106e-05,  6.88452594e-03,\n",
       "        2.13550191e-03,  1.18440699e-02, -2.16436584e-03,  4.33980341e-03,\n",
       "       -2.49448289e-03, -4.53135746e-03, -6.01401925e-03, -5.11480758e-03,\n",
       "        1.11858813e-03, -2.92326068e-03,  1.50975155e-03, -1.30035908e-03,\n",
       "        4.11107131e-03, -3.32724368e-03, -2.89699630e-03,  2.74550560e-03,\n",
       "        4.84841236e-03, -2.83628300e-04,  3.20974652e-03, -8.47301655e-04,\n",
       "       -4.04412952e-03,  1.53349536e-03,  1.66612009e-04,  2.44501309e-03,\n",
       "       -2.40886546e-03,  3.81834680e-04,  1.13255813e-03, -1.67601189e-03,\n",
       "        1.69559827e-03,  1.22024413e-04,  3.87982408e-03,  1.14976717e-03,\n",
       "        1.41684669e-03,  2.46084485e-03])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x124c115e0>]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist.plot.scatter(x = \"yield_yesterday\", y = \"yield_tomorrow\")\n",
    "plt.plot(hist['yield_yesterday'], preds, color=\"black\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/huiliu/Documents/YellowstoneIBridgePy'"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist.to_csv(os.path.join(os.getcwd(), 'Output', 'myHist.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "newHist = pd.read_csv(os.path.join(os.getcwd(), 'Output', 'myHist.csv'), header=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>close_yesterday</th>\n",
       "      <th>yield_yesterday</th>\n",
       "      <th>yield_tomorrow</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-18</td>\n",
       "      <td>320.01</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.53</td>\n",
       "      <td>319.59</td>\n",
       "      <td>276219</td>\n",
       "      <td>319.57</td>\n",
       "      <td>0.000063</td>\n",
       "      <td>0.004099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-12-19</td>\n",
       "      <td>319.79</td>\n",
       "      <td>320.98</td>\n",
       "      <td>319.75</td>\n",
       "      <td>320.90</td>\n",
       "      <td>344693</td>\n",
       "      <td>319.59</td>\n",
       "      <td>0.004099</td>\n",
       "      <td>-0.000530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-12-20</td>\n",
       "      <td>320.46</td>\n",
       "      <td>321.45</td>\n",
       "      <td>320.37</td>\n",
       "      <td>320.73</td>\n",
       "      <td>521812</td>\n",
       "      <td>320.90</td>\n",
       "      <td>-0.000530</td>\n",
       "      <td>0.001528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-12-23</td>\n",
       "      <td>321.59</td>\n",
       "      <td>321.65</td>\n",
       "      <td>321.06</td>\n",
       "      <td>321.22</td>\n",
       "      <td>257147</td>\n",
       "      <td>320.73</td>\n",
       "      <td>0.001528</td>\n",
       "      <td>0.000031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-12-24</td>\n",
       "      <td>321.47</td>\n",
       "      <td>321.52</td>\n",
       "      <td>320.90</td>\n",
       "      <td>321.23</td>\n",
       "      <td>122217</td>\n",
       "      <td>321.22</td>\n",
       "      <td>0.000031</td>\n",
       "      <td>0.005323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>367.69</td>\n",
       "      <td>370.78</td>\n",
       "      <td>367.67</td>\n",
       "      <td>370.17</td>\n",
       "      <td>269841</td>\n",
       "      <td>369.09</td>\n",
       "      <td>0.002926</td>\n",
       "      <td>-0.008969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>370.88</td>\n",
       "      <td>371.05</td>\n",
       "      <td>365.95</td>\n",
       "      <td>366.85</td>\n",
       "      <td>499276</td>\n",
       "      <td>370.17</td>\n",
       "      <td>-0.008969</td>\n",
       "      <td>-0.000327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>365.37</td>\n",
       "      <td>367.86</td>\n",
       "      <td>364.43</td>\n",
       "      <td>366.73</td>\n",
       "      <td>344586</td>\n",
       "      <td>366.85</td>\n",
       "      <td>-0.000327</td>\n",
       "      <td>-0.001173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>2020-12-11</td>\n",
       "      <td>364.90</td>\n",
       "      <td>366.58</td>\n",
       "      <td>363.26</td>\n",
       "      <td>366.30</td>\n",
       "      <td>365387</td>\n",
       "      <td>366.73</td>\n",
       "      <td>-0.001173</td>\n",
       "      <td>-0.004477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>368.62</td>\n",
       "      <td>369.80</td>\n",
       "      <td>364.47</td>\n",
       "      <td>364.66</td>\n",
       "      <td>437356</td>\n",
       "      <td>366.30</td>\n",
       "      <td>-0.004477</td>\n",
       "      <td>0.013519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0    open    high     low   close  volume  close_yesterday  \\\n",
       "0    2019-12-18  320.01  320.25  319.53  319.59  276219           319.57   \n",
       "1    2019-12-19  319.79  320.98  319.75  320.90  344693           319.59   \n",
       "2    2019-12-20  320.46  321.45  320.37  320.73  521812           320.90   \n",
       "3    2019-12-23  321.59  321.65  321.06  321.22  257147           320.73   \n",
       "4    2019-12-24  321.47  321.52  320.90  321.23  122217           321.22   \n",
       "..          ...     ...     ...     ...     ...     ...              ...   \n",
       "245  2020-12-08  367.69  370.78  367.67  370.17  269841           369.09   \n",
       "246  2020-12-09  370.88  371.05  365.95  366.85  499276           370.17   \n",
       "247  2020-12-10  365.37  367.86  364.43  366.73  344586           366.85   \n",
       "248  2020-12-11  364.90  366.58  363.26  366.30  365387           366.73   \n",
       "249  2020-12-14  368.62  369.80  364.47  364.66  437356           366.30   \n",
       "\n",
       "     yield_yesterday  yield_tomorrow  \n",
       "0           0.000063        0.004099  \n",
       "1           0.004099       -0.000530  \n",
       "2          -0.000530        0.001528  \n",
       "3           0.001528        0.000031  \n",
       "4           0.000031        0.005323  \n",
       "..               ...             ...  \n",
       "245         0.002926       -0.008969  \n",
       "246        -0.008969       -0.000327  \n",
       "247        -0.000327       -0.001173  \n",
       "248        -0.001173       -0.004477  \n",
       "249        -0.004477        0.013519  \n",
       "\n",
       "[250 rows x 9 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newHist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>close_yesterday</th>\n",
       "      <th>yield_yesterday</th>\n",
       "      <th>yield_tomorrow</th>\n",
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       "    <tr>\n",
       "      <th>Unnamed: 0</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-12-18</th>\n",
       "      <td>320.01</td>\n",
       "      <td>320.25</td>\n",
       "      <td>319.53</td>\n",
       "      <td>319.59</td>\n",
       "      <td>276219</td>\n",
       "      <td>319.57</td>\n",
       "      <td>0.000063</td>\n",
       "      <td>0.004099</td>\n",
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       "    <tr>\n",
       "      <th>2019-12-19</th>\n",
       "      <td>319.79</td>\n",
       "      <td>320.98</td>\n",
       "      <td>319.75</td>\n",
       "      <td>320.90</td>\n",
       "      <td>344693</td>\n",
       "      <td>319.59</td>\n",
       "      <td>0.004099</td>\n",
       "      <td>-0.000530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-20</th>\n",
       "      <td>320.46</td>\n",
       "      <td>321.45</td>\n",
       "      <td>320.37</td>\n",
       "      <td>320.73</td>\n",
       "      <td>521812</td>\n",
       "      <td>320.90</td>\n",
       "      <td>-0.000530</td>\n",
       "      <td>0.001528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23</th>\n",
       "      <td>321.59</td>\n",
       "      <td>321.65</td>\n",
       "      <td>321.06</td>\n",
       "      <td>321.22</td>\n",
       "      <td>257147</td>\n",
       "      <td>320.73</td>\n",
       "      <td>0.001528</td>\n",
       "      <td>0.000031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-24</th>\n",
       "      <td>321.47</td>\n",
       "      <td>321.52</td>\n",
       "      <td>320.90</td>\n",
       "      <td>321.23</td>\n",
       "      <td>122217</td>\n",
       "      <td>321.22</td>\n",
       "      <td>0.000031</td>\n",
       "      <td>0.005323</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-08</th>\n",
       "      <td>367.69</td>\n",
       "      <td>370.78</td>\n",
       "      <td>367.67</td>\n",
       "      <td>370.17</td>\n",
       "      <td>269841</td>\n",
       "      <td>369.09</td>\n",
       "      <td>0.002926</td>\n",
       "      <td>-0.008969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-09</th>\n",
       "      <td>370.88</td>\n",
       "      <td>371.05</td>\n",
       "      <td>365.95</td>\n",
       "      <td>366.85</td>\n",
       "      <td>499276</td>\n",
       "      <td>370.17</td>\n",
       "      <td>-0.008969</td>\n",
       "      <td>-0.000327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-10</th>\n",
       "      <td>365.37</td>\n",
       "      <td>367.86</td>\n",
       "      <td>364.43</td>\n",
       "      <td>366.73</td>\n",
       "      <td>344586</td>\n",
       "      <td>366.85</td>\n",
       "      <td>-0.000327</td>\n",
       "      <td>-0.001173</td>\n",
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       "    <tr>\n",
       "      <th>2020-12-11</th>\n",
       "      <td>364.90</td>\n",
       "      <td>366.58</td>\n",
       "      <td>363.26</td>\n",
       "      <td>366.30</td>\n",
       "      <td>365387</td>\n",
       "      <td>366.73</td>\n",
       "      <td>-0.001173</td>\n",
       "      <td>-0.004477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-14</th>\n",
       "      <td>368.62</td>\n",
       "      <td>369.80</td>\n",
       "      <td>364.47</td>\n",
       "      <td>364.66</td>\n",
       "      <td>437356</td>\n",
       "      <td>366.30</td>\n",
       "      <td>-0.004477</td>\n",
       "      <td>0.013519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low   close  volume  close_yesterday  \\\n",
       "Unnamed: 0                                                            \n",
       "2019-12-18  320.01  320.25  319.53  319.59  276219           319.57   \n",
       "2019-12-19  319.79  320.98  319.75  320.90  344693           319.59   \n",
       "2019-12-20  320.46  321.45  320.37  320.73  521812           320.90   \n",
       "2019-12-23  321.59  321.65  321.06  321.22  257147           320.73   \n",
       "2019-12-24  321.47  321.52  320.90  321.23  122217           321.22   \n",
       "...            ...     ...     ...     ...     ...              ...   \n",
       "2020-12-08  367.69  370.78  367.67  370.17  269841           369.09   \n",
       "2020-12-09  370.88  371.05  365.95  366.85  499276           370.17   \n",
       "2020-12-10  365.37  367.86  364.43  366.73  344586           366.85   \n",
       "2020-12-11  364.90  366.58  363.26  366.30  365387           366.73   \n",
       "2020-12-14  368.62  369.80  364.47  364.66  437356           366.30   \n",
       "\n",
       "            yield_yesterday  yield_tomorrow  \n",
       "Unnamed: 0                                   \n",
       "2019-12-18         0.000063        0.004099  \n",
       "2019-12-19         0.004099       -0.000530  \n",
       "2019-12-20        -0.000530        0.001528  \n",
       "2019-12-23         0.001528        0.000031  \n",
       "2019-12-24         0.000031        0.005323  \n",
       "...                     ...             ...  \n",
       "2020-12-08         0.002926       -0.008969  \n",
       "2020-12-09        -0.008969       -0.000327  \n",
       "2020-12-10        -0.000327       -0.001173  \n",
       "2020-12-11        -0.001173       -0.004477  \n",
       "2020-12-14        -0.004477        0.013519  \n",
       "\n",
       "[250 rows x 8 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newHist.set_index('Unnamed: 0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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