FBProphet_time_series_forecast.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime\n",
    "from fbprophet import Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>Date</th>\n",
       "      <th>Usage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>835</th>\n",
       "      <td>2018-04-14</td>\n",
       "      <td>55897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>836</th>\n",
       "      <td>2018-04-15</td>\n",
       "      <td>40892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837</th>\n",
       "      <td>2018-04-16</td>\n",
       "      <td>66625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>838</th>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>45260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>839</th>\n",
       "      <td>2018-04-18</td>\n",
       "      <td>37927</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "           Date  Usage\n",
       "835  2018-04-14  55897\n",
       "836  2018-04-15  40892\n",
       "837  2018-04-16  66625\n",
       "838  2018-04-17  45260\n",
       "839  2018-04-18  37927"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('sms_usage.csv',parse_dates=True)\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = ['ds', 'y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Prophet(daily_seasonality=True,changepoint_prior_scale=0.15,yearly_seasonality=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/multiplexer/anaconda3/envs/py3/lib/python3.6/site-packages/pystan/misc.py:399: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  elif np.issubdtype(np.asarray(v).dtype, float):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x7f37da6c1e80>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet.forecaster:Found custom seasonality named \"weekly\", disabling built-in weekly seasonality.\n"
     ]
    }
   ],
   "source": [
    "model.set_auto_seasonalities()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "future = model.make_future_dataframe(periods=30,freq='D')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "forecast = model.predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>yhat</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>trend</th>\n",
       "      <th>OLD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>39630.768050</td>\n",
       "      <td>-19355.082733</td>\n",
       "      <td>100417.396513</td>\n",
       "      <td>45840.711411</td>\n",
       "      <td>47139.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-01-02</td>\n",
       "      <td>48018.097648</td>\n",
       "      <td>-11343.589670</td>\n",
       "      <td>110190.685407</td>\n",
       "      <td>45906.981207</td>\n",
       "      <td>85312.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>25631.024399</td>\n",
       "      <td>-36213.665612</td>\n",
       "      <td>87827.240487</td>\n",
       "      <td>45973.251003</td>\n",
       "      <td>14301.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-04</td>\n",
       "      <td>34570.274262</td>\n",
       "      <td>-26897.341475</td>\n",
       "      <td>96976.152585</td>\n",
       "      <td>46039.520799</td>\n",
       "      <td>20510.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>50298.293699</td>\n",
       "      <td>-13296.045877</td>\n",
       "      <td>111759.534940</td>\n",
       "      <td>46105.790594</td>\n",
       "      <td>24225.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ds          yhat    yhat_lower     yhat_upper         trend      OLD\n",
       "0 2016-01-01  39630.768050 -19355.082733  100417.396513  45840.711411  47139.0\n",
       "1 2016-01-02  48018.097648 -11343.589670  110190.685407  45906.981207  85312.0\n",
       "2 2016-01-03  25631.024399 -36213.665612   87827.240487  45973.251003  14301.0\n",
       "3 2016-01-04  34570.274262 -26897.341475   96976.152585  46039.520799  20510.0\n",
       "4 2016-01-05  50298.293699 -13296.045877  111759.534940  46105.790594  24225.0"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper', 'trend','OLD']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "forecast['OLD'] = df['y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>trend</th>\n",
       "      <th>trend_lower</th>\n",
       "      <th>trend_upper</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>daily</th>\n",
       "      <th>daily_lower</th>\n",
       "      <th>daily_upper</th>\n",
       "      <th>seasonal</th>\n",
       "      <th>seasonal_lower</th>\n",
       "      <th>seasonal_upper</th>\n",
       "      <th>seasonalities</th>\n",
       "      <th>seasonalities_lower</th>\n",
       "      <th>seasonalities_upper</th>\n",
       "      <th>weekly</th>\n",
       "      <th>weekly_lower</th>\n",
       "      <th>weekly_upper</th>\n",
       "      <th>yhat</th>\n",
       "      <th>OLD</th>\n",
       "      <th>predicted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>8.700000e+02</td>\n",
       "      <td>8.700000e+02</td>\n",
       "      <td>8.700000e+02</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>870.000000</td>\n",
       "      <td>840.000000</td>\n",
       "      <td>870.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>68034.548446</td>\n",
       "      <td>68033.936920</td>\n",
       "      <td>68035.221111</td>\n",
       "      <td>2580.559089</td>\n",
       "      <td>123159.387494</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5062.908990</td>\n",
       "      <td>-5062.908990</td>\n",
       "      <td>-5062.908990</td>\n",
       "      <td>-5062.908990</td>\n",
       "      <td>-5062.908990</td>\n",
       "      <td>-5062.908990</td>\n",
       "      <td>6.943538</td>\n",
       "      <td>6.943538</td>\n",
       "      <td>6.943538</td>\n",
       "      <td>62971.639456</td>\n",
       "      <td>62745.089286</td>\n",
       "      <td>52544.279959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9783.244151</td>\n",
       "      <td>9782.856683</td>\n",
       "      <td>9783.672931</td>\n",
       "      <td>12862.568998</td>\n",
       "      <td>12868.757801</td>\n",
       "      <td>1.820036e-12</td>\n",
       "      <td>1.820036e-12</td>\n",
       "      <td>1.820036e-12</td>\n",
       "      <td>7873.455855</td>\n",
       "      <td>7873.455855</td>\n",
       "      <td>7873.455855</td>\n",
       "      <td>7873.455855</td>\n",
       "      <td>7873.455855</td>\n",
       "      <td>7873.455855</td>\n",
       "      <td>7873.455855</td>\n",
       "      <td>7873.455855</td>\n",
       "      <td>7873.455855</td>\n",
       "      <td>12573.311002</td>\n",
       "      <td>48849.474507</td>\n",
       "      <td>10326.796094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>45840.711411</td>\n",
       "      <td>45840.711411</td>\n",
       "      <td>45840.711411</td>\n",
       "      <td>-37776.284567</td>\n",
       "      <td>84736.035005</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>25631.024399</td>\n",
       "      <td>2737.000000</td>\n",
       "      <td>35623.349243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>60250.173751</td>\n",
       "      <td>60250.173751</td>\n",
       "      <td>60250.173751</td>\n",
       "      <td>-6604.054894</td>\n",
       "      <td>114103.527120</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>54496.808807</td>\n",
       "      <td>36651.750000</td>\n",
       "      <td>44580.913313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>74270.475770</td>\n",
       "      <td>74246.691912</td>\n",
       "      <td>74293.053239</td>\n",
       "      <td>4408.825960</td>\n",
       "      <td>125391.316296</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>64700.419616</td>\n",
       "      <td>52852.500000</td>\n",
       "      <td>48785.229368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>75800.435712</td>\n",
       "      <td>75800.435712</td>\n",
       "      <td>75800.435712</td>\n",
       "      <td>13058.428047</td>\n",
       "      <td>133836.409045</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>73628.663118</td>\n",
       "      <td>74907.750000</td>\n",
       "      <td>60359.941927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>77219.673922</td>\n",
       "      <td>77219.673922</td>\n",
       "      <td>77219.673922</td>\n",
       "      <td>26573.447875</td>\n",
       "      <td>146584.176373</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>-5.069853e+03</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>81388.555218</td>\n",
       "      <td>645130.000000</td>\n",
       "      <td>80990.159074</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              trend   trend_lower   trend_upper    yhat_lower     yhat_upper  \\\n",
       "count    870.000000    870.000000    870.000000    870.000000     870.000000   \n",
       "mean   68034.548446  68033.936920  68035.221111   2580.559089  123159.387494   \n",
       "std     9783.244151   9782.856683   9783.672931  12862.568998   12868.757801   \n",
       "min    45840.711411  45840.711411  45840.711411 -37776.284567   84736.035005   \n",
       "25%    60250.173751  60250.173751  60250.173751  -6604.054894  114103.527120   \n",
       "50%    74270.475770  74246.691912  74293.053239   4408.825960  125391.316296   \n",
       "75%    75800.435712  75800.435712  75800.435712  13058.428047  133836.409045   \n",
       "max    77219.673922  77219.673922  77219.673922  26573.447875  146584.176373   \n",
       "\n",
       "              daily   daily_lower   daily_upper      seasonal  seasonal_lower  \\\n",
       "count  8.700000e+02  8.700000e+02  8.700000e+02    870.000000      870.000000   \n",
       "mean  -5.069853e+03 -5.069853e+03 -5.069853e+03  -5062.908990    -5062.908990   \n",
       "std    1.820036e-12  1.820036e-12  1.820036e-12   7873.455855     7873.455855   \n",
       "min   -5.069853e+03 -5.069853e+03 -5.069853e+03 -20342.226603   -20342.226603   \n",
       "25%   -5.069853e+03 -5.069853e+03 -5.069853e+03 -11469.246537   -11469.246537   \n",
       "50%   -5.069853e+03 -5.069853e+03 -5.069853e+03  -2548.516616    -2548.516616   \n",
       "75%   -5.069853e+03 -5.069853e+03 -5.069853e+03   2111.116441     2111.116441   \n",
       "max   -5.069853e+03 -5.069853e+03 -5.069853e+03   4192.503105     4192.503105   \n",
       "\n",
       "       seasonal_upper  seasonalities  seasonalities_lower  \\\n",
       "count      870.000000     870.000000           870.000000   \n",
       "mean     -5062.908990   -5062.908990         -5062.908990   \n",
       "std       7873.455855    7873.455855          7873.455855   \n",
       "min     -20342.226603  -20342.226603        -20342.226603   \n",
       "25%     -11469.246537  -11469.246537        -11469.246537   \n",
       "50%      -2548.516616   -2548.516616         -2548.516616   \n",
       "75%       2111.116441    2111.116441          2111.116441   \n",
       "max       4192.503105    4192.503105          4192.503105   \n",
       "\n",
       "       seasonalities_upper        weekly  weekly_lower  weekly_upper  \\\n",
       "count           870.000000    870.000000    870.000000    870.000000   \n",
       "mean          -5062.908990      6.943538      6.943538      6.943538   \n",
       "std            7873.455855   7873.455855   7873.455855   7873.455855   \n",
       "min          -20342.226603 -15272.374075 -15272.374075 -15272.374075   \n",
       "25%          -11469.246537  -6399.394009  -6399.394009  -6399.394009   \n",
       "50%           -2548.516616   2521.335912   2521.335912   2521.335912   \n",
       "75%            2111.116441   7180.968969   7180.968969   7180.968969   \n",
       "max            4192.503105   9262.355633   9262.355633   9262.355633   \n",
       "\n",
       "               yhat            OLD     predicted  \n",
       "count    870.000000     840.000000    870.000000  \n",
       "mean   62971.639456   62745.089286  52544.279959  \n",
       "std    12573.311002   48849.474507  10326.796094  \n",
       "min    25631.024399    2737.000000  35623.349243  \n",
       "25%    54496.808807   36651.750000  44580.913313  \n",
       "50%    64700.419616   52852.500000  48785.229368  \n",
       "75%    73628.663118   74907.750000  60359.941927  \n",
       "max    81388.555218  645130.000000  80990.159074  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# forecast['predicted'] = (forecast['yhat_upper']-forecast['yhat']-forecast['yhat_lower'])\n",
    "forecast['predicted'] = ((forecast['yhat_upper']-forecast['trend'])-forecast['yhat_lower'])\n",
    "forecast.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['ds', 'trend', 'trend_lower', 'trend_upper', 'yhat_lower', 'yhat_upper',\n",
      "       'daily', 'daily_lower', 'daily_upper', 'seasonal', 'seasonal_lower',\n",
      "       'seasonal_upper', 'seasonalities', 'seasonalities_lower',\n",
      "       'seasonalities_upper', 'weekly', 'weekly_lower', 'weekly_upper', 'yhat',\n",
      "       'OLD', 'predicted'],\n",
      "      dtype='object')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "-0.2046565256946557"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(forecast.columns)\n",
    "forecast['OLD'].corr(forecast['predicted'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>ds</th>\n",
       "      <th>trend</th>\n",
       "      <th>trend_lower</th>\n",
       "      <th>trend_upper</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>daily</th>\n",
       "      <th>daily_lower</th>\n",
       "      <th>daily_upper</th>\n",
       "      <th>seasonal</th>\n",
       "      <th>...</th>\n",
       "      <th>seasonal_upper</th>\n",
       "      <th>seasonalities</th>\n",
       "      <th>seasonalities_lower</th>\n",
       "      <th>seasonalities_upper</th>\n",
       "      <th>weekly</th>\n",
       "      <th>weekly_lower</th>\n",
       "      <th>weekly_upper</th>\n",
       "      <th>yhat</th>\n",
       "      <th>OLD</th>\n",
       "      <th>predicted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>830</th>\n",
       "      <td>2018-04-09</td>\n",
       "      <td>74503.311227</td>\n",
       "      <td>74503.311227</td>\n",
       "      <td>74503.311227</td>\n",
       "      <td>3277.807370</td>\n",
       "      <td>123069.199636</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>...</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>63034.064690</td>\n",
       "      <td>78592.0</td>\n",
       "      <td>45288.081039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>831</th>\n",
       "      <td>2018-04-10</td>\n",
       "      <td>74495.437940</td>\n",
       "      <td>74495.437940</td>\n",
       "      <td>74495.437940</td>\n",
       "      <td>14248.256017</td>\n",
       "      <td>135983.717860</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>...</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>78687.941045</td>\n",
       "      <td>73999.0</td>\n",
       "      <td>47240.023904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>832</th>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>74487.564653</td>\n",
       "      <td>74487.564653</td>\n",
       "      <td>74487.564653</td>\n",
       "      <td>13987.459843</td>\n",
       "      <td>139030.047072</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>...</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>73264.910528</td>\n",
       "      <td>47154.0</td>\n",
       "      <td>50555.022575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>833</th>\n",
       "      <td>2018-04-12</td>\n",
       "      <td>74479.691367</td>\n",
       "      <td>74479.691367</td>\n",
       "      <td>74479.691367</td>\n",
       "      <td>10695.649782</td>\n",
       "      <td>133696.614342</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>...</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>71931.174751</td>\n",
       "      <td>46329.0</td>\n",
       "      <td>48521.273193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>834</th>\n",
       "      <td>2018-04-13</td>\n",
       "      <td>74471.818080</td>\n",
       "      <td>74471.818080</td>\n",
       "      <td>74471.818080</td>\n",
       "      <td>11904.708198</td>\n",
       "      <td>131766.519972</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>...</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>68261.874720</td>\n",
       "      <td>73324.0</td>\n",
       "      <td>45389.993694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>835</th>\n",
       "      <td>2018-04-14</td>\n",
       "      <td>74463.944794</td>\n",
       "      <td>74463.944794</td>\n",
       "      <td>74463.944794</td>\n",
       "      <td>12804.175253</td>\n",
       "      <td>137012.991612</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>...</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>76575.061235</td>\n",
       "      <td>55897.0</td>\n",
       "      <td>49744.871565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>836</th>\n",
       "      <td>2018-04-15</td>\n",
       "      <td>74456.071507</td>\n",
       "      <td>74456.071507</td>\n",
       "      <td>74456.071507</td>\n",
       "      <td>-3519.469248</td>\n",
       "      <td>114371.885588</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>...</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>54113.844904</td>\n",
       "      <td>40892.0</td>\n",
       "      <td>43435.283329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837</th>\n",
       "      <td>2018-04-16</td>\n",
       "      <td>74448.198220</td>\n",
       "      <td>74448.198220</td>\n",
       "      <td>74448.198220</td>\n",
       "      <td>2653.421399</td>\n",
       "      <td>118287.066228</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>...</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>62978.951684</td>\n",
       "      <td>66625.0</td>\n",
       "      <td>41185.446608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>838</th>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>74440.324934</td>\n",
       "      <td>74440.324934</td>\n",
       "      <td>74440.324934</td>\n",
       "      <td>20832.188681</td>\n",
       "      <td>138877.141918</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>...</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>78632.828038</td>\n",
       "      <td>45260.0</td>\n",
       "      <td>43604.628304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>839</th>\n",
       "      <td>2018-04-18</td>\n",
       "      <td>74432.451647</td>\n",
       "      <td>74432.451647</td>\n",
       "      <td>74432.451647</td>\n",
       "      <td>11796.397746</td>\n",
       "      <td>131976.301285</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>...</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>73209.797522</td>\n",
       "      <td>37927.0</td>\n",
       "      <td>45747.451892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840</th>\n",
       "      <td>2018-04-19</td>\n",
       "      <td>74424.578361</td>\n",
       "      <td>74424.578361</td>\n",
       "      <td>74424.578361</td>\n",
       "      <td>9160.477302</td>\n",
       "      <td>129691.677773</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>...</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>71876.061745</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46106.622110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>841</th>\n",
       "      <td>2018-04-20</td>\n",
       "      <td>74416.705074</td>\n",
       "      <td>74416.705074</td>\n",
       "      <td>74416.705074</td>\n",
       "      <td>5441.006959</td>\n",
       "      <td>130035.605371</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>...</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>68206.761713</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50177.893338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>842</th>\n",
       "      <td>2018-04-21</td>\n",
       "      <td>74408.831787</td>\n",
       "      <td>74408.831787</td>\n",
       "      <td>74408.831787</td>\n",
       "      <td>16210.649713</td>\n",
       "      <td>136382.085102</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>...</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>76519.948228</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45762.603602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>843</th>\n",
       "      <td>2018-04-22</td>\n",
       "      <td>74400.958501</td>\n",
       "      <td>74400.958501</td>\n",
       "      <td>74400.958501</td>\n",
       "      <td>-11526.605972</td>\n",
       "      <td>110342.287342</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>...</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>54058.731898</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47467.934813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>844</th>\n",
       "      <td>2018-04-23</td>\n",
       "      <td>74393.085214</td>\n",
       "      <td>74393.085214</td>\n",
       "      <td>74393.085214</td>\n",
       "      <td>1220.203080</td>\n",
       "      <td>122810.460097</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>...</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>62923.838677</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47197.171803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>845</th>\n",
       "      <td>2018-04-24</td>\n",
       "      <td>74385.211928</td>\n",
       "      <td>74385.211928</td>\n",
       "      <td>74385.211928</td>\n",
       "      <td>26573.447875</td>\n",
       "      <td>140785.730636</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>...</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>78577.715032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39827.070834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>846</th>\n",
       "      <td>2018-04-25</td>\n",
       "      <td>74377.338641</td>\n",
       "      <td>74377.338641</td>\n",
       "      <td>74377.338641</td>\n",
       "      <td>16367.995301</td>\n",
       "      <td>132959.201392</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>...</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>73154.684515</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42213.867450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847</th>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>74369.465354</td>\n",
       "      <td>74369.464675</td>\n",
       "      <td>74369.786846</td>\n",
       "      <td>15173.674830</td>\n",
       "      <td>128081.165874</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>...</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>71820.948738</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38538.025690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>74361.592068</td>\n",
       "      <td>74361.197749</td>\n",
       "      <td>74362.817450</td>\n",
       "      <td>5446.039510</td>\n",
       "      <td>124559.747399</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>...</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>68151.648707</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44752.115820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>849</th>\n",
       "      <td>2018-04-28</td>\n",
       "      <td>74353.718781</td>\n",
       "      <td>74352.401551</td>\n",
       "      <td>74356.157886</td>\n",
       "      <td>15314.577125</td>\n",
       "      <td>133031.023853</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>...</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>76464.835222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43362.727947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>2018-04-29</td>\n",
       "      <td>74345.845495</td>\n",
       "      <td>74342.919636</td>\n",
       "      <td>74349.756288</td>\n",
       "      <td>-9251.996007</td>\n",
       "      <td>111063.386311</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>...</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>54003.618891</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45969.536823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>851</th>\n",
       "      <td>2018-04-30</td>\n",
       "      <td>74337.972208</td>\n",
       "      <td>74333.699844</td>\n",
       "      <td>74343.324472</td>\n",
       "      <td>3258.832266</td>\n",
       "      <td>121247.705697</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>...</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>62868.725671</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43650.901222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>852</th>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>74330.098921</td>\n",
       "      <td>74324.112898</td>\n",
       "      <td>74337.918775</td>\n",
       "      <td>16740.201332</td>\n",
       "      <td>140563.243947</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>...</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>78522.602026</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49492.943694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>853</th>\n",
       "      <td>2018-05-02</td>\n",
       "      <td>74322.225635</td>\n",
       "      <td>74313.839269</td>\n",
       "      <td>74332.138948</td>\n",
       "      <td>13089.545122</td>\n",
       "      <td>131092.229544</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>...</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>73099.571509</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43680.458787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>854</th>\n",
       "      <td>2018-05-03</td>\n",
       "      <td>74314.352348</td>\n",
       "      <td>74302.898331</td>\n",
       "      <td>74326.218302</td>\n",
       "      <td>11763.588910</td>\n",
       "      <td>134452.358435</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>...</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>71765.835732</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48374.417177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>855</th>\n",
       "      <td>2018-05-04</td>\n",
       "      <td>74306.479062</td>\n",
       "      <td>74292.013954</td>\n",
       "      <td>74322.249864</td>\n",
       "      <td>8806.556948</td>\n",
       "      <td>128759.418798</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>...</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>68096.535701</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45646.382788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856</th>\n",
       "      <td>2018-05-05</td>\n",
       "      <td>74298.605775</td>\n",
       "      <td>74281.601307</td>\n",
       "      <td>74316.185695</td>\n",
       "      <td>16548.227927</td>\n",
       "      <td>133215.601028</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>...</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>76409.722216</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42368.767326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>857</th>\n",
       "      <td>2018-05-06</td>\n",
       "      <td>74290.732488</td>\n",
       "      <td>74271.633831</td>\n",
       "      <td>74309.245919</td>\n",
       "      <td>-7258.017047</td>\n",
       "      <td>115050.039071</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>...</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>53948.505885</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48017.323629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>858</th>\n",
       "      <td>2018-05-07</td>\n",
       "      <td>74282.859202</td>\n",
       "      <td>74261.994338</td>\n",
       "      <td>74303.371492</td>\n",
       "      <td>3841.205362</td>\n",
       "      <td>123555.111285</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>...</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>62813.612665</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45431.046721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>859</th>\n",
       "      <td>2018-05-08</td>\n",
       "      <td>74274.985915</td>\n",
       "      <td>74251.720829</td>\n",
       "      <td>74299.557121</td>\n",
       "      <td>16852.476481</td>\n",
       "      <td>137704.757569</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>...</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>78467.489020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46577.295173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>860</th>\n",
       "      <td>2018-05-09</td>\n",
       "      <td>74267.112629</td>\n",
       "      <td>74241.662996</td>\n",
       "      <td>74295.427761</td>\n",
       "      <td>11826.168188</td>\n",
       "      <td>135234.543398</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>...</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>73044.458503</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49141.262581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>861</th>\n",
       "      <td>2018-05-10</td>\n",
       "      <td>74259.239342</td>\n",
       "      <td>74230.224297</td>\n",
       "      <td>74290.678717</td>\n",
       "      <td>18896.126453</td>\n",
       "      <td>131771.137895</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>...</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>71710.722726</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38615.772101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>862</th>\n",
       "      <td>2018-05-11</td>\n",
       "      <td>74251.366055</td>\n",
       "      <td>74219.602466</td>\n",
       "      <td>74285.866754</td>\n",
       "      <td>9549.332444</td>\n",
       "      <td>126575.886071</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>...</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>68041.422695</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42775.187572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>2018-05-12</td>\n",
       "      <td>74243.492769</td>\n",
       "      <td>74209.299216</td>\n",
       "      <td>74283.163188</td>\n",
       "      <td>18251.343960</td>\n",
       "      <td>144202.875033</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>...</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>2111.116441</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>7180.968969</td>\n",
       "      <td>76354.609210</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51708.038304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>864</th>\n",
       "      <td>2018-05-13</td>\n",
       "      <td>74235.619482</td>\n",
       "      <td>74197.948824</td>\n",
       "      <td>74278.001755</td>\n",
       "      <td>-3002.902364</td>\n",
       "      <td>113314.915111</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>...</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-20342.226603</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>-15272.374075</td>\n",
       "      <td>53893.392879</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42082.197993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>865</th>\n",
       "      <td>2018-05-14</td>\n",
       "      <td>74227.746195</td>\n",
       "      <td>74186.304619</td>\n",
       "      <td>74273.908967</td>\n",
       "      <td>-15.145717</td>\n",
       "      <td>119383.495883</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>...</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-11469.246537</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>-6399.394009</td>\n",
       "      <td>62758.499659</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45170.895405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866</th>\n",
       "      <td>2018-05-15</td>\n",
       "      <td>74219.872909</td>\n",
       "      <td>74174.677572</td>\n",
       "      <td>74268.863862</td>\n",
       "      <td>22062.815414</td>\n",
       "      <td>141610.893009</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>...</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>4192.503105</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>9262.355633</td>\n",
       "      <td>78412.376014</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45328.204686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867</th>\n",
       "      <td>2018-05-16</td>\n",
       "      <td>74211.999622</td>\n",
       "      <td>74163.802904</td>\n",
       "      <td>74265.527125</td>\n",
       "      <td>8804.192247</td>\n",
       "      <td>132693.086261</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>...</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>-1222.654126</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>3847.198402</td>\n",
       "      <td>72989.345497</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49676.894391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>868</th>\n",
       "      <td>2018-05-17</td>\n",
       "      <td>74204.126336</td>\n",
       "      <td>74150.779450</td>\n",
       "      <td>74262.578347</td>\n",
       "      <td>11920.205716</td>\n",
       "      <td>133584.898235</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>...</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>-2548.516616</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>2521.335912</td>\n",
       "      <td>71655.609720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47460.566183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>869</th>\n",
       "      <td>2018-05-18</td>\n",
       "      <td>74196.253049</td>\n",
       "      <td>74139.934251</td>\n",
       "      <td>74258.235096</td>\n",
       "      <td>8802.371182</td>\n",
       "      <td>126430.468084</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-5069.852528</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>...</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-6209.943361</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>-1140.090833</td>\n",
       "      <td>67986.309688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43431.843853</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>40 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds         trend   trend_lower   trend_upper    yhat_lower  \\\n",
       "830 2018-04-09  74503.311227  74503.311227  74503.311227   3277.807370   \n",
       "831 2018-04-10  74495.437940  74495.437940  74495.437940  14248.256017   \n",
       "832 2018-04-11  74487.564653  74487.564653  74487.564653  13987.459843   \n",
       "833 2018-04-12  74479.691367  74479.691367  74479.691367  10695.649782   \n",
       "834 2018-04-13  74471.818080  74471.818080  74471.818080  11904.708198   \n",
       "835 2018-04-14  74463.944794  74463.944794  74463.944794  12804.175253   \n",
       "836 2018-04-15  74456.071507  74456.071507  74456.071507  -3519.469248   \n",
       "837 2018-04-16  74448.198220  74448.198220  74448.198220   2653.421399   \n",
       "838 2018-04-17  74440.324934  74440.324934  74440.324934  20832.188681   \n",
       "839 2018-04-18  74432.451647  74432.451647  74432.451647  11796.397746   \n",
       "840 2018-04-19  74424.578361  74424.578361  74424.578361   9160.477302   \n",
       "841 2018-04-20  74416.705074  74416.705074  74416.705074   5441.006959   \n",
       "842 2018-04-21  74408.831787  74408.831787  74408.831787  16210.649713   \n",
       "843 2018-04-22  74400.958501  74400.958501  74400.958501 -11526.605972   \n",
       "844 2018-04-23  74393.085214  74393.085214  74393.085214   1220.203080   \n",
       "845 2018-04-24  74385.211928  74385.211928  74385.211928  26573.447875   \n",
       "846 2018-04-25  74377.338641  74377.338641  74377.338641  16367.995301   \n",
       "847 2018-04-26  74369.465354  74369.464675  74369.786846  15173.674830   \n",
       "848 2018-04-27  74361.592068  74361.197749  74362.817450   5446.039510   \n",
       "849 2018-04-28  74353.718781  74352.401551  74356.157886  15314.577125   \n",
       "850 2018-04-29  74345.845495  74342.919636  74349.756288  -9251.996007   \n",
       "851 2018-04-30  74337.972208  74333.699844  74343.324472   3258.832266   \n",
       "852 2018-05-01  74330.098921  74324.112898  74337.918775  16740.201332   \n",
       "853 2018-05-02  74322.225635  74313.839269  74332.138948  13089.545122   \n",
       "854 2018-05-03  74314.352348  74302.898331  74326.218302  11763.588910   \n",
       "855 2018-05-04  74306.479062  74292.013954  74322.249864   8806.556948   \n",
       "856 2018-05-05  74298.605775  74281.601307  74316.185695  16548.227927   \n",
       "857 2018-05-06  74290.732488  74271.633831  74309.245919  -7258.017047   \n",
       "858 2018-05-07  74282.859202  74261.994338  74303.371492   3841.205362   \n",
       "859 2018-05-08  74274.985915  74251.720829  74299.557121  16852.476481   \n",
       "860 2018-05-09  74267.112629  74241.662996  74295.427761  11826.168188   \n",
       "861 2018-05-10  74259.239342  74230.224297  74290.678717  18896.126453   \n",
       "862 2018-05-11  74251.366055  74219.602466  74285.866754   9549.332444   \n",
       "863 2018-05-12  74243.492769  74209.299216  74283.163188  18251.343960   \n",
       "864 2018-05-13  74235.619482  74197.948824  74278.001755  -3002.902364   \n",
       "865 2018-05-14  74227.746195  74186.304619  74273.908967    -15.145717   \n",
       "866 2018-05-15  74219.872909  74174.677572  74268.863862  22062.815414   \n",
       "867 2018-05-16  74211.999622  74163.802904  74265.527125   8804.192247   \n",
       "868 2018-05-17  74204.126336  74150.779450  74262.578347  11920.205716   \n",
       "869 2018-05-18  74196.253049  74139.934251  74258.235096   8802.371182   \n",
       "\n",
       "        yhat_upper        daily  daily_lower  daily_upper      seasonal  \\\n",
       "830  123069.199636 -5069.852528 -5069.852528 -5069.852528 -11469.246537   \n",
       "831  135983.717860 -5069.852528 -5069.852528 -5069.852528   4192.503105   \n",
       "832  139030.047072 -5069.852528 -5069.852528 -5069.852528  -1222.654126   \n",
       "833  133696.614342 -5069.852528 -5069.852528 -5069.852528  -2548.516616   \n",
       "834  131766.519972 -5069.852528 -5069.852528 -5069.852528  -6209.943361   \n",
       "835  137012.991612 -5069.852528 -5069.852528 -5069.852528   2111.116441   \n",
       "836  114371.885588 -5069.852528 -5069.852528 -5069.852528 -20342.226603   \n",
       "837  118287.066228 -5069.852528 -5069.852528 -5069.852528 -11469.246537   \n",
       "838  138877.141918 -5069.852528 -5069.852528 -5069.852528   4192.503105   \n",
       "839  131976.301285 -5069.852528 -5069.852528 -5069.852528  -1222.654126   \n",
       "840  129691.677773 -5069.852528 -5069.852528 -5069.852528  -2548.516616   \n",
       "841  130035.605371 -5069.852528 -5069.852528 -5069.852528  -6209.943361   \n",
       "842  136382.085102 -5069.852528 -5069.852528 -5069.852528   2111.116441   \n",
       "843  110342.287342 -5069.852528 -5069.852528 -5069.852528 -20342.226603   \n",
       "844  122810.460097 -5069.852528 -5069.852528 -5069.852528 -11469.246537   \n",
       "845  140785.730636 -5069.852528 -5069.852528 -5069.852528   4192.503105   \n",
       "846  132959.201392 -5069.852528 -5069.852528 -5069.852528  -1222.654126   \n",
       "847  128081.165874 -5069.852528 -5069.852528 -5069.852528  -2548.516616   \n",
       "848  124559.747399 -5069.852528 -5069.852528 -5069.852528  -6209.943361   \n",
       "849  133031.023853 -5069.852528 -5069.852528 -5069.852528   2111.116441   \n",
       "850  111063.386311 -5069.852528 -5069.852528 -5069.852528 -20342.226603   \n",
       "851  121247.705697 -5069.852528 -5069.852528 -5069.852528 -11469.246537   \n",
       "852  140563.243947 -5069.852528 -5069.852528 -5069.852528   4192.503105   \n",
       "853  131092.229544 -5069.852528 -5069.852528 -5069.852528  -1222.654126   \n",
       "854  134452.358435 -5069.852528 -5069.852528 -5069.852528  -2548.516616   \n",
       "855  128759.418798 -5069.852528 -5069.852528 -5069.852528  -6209.943361   \n",
       "856  133215.601028 -5069.852528 -5069.852528 -5069.852528   2111.116441   \n",
       "857  115050.039071 -5069.852528 -5069.852528 -5069.852528 -20342.226603   \n",
       "858  123555.111285 -5069.852528 -5069.852528 -5069.852528 -11469.246537   \n",
       "859  137704.757569 -5069.852528 -5069.852528 -5069.852528   4192.503105   \n",
       "860  135234.543398 -5069.852528 -5069.852528 -5069.852528  -1222.654126   \n",
       "861  131771.137895 -5069.852528 -5069.852528 -5069.852528  -2548.516616   \n",
       "862  126575.886071 -5069.852528 -5069.852528 -5069.852528  -6209.943361   \n",
       "863  144202.875033 -5069.852528 -5069.852528 -5069.852528   2111.116441   \n",
       "864  113314.915111 -5069.852528 -5069.852528 -5069.852528 -20342.226603   \n",
       "865  119383.495883 -5069.852528 -5069.852528 -5069.852528 -11469.246537   \n",
       "866  141610.893009 -5069.852528 -5069.852528 -5069.852528   4192.503105   \n",
       "867  132693.086261 -5069.852528 -5069.852528 -5069.852528  -1222.654126   \n",
       "868  133584.898235 -5069.852528 -5069.852528 -5069.852528  -2548.516616   \n",
       "869  126430.468084 -5069.852528 -5069.852528 -5069.852528  -6209.943361   \n",
       "\n",
       "         ...       seasonal_upper  seasonalities  seasonalities_lower  \\\n",
       "830      ...        -11469.246537  -11469.246537        -11469.246537   \n",
       "831      ...          4192.503105    4192.503105          4192.503105   \n",
       "832      ...         -1222.654126   -1222.654126         -1222.654126   \n",
       "833      ...         -2548.516616   -2548.516616         -2548.516616   \n",
       "834      ...         -6209.943361   -6209.943361         -6209.943361   \n",
       "835      ...          2111.116441    2111.116441          2111.116441   \n",
       "836      ...        -20342.226603  -20342.226603        -20342.226603   \n",
       "837      ...        -11469.246537  -11469.246537        -11469.246537   \n",
       "838      ...          4192.503105    4192.503105          4192.503105   \n",
       "839      ...         -1222.654126   -1222.654126         -1222.654126   \n",
       "840      ...         -2548.516616   -2548.516616         -2548.516616   \n",
       "841      ...         -6209.943361   -6209.943361         -6209.943361   \n",
       "842      ...          2111.116441    2111.116441          2111.116441   \n",
       "843      ...        -20342.226603  -20342.226603        -20342.226603   \n",
       "844      ...        -11469.246537  -11469.246537        -11469.246537   \n",
       "845      ...          4192.503105    4192.503105          4192.503105   \n",
       "846      ...         -1222.654126   -1222.654126         -1222.654126   \n",
       "847      ...         -2548.516616   -2548.516616         -2548.516616   \n",
       "848      ...         -6209.943361   -6209.943361         -6209.943361   \n",
       "849      ...          2111.116441    2111.116441          2111.116441   \n",
       "850      ...        -20342.226603  -20342.226603        -20342.226603   \n",
       "851      ...        -11469.246537  -11469.246537        -11469.246537   \n",
       "852      ...          4192.503105    4192.503105          4192.503105   \n",
       "853      ...         -1222.654126   -1222.654126         -1222.654126   \n",
       "854      ...         -2548.516616   -2548.516616         -2548.516616   \n",
       "855      ...         -6209.943361   -6209.943361         -6209.943361   \n",
       "856      ...          2111.116441    2111.116441          2111.116441   \n",
       "857      ...        -20342.226603  -20342.226603        -20342.226603   \n",
       "858      ...        -11469.246537  -11469.246537        -11469.246537   \n",
       "859      ...          4192.503105    4192.503105          4192.503105   \n",
       "860      ...         -1222.654126   -1222.654126         -1222.654126   \n",
       "861      ...         -2548.516616   -2548.516616         -2548.516616   \n",
       "862      ...         -6209.943361   -6209.943361         -6209.943361   \n",
       "863      ...          2111.116441    2111.116441          2111.116441   \n",
       "864      ...        -20342.226603  -20342.226603        -20342.226603   \n",
       "865      ...        -11469.246537  -11469.246537        -11469.246537   \n",
       "866      ...          4192.503105    4192.503105          4192.503105   \n",
       "867      ...         -1222.654126   -1222.654126         -1222.654126   \n",
       "868      ...         -2548.516616   -2548.516616         -2548.516616   \n",
       "869      ...         -6209.943361   -6209.943361         -6209.943361   \n",
       "\n",
       "     seasonalities_upper        weekly  weekly_lower  weekly_upper  \\\n",
       "830        -11469.246537  -6399.394009  -6399.394009  -6399.394009   \n",
       "831          4192.503105   9262.355633   9262.355633   9262.355633   \n",
       "832         -1222.654126   3847.198402   3847.198402   3847.198402   \n",
       "833         -2548.516616   2521.335912   2521.335912   2521.335912   \n",
       "834         -6209.943361  -1140.090833  -1140.090833  -1140.090833   \n",
       "835          2111.116441   7180.968969   7180.968969   7180.968969   \n",
       "836        -20342.226603 -15272.374075 -15272.374075 -15272.374075   \n",
       "837        -11469.246537  -6399.394009  -6399.394009  -6399.394009   \n",
       "838          4192.503105   9262.355633   9262.355633   9262.355633   \n",
       "839         -1222.654126   3847.198402   3847.198402   3847.198402   \n",
       "840         -2548.516616   2521.335912   2521.335912   2521.335912   \n",
       "841         -6209.943361  -1140.090833  -1140.090833  -1140.090833   \n",
       "842          2111.116441   7180.968969   7180.968969   7180.968969   \n",
       "843        -20342.226603 -15272.374075 -15272.374075 -15272.374075   \n",
       "844        -11469.246537  -6399.394009  -6399.394009  -6399.394009   \n",
       "845          4192.503105   9262.355633   9262.355633   9262.355633   \n",
       "846         -1222.654126   3847.198402   3847.198402   3847.198402   \n",
       "847         -2548.516616   2521.335912   2521.335912   2521.335912   \n",
       "848         -6209.943361  -1140.090833  -1140.090833  -1140.090833   \n",
       "849          2111.116441   7180.968969   7180.968969   7180.968969   \n",
       "850        -20342.226603 -15272.374075 -15272.374075 -15272.374075   \n",
       "851        -11469.246537  -6399.394009  -6399.394009  -6399.394009   \n",
       "852          4192.503105   9262.355633   9262.355633   9262.355633   \n",
       "853         -1222.654126   3847.198402   3847.198402   3847.198402   \n",
       "854         -2548.516616   2521.335912   2521.335912   2521.335912   \n",
       "855         -6209.943361  -1140.090833  -1140.090833  -1140.090833   \n",
       "856          2111.116441   7180.968969   7180.968969   7180.968969   \n",
       "857        -20342.226603 -15272.374075 -15272.374075 -15272.374075   \n",
       "858        -11469.246537  -6399.394009  -6399.394009  -6399.394009   \n",
       "859          4192.503105   9262.355633   9262.355633   9262.355633   \n",
       "860         -1222.654126   3847.198402   3847.198402   3847.198402   \n",
       "861         -2548.516616   2521.335912   2521.335912   2521.335912   \n",
       "862         -6209.943361  -1140.090833  -1140.090833  -1140.090833   \n",
       "863          2111.116441   7180.968969   7180.968969   7180.968969   \n",
       "864        -20342.226603 -15272.374075 -15272.374075 -15272.374075   \n",
       "865        -11469.246537  -6399.394009  -6399.394009  -6399.394009   \n",
       "866          4192.503105   9262.355633   9262.355633   9262.355633   \n",
       "867         -1222.654126   3847.198402   3847.198402   3847.198402   \n",
       "868         -2548.516616   2521.335912   2521.335912   2521.335912   \n",
       "869         -6209.943361  -1140.090833  -1140.090833  -1140.090833   \n",
       "\n",
       "             yhat      OLD     predicted  \n",
       "830  63034.064690  78592.0  45288.081039  \n",
       "831  78687.941045  73999.0  47240.023904  \n",
       "832  73264.910528  47154.0  50555.022575  \n",
       "833  71931.174751  46329.0  48521.273193  \n",
       "834  68261.874720  73324.0  45389.993694  \n",
       "835  76575.061235  55897.0  49744.871565  \n",
       "836  54113.844904  40892.0  43435.283329  \n",
       "837  62978.951684  66625.0  41185.446608  \n",
       "838  78632.828038  45260.0  43604.628304  \n",
       "839  73209.797522  37927.0  45747.451892  \n",
       "840  71876.061745      NaN  46106.622110  \n",
       "841  68206.761713      NaN  50177.893338  \n",
       "842  76519.948228      NaN  45762.603602  \n",
       "843  54058.731898      NaN  47467.934813  \n",
       "844  62923.838677      NaN  47197.171803  \n",
       "845  78577.715032      NaN  39827.070834  \n",
       "846  73154.684515      NaN  42213.867450  \n",
       "847  71820.948738      NaN  38538.025690  \n",
       "848  68151.648707      NaN  44752.115820  \n",
       "849  76464.835222      NaN  43362.727947  \n",
       "850  54003.618891      NaN  45969.536823  \n",
       "851  62868.725671      NaN  43650.901222  \n",
       "852  78522.602026      NaN  49492.943694  \n",
       "853  73099.571509      NaN  43680.458787  \n",
       "854  71765.835732      NaN  48374.417177  \n",
       "855  68096.535701      NaN  45646.382788  \n",
       "856  76409.722216      NaN  42368.767326  \n",
       "857  53948.505885      NaN  48017.323629  \n",
       "858  62813.612665      NaN  45431.046721  \n",
       "859  78467.489020      NaN  46577.295173  \n",
       "860  73044.458503      NaN  49141.262581  \n",
       "861  71710.722726      NaN  38615.772101  \n",
       "862  68041.422695      NaN  42775.187572  \n",
       "863  76354.609210      NaN  51708.038304  \n",
       "864  53893.392879      NaN  42082.197993  \n",
       "865  62758.499659      NaN  45170.895405  \n",
       "866  78412.376014      NaN  45328.204686  \n",
       "867  72989.345497      NaN  49676.894391  \n",
       "868  71655.609720      NaN  47460.566183  \n",
       "869  67986.309688      NaN  43431.843853  \n",
       "\n",
       "[40 rows x 21 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast.to_csv('sms_predicted.csv')\n",
    "forecast.tail(40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2916775116.4796305"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean((forecast['predicted'].head(838)-forecast['OLD'].head(838))**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.plot(forecast);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.plot_components(forecast);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda Python(py3)",
   "language": "python",
   "name": "py3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}