TimeSeries.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import quandl # for stock data\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = quandl.get(\"EOD/V\",api_key=\"FBC-Lq9A7Tt4Ners7dxJ\",start_date=\"2015-08-20\",end_date=\"2018-01-11\",columns = ['date', 'adj_close'] ) # getting stock data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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i3KOGMTolBgP87Yvd/OPrA6THR5JTVMWG/WW8vmY/i2+bR1ZaLOv2lbKvpJoH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\nIFFKKdUrGkiUUkr1igYSpZRSvfL/y5YX5Q/dHcsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting train data\n",
    "plt.plot(data.index,data['Adj_Close'])\n",
    "plt.title('Visa closing stock price')\n",
    "plt.ylabel('Price ($)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "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",
       "      <th>Dividend</th>\n",
       "      <th>Split</th>\n",
       "      <th>Adj_Open</th>\n",
       "      <th>Adj_High</th>\n",
       "      <th>Adj_Low</th>\n",
       "      <th>Adj_Close</th>\n",
       "      <th>Adj_Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-08-20</th>\n",
       "      <td>73.56</td>\n",
       "      <td>74.53</td>\n",
       "      <td>72.81</td>\n",
       "      <td>73.95</td>\n",
       "      <td>12082313.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>72.020340</td>\n",
       "      <td>72.970038</td>\n",
       "      <td>71.286038</td>\n",
       "      <td>72.402178</td>\n",
       "      <td>12082313.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-21</th>\n",
       "      <td>72.50</td>\n",
       "      <td>73.62</td>\n",
       "      <td>70.96</td>\n",
       "      <td>71.19</td>\n",
       "      <td>15751191.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>70.982527</td>\n",
       "      <td>72.079085</td>\n",
       "      <td>69.474760</td>\n",
       "      <td>69.699946</td>\n",
       "      <td>15751191.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-24</th>\n",
       "      <td>64.16</td>\n",
       "      <td>71.06</td>\n",
       "      <td>60.00</td>\n",
       "      <td>68.36</td>\n",
       "      <td>20949581.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>62.817089</td>\n",
       "      <td>69.572667</td>\n",
       "      <td>58.744160</td>\n",
       "      <td>66.929180</td>\n",
       "      <td>20949581.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-25</th>\n",
       "      <td>71.69</td>\n",
       "      <td>71.80</td>\n",
       "      <td>66.60</td>\n",
       "      <td>66.97</td>\n",
       "      <td>14483302.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>70.189481</td>\n",
       "      <td>70.297178</td>\n",
       "      <td>65.206018</td>\n",
       "      <td>65.568274</td>\n",
       "      <td>14483302.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-26</th>\n",
       "      <td>69.37</td>\n",
       "      <td>70.99</td>\n",
       "      <td>67.90</td>\n",
       "      <td>70.69</td>\n",
       "      <td>12188142.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>67.918040</td>\n",
       "      <td>69.504132</td>\n",
       "      <td>66.478808</td>\n",
       "      <td>69.210411</td>\n",
       "      <td>12188142.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open   High    Low  Close      Volume  Dividend  Split  \\\n",
       "Date                                                                  \n",
       "2015-08-20  73.56  74.53  72.81  73.95  12082313.0       0.0    1.0   \n",
       "2015-08-21  72.50  73.62  70.96  71.19  15751191.0       0.0    1.0   \n",
       "2015-08-24  64.16  71.06  60.00  68.36  20949581.0       0.0    1.0   \n",
       "2015-08-25  71.69  71.80  66.60  66.97  14483302.0       0.0    1.0   \n",
       "2015-08-26  69.37  70.99  67.90  70.69  12188142.0       0.0    1.0   \n",
       "\n",
       "             Adj_Open   Adj_High    Adj_Low  Adj_Close  Adj_Volume  \n",
       "Date                                                                \n",
       "2015-08-20  72.020340  72.970038  71.286038  72.402178  12082313.0  \n",
       "2015-08-21  70.982527  72.079085  69.474760  69.699946  15751191.0  \n",
       "2015-08-24  62.817089  69.572667  58.744160  66.929180  20949581.0  \n",
       "2015-08-25  70.189481  70.297178  65.206018  65.568274  14483302.0  \n",
       "2015-08-26  67.918040  69.504132  66.478808  69.210411  12188142.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas.stats.moments import ewma # for removing outliers\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "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",
       "      <th>Dividend</th>\n",
       "      <th>Split</th>\n",
       "      <th>Adj_Open</th>\n",
       "      <th>Adj_High</th>\n",
       "      <th>Adj_Low</th>\n",
       "      <th>Adj_Close</th>\n",
       "      <th>Adj_Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-08-20</th>\n",
       "      <td>73.560000</td>\n",
       "      <td>74.530000</td>\n",
       "      <td>72.810000</td>\n",
       "      <td>73.950000</td>\n",
       "      <td>1.208231e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>72.020340</td>\n",
       "      <td>72.970038</td>\n",
       "      <td>71.286038</td>\n",
       "      <td>72.402178</td>\n",
       "      <td>1.208231e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-21</th>\n",
       "      <td>73.012333</td>\n",
       "      <td>74.059833</td>\n",
       "      <td>71.854167</td>\n",
       "      <td>72.524000</td>\n",
       "      <td>1.397790e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>71.484137</td>\n",
       "      <td>72.509712</td>\n",
       "      <td>70.350211</td>\n",
       "      <td>71.006025</td>\n",
       "      <td>1.397790e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-24</th>\n",
       "      <td>69.862725</td>\n",
       "      <td>72.992510</td>\n",
       "      <td>67.636524</td>\n",
       "      <td>71.042473</td>\n",
       "      <td>1.645838e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>68.400452</td>\n",
       "      <td>71.464729</td>\n",
       "      <td>66.220846</td>\n",
       "      <td>69.555507</td>\n",
       "      <td>1.645838e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-25</th>\n",
       "      <td>70.366206</td>\n",
       "      <td>72.663930</td>\n",
       "      <td>67.350924</td>\n",
       "      <td>69.920358</td>\n",
       "      <td>1.591418e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>68.893395</td>\n",
       "      <td>71.143026</td>\n",
       "      <td>65.941224</td>\n",
       "      <td>68.456879</td>\n",
       "      <td>1.591418e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-26</th>\n",
       "      <td>70.139545</td>\n",
       "      <td>72.283071</td>\n",
       "      <td>67.475852</td>\n",
       "      <td>70.095470</td>\n",
       "      <td>1.506641e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>68.671478</td>\n",
       "      <td>70.770138</td>\n",
       "      <td>66.063537</td>\n",
       "      <td>68.628326</td>\n",
       "      <td>1.506641e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close        Volume  \\\n",
       "Date                                                                   \n",
       "2015-08-20  73.560000  74.530000  72.810000  73.950000  1.208231e+07   \n",
       "2015-08-21  73.012333  74.059833  71.854167  72.524000  1.397790e+07   \n",
       "2015-08-24  69.862725  72.992510  67.636524  71.042473  1.645838e+07   \n",
       "2015-08-25  70.366206  72.663930  67.350924  69.920358  1.591418e+07   \n",
       "2015-08-26  70.139545  72.283071  67.475852  70.095470  1.506641e+07   \n",
       "\n",
       "            Dividend  Split   Adj_Open   Adj_High    Adj_Low  Adj_Close  \\\n",
       "Date                                                                      \n",
       "2015-08-20       0.0    1.0  72.020340  72.970038  71.286038  72.402178   \n",
       "2015-08-21       0.0    1.0  71.484137  72.509712  70.350211  71.006025   \n",
       "2015-08-24       0.0    1.0  68.400452  71.464729  66.220846  69.555507   \n",
       "2015-08-25       0.0    1.0  68.893395  71.143026  65.941224  68.456879   \n",
       "2015-08-26       0.0    1.0  68.671478  70.770138  66.063537  68.628326   \n",
       "\n",
       "              Adj_Volume  \n",
       "Date                      \n",
       "2015-08-20  1.208231e+07  \n",
       "2015-08-21  1.397790e+07  \n",
       "2015-08-24  1.645838e+07  \n",
       "2015-08-25  1.591418e+07  \n",
       "2015-08-26  1.506641e+07  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smoothed_data = data.ewm(span=30).mean() # taking lags or previous periods for avg as 30\n",
    "smoothed_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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LNVxE5GkRSRWR7SIyzl95KaUUwDNfpRITGcYbt0xi5qiedqfTqvlzj+Q1YMZJw+4DVhhj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\nhUQppZRXtJAopZTyyv8HMY4UqIZLJLMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(smoothed_data.index,smoothed_data['Adj_Close'])\n",
    "plt.title('visa closing stock price')\n",
    "plt.ylabel('price ($)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test = quandl.get(\"EOD/V\",api_key=\"FBC-Lq9A7Tt4Ners7dxJ\",start_date=\"2018-01-12\",end_date=\"2018-08-21\") #getting test data\n",
    "\n",
    "smoothed_data=smoothed_data.reset_index(level=0) # modiving data as column\n",
    "\n",
    "smoothed_data=smoothed_data[['Date','Adj_Close']]\n",
    "smoothed_data=smoothed_data.rename(index=str,columns={\"Date\":\"ds\",\"Adj_Close\":\"y\"}) # modifing the columns according to the model takes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "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>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-08-20</td>\n",
       "      <td>72.402178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-08-21</td>\n",
       "      <td>71.006025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-08-24</td>\n",
       "      <td>69.555507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-08-25</td>\n",
       "      <td>68.456879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-08-26</td>\n",
       "      <td>68.628326</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ds          y\n",
       "0 2015-08-20  72.402178\n",
       "1 2015-08-21  71.006025\n",
       "2 2015-08-24  69.555507\n",
       "3 2015-08-25  68.456879\n",
       "4 2015-08-26  68.628326"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import fbprophet # faceook prophet\n",
    "smoothed_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stock_model = fbprophet.Prophet(seasonality_mode='multiplicative',daily_seasonality=True) # creating model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x24311fa8780>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_model.fit(smoothed_data) # fitting model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stock_forecast = stock_model.make_future_dataframe(periods=len(test),freq='D') # making future data frame\n",
    "forecast = stock_model.predict(stock_forecast) # predicting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "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>additive_terms</th>\n",
       "      <th>additive_terms_lower</th>\n",
       "      <th>additive_terms_upper</th>\n",
       "      <th>daily</th>\n",
       "      <th>...</th>\n",
       "      <th>multiplicative_terms</th>\n",
       "      <th>multiplicative_terms_lower</th>\n",
       "      <th>multiplicative_terms_upper</th>\n",
       "      <th>weekly</th>\n",
       "      <th>weekly_lower</th>\n",
       "      <th>weekly_upper</th>\n",
       "      <th>yearly</th>\n",
       "      <th>yearly_lower</th>\n",
       "      <th>yearly_upper</th>\n",
       "      <th>yhat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-08-20</td>\n",
       "      <td>17.730065</td>\n",
       "      <td>17.730065</td>\n",
       "      <td>17.730065</td>\n",
       "      <td>69.797653</td>\n",
       "      <td>70.405581</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.803696</td>\n",
       "      <td>...</td>\n",
       "      <td>2.954265</td>\n",
       "      <td>2.954265</td>\n",
       "      <td>2.954265</td>\n",
       "      <td>0.141867</td>\n",
       "      <td>0.141867</td>\n",
       "      <td>0.141867</td>\n",
       "      <td>0.008701</td>\n",
       "      <td>0.008701</td>\n",
       "      <td>0.008701</td>\n",
       "      <td>70.109373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-08-21</td>\n",
       "      <td>17.717558</td>\n",
       "      <td>17.717558</td>\n",
       "      <td>17.717558</td>\n",
       "      <td>69.741636</td>\n",
       "      <td>70.349561</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.803696</td>\n",
       "      <td>...</td>\n",
       "      <td>2.953745</td>\n",
       "      <td>2.953745</td>\n",
       "      <td>2.953745</td>\n",
       "      <td>0.142444</td>\n",
       "      <td>0.142444</td>\n",
       "      <td>0.142444</td>\n",
       "      <td>0.007604</td>\n",
       "      <td>0.007604</td>\n",
       "      <td>0.007604</td>\n",
       "      <td>70.050714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-08-24</td>\n",
       "      <td>17.680039</td>\n",
       "      <td>17.680039</td>\n",
       "      <td>17.680039</td>\n",
       "      <td>69.476163</td>\n",
       "      <td>70.075281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.803696</td>\n",
       "      <td>...</td>\n",
       "      <td>2.946891</td>\n",
       "      <td>2.946891</td>\n",
       "      <td>2.946891</td>\n",
       "      <td>0.138389</td>\n",
       "      <td>0.138389</td>\n",
       "      <td>0.138389</td>\n",
       "      <td>0.004806</td>\n",
       "      <td>0.004806</td>\n",
       "      <td>0.004806</td>\n",
       "      <td>69.781178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-08-25</td>\n",
       "      <td>17.667532</td>\n",
       "      <td>17.667532</td>\n",
       "      <td>17.667532</td>\n",
       "      <td>69.411643</td>\n",
       "      <td>70.016253</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.803696</td>\n",
       "      <td>...</td>\n",
       "      <td>2.946136</td>\n",
       "      <td>2.946136</td>\n",
       "      <td>2.946136</td>\n",
       "      <td>0.138364</td>\n",
       "      <td>0.138364</td>\n",
       "      <td>0.138364</td>\n",
       "      <td>0.004076</td>\n",
       "      <td>0.004076</td>\n",
       "      <td>0.004076</td>\n",
       "      <td>69.718488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-08-26</td>\n",
       "      <td>17.655026</td>\n",
       "      <td>17.655026</td>\n",
       "      <td>17.655026</td>\n",
       "      <td>69.362570</td>\n",
       "      <td>69.998042</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.803696</td>\n",
       "      <td>...</td>\n",
       "      <td>2.947015</td>\n",
       "      <td>2.947015</td>\n",
       "      <td>2.947015</td>\n",
       "      <td>0.139860</td>\n",
       "      <td>0.139860</td>\n",
       "      <td>0.139860</td>\n",
       "      <td>0.003458</td>\n",
       "      <td>0.003458</td>\n",
       "      <td>0.003458</td>\n",
       "      <td>69.684643</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          ds      trend  trend_lower  trend_upper  yhat_lower  yhat_upper  \\\n",
       "0 2015-08-20  17.730065    17.730065    17.730065   69.797653   70.405581   \n",
       "1 2015-08-21  17.717558    17.717558    17.717558   69.741636   70.349561   \n",
       "2 2015-08-24  17.680039    17.680039    17.680039   69.476163   70.075281   \n",
       "3 2015-08-25  17.667532    17.667532    17.667532   69.411643   70.016253   \n",
       "4 2015-08-26  17.655026    17.655026    17.655026   69.362570   69.998042   \n",
       "\n",
       "   additive_terms  additive_terms_lower  additive_terms_upper     daily  \\\n",
       "0             0.0                   0.0                   0.0  2.803696   \n",
       "1             0.0                   0.0                   0.0  2.803696   \n",
       "2             0.0                   0.0                   0.0  2.803696   \n",
       "3             0.0                   0.0                   0.0  2.803696   \n",
       "4             0.0                   0.0                   0.0  2.803696   \n",
       "\n",
       "     ...      multiplicative_terms  multiplicative_terms_lower  \\\n",
       "0    ...                  2.954265                    2.954265   \n",
       "1    ...                  2.953745                    2.953745   \n",
       "2    ...                  2.946891                    2.946891   \n",
       "3    ...                  2.946136                    2.946136   \n",
       "4    ...                  2.947015                    2.947015   \n",
       "\n",
       "   multiplicative_terms_upper    weekly  weekly_lower  weekly_upper    yearly  \\\n",
       "0                    2.954265  0.141867      0.141867      0.141867  0.008701   \n",
       "1                    2.953745  0.142444      0.142444      0.142444  0.007604   \n",
       "2                    2.946891  0.138389      0.138389      0.138389  0.004806   \n",
       "3                    2.946136  0.138364      0.138364      0.138364  0.004076   \n",
       "4                    2.947015  0.139860      0.139860      0.139860  0.003458   \n",
       "\n",
       "   yearly_lower  yearly_upper       yhat  \n",
       "0      0.008701      0.008701  70.109373  \n",
       "1      0.007604      0.007604  70.050714  \n",
       "2      0.004806      0.004806  69.781178  \n",
       "3      0.004076      0.004076  69.718488  \n",
       "4      0.003458      0.003458  69.684643  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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oRQrIIiIiIjVqPF9kz2ie1kYXv9QyYUhWZcM/T+SDuLxsbiNubDGIaxyrBzkZ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\nAVlEREREJI//B3BNwgMXL6ypAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_prediction=stock_model.plot(forecast) # plotiing prediction\n",
    "plot_prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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QABQRkYBqaHfz523lPLapjLdL6rFaYFJOEtdMymH6sFROzknU6V6RXqYAKCIi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\nL5aNac2F3BLiP9lOZmGp3t/zuwNpTN90fZH9Z7sEYWslvS6GSgpAUS+e6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xIAAAKnSURB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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 648x864 with 4 Axes>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ploting_predcition_components=stock_model.plot_components(forecast)\n",
    "ploting_predcition_components # plotting components of the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error # modules to evaluate\n",
    "from math import sqrt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.264156008891835"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sqrt(mean_squared_error(test['Adj_Close'],forecast.tail(len(test))['yhat'])) # test set error\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.200770709696132"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sqrt(mean_squared_error(data['Adj_Close'],forecast.head(len(data))['yhat'])) # train set error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}