Naive_Average_Holt_winter_Same_Data-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests, pandas as pd, numpy as np\n",
    "from pandas import DataFrame\n",
    "from io import StringIO\n",
    "import time, json\n",
    "from datetime import date\n",
    "from statsmodels.tsa.stattools import adfuller, acf, pacf\n",
    "from statsmodels.tsa.arima_model import ARIMA\n",
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "from sklearn.metrics import *\n",
    "import matplotlib.pylab as plt\n",
    "%matplotlib inline\n",
    "from matplotlib.pylab import rcParams\n",
    "rcParams['figure.figsize'] = 15, 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume_(BTC)</th>\n",
       "      <th>Volume_(Currency)</th>\n",
       "      <th>Weighted_Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1325317920</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1325317980</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1325318040</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1325318100</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1325318160</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1325318220</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1325318280</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1325318340</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1325318400</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1325318460</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.39</td>\n",
       "      <td>0.455581</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Timestamp  Open  High   Low  Close  Volume_(BTC)  Volume_(Currency)  \\\n",
       "0  1325317920  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "1  1325317980  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "2  1325318040  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "3  1325318100  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "4  1325318160  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "5  1325318220  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "6  1325318280  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "7  1325318340  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "8  1325318400  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "9  1325318460  4.39  4.39  4.39   4.39      0.455581                2.0   \n",
       "\n",
       "   Weighted_Price  \n",
       "0            4.39  \n",
       "1            4.39  \n",
       "2            4.39  \n",
       "3            4.39  \n",
       "4            4.39  \n",
       "5            4.39  \n",
       "6            4.39  \n",
       "7            4.39  \n",
       "8            4.39  \n",
       "9            4.39  "
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('bitstampUSD_1-min_data_2012-01-01_to_2018-01-08.csv')\n",
    "df.isnull().values.any()\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2011-12-31    4.472579\n",
       "2012-01-01    4.680778\n",
       "2012-01-02    5.000000\n",
       "2012-01-03    5.145917\n",
       "2012-01-04    5.195443\n",
       "Name: Weighted_Price, dtype: float64"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Date'] = pd.to_datetime(df['Timestamp'],unit='s').dt.date\n",
    "group = df.groupby('Date')\n",
    "Daily_Price = group['Weighted_Price'].mean()\n",
    "Daily_Price.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df= pd.DataFrame(list(Daily_Price), index = Daily_Price.index, columns = [\"Close\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>4.472579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01</th>\n",
       "      <td>4.680778</td>\n",
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       "      <th>2012-01-02</th>\n",
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       "    <tr>\n",
       "      <th>2012-01-03</th>\n",
       "      <td>5.145917</td>\n",
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       "    <tr>\n",
       "      <th>2012-01-04</th>\n",
       "      <td>5.195443</td>\n",
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      ],
      "text/plain": [
       "               Close\n",
       "Date                \n",
       "2011-12-31  4.472579\n",
       "2012-01-01  4.680778\n",
       "2012-01-02  5.000000\n",
       "2012-01-03  5.145917\n",
       "2012-01-04  5.195443"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f4159ad36d8>]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f413cce3f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(new_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2198"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# new_df=new_df.asfreq(freq='1D')\n",
    "len(new_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  Close\n",
      "Date                   \n",
      "2017-06-25  2559.189984\n",
      "2017-06-26  2464.850872\n",
      "2017-06-27  2407.678633\n",
      "2017-06-28  2533.627700\n",
      "2017-06-29  2558.611860\n"
     ]
    }
   ],
   "source": [
    "train=new_df[0:2000] \n",
    "test=new_df[2000:]\n",
    "# print(train.tail())\n",
    "print(test.head())\n",
    "# print(test.tail())\n",
    "# np.any(np.isnan(train.Close))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f413cd96320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.Close.plot(figsize=(15,8), title= 'Daily Price', fontsize=14)\n",
    "test.Close.plot(figsize=(15,8), title= 'Daily Price', fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f413daa9128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dd= np.asarray(train.Close)\n",
    "y_hat = test.copy()\n",
    "y_hat['naive'] = dd[len(dd)-1]\n",
    "\n",
    "#ploting Graph between Train test NAIVE Approach for forecast\n",
    "plt.figure(figsize=(12,8))\n",
    "plt.plot(train.index, train['Close'], label='Train')\n",
    "plt.plot(test.index,test['Close'], label='Test')\n",
    "plt.plot(y_hat.index,y_hat['naive'], label='Naive Forecast')\n",
    "plt.legend(loc='best')\n",
    "plt.title(\"Naive Forecast\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6035.757317152395\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "from math import sqrt\n",
    "rms = sqrt(mean_squared_error(test.Close, y_hat.naive))\n",
    "print(rms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4159a94cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_hat_avg = test.copy()\n",
    "y_hat_avg['avg_forecast'] = train['Close'].mean()\n",
    "\n",
    "plt.figure(figsize=(12,8))\n",
    "plt.plot(train['Close'], label='Train')\n",
    "plt.plot(test['Close'], label='Test')\n",
    "plt.plot(y_hat_avg['avg_forecast'], label='Average Forecast')\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7702.261889682111\n"
     ]
    }
   ],
   "source": [
    "rms = sqrt(mean_squared_error(test.Close, y_hat_avg.avg_forecast))\n",
    "print(rms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f413d9ae8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_hat_avg = test.copy()\n",
    "y_hat_avg['moving_avg_forecast'] = train['Close'].rolling(60).mean().iloc[-1]\n",
    "\n",
    "plt.figure(figsize=(16,8))\n",
    "plt.plot(train['Close'], label='Train')\n",
    "plt.plot(test['Close'], label='Test')\n",
    "plt.plot(y_hat_avg['moving_avg_forecast'], label='Moving Average Forecast')\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6388.595483626814\n"
     ]
    }
   ],
   "source": [
    "rms = sqrt(mean_squared_error(test.Close, y_hat_avg.moving_avg_forecast))\n",
    "print(rms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.api import ExponentialSmoothing, SimpleExpSmoothing, Holt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f413da4b208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_hat_avg = test.copy()\n",
    "# print(y_hat_avg)\n",
    "fit2 = SimpleExpSmoothing(np.asarray(train['Close'])).fit(smoothing_level=0.6,optimized=False)\n",
    "\n",
    "y_hat_avg['SES'] = fit2.forecast(len(test))\n",
    "# print(y_hat_avg['SES'])\n",
    "\n",
    "plt.figure(figsize=(16,8))\n",
    "plt.plot(train['Close'], label='Train')\n",
    "plt.plot(test['Close'], label='Test')\n",
    "plt.plot(y_hat_avg['SES'], label='SES')\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6023.882746244405\n"
     ]
    }
   ],
   "source": [
    "rms = sqrt(mean_squared_error(test.Close, y_hat_avg.SES))\n",
    "print(rms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f413cd1d358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "sm.tsa.seasonal_decompose(train.Close,freq=1).plot()\n",
    "result = sm.tsa.stattools.adfuller(train.Close)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4115830358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_hat_avg = test.copy()\n",
    "\n",
    "fit1 = Holt(np.asarray(train['Close'])).fit(smoothing_level = 0.3,smoothing_slope = 0.1)\n",
    "y_hat_avg['Holt_linear'] = fit1.forecast(len(test))\n",
    "\n",
    "plt.figure(figsize=(16,8))\n",
    "plt.plot(train['Close'], label='Train')\n",
    "plt.plot(test['Close'], label='Test')\n",
    "plt.plot(y_hat_avg['Holt_linear'], label='Holt_linear')\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5523.209004475812\n"
     ]
    }
   ],
   "source": [
    "rms = sqrt(mean_squared_error(test.Close, y_hat_avg.Holt_linear))\n",
    "print(rms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4126777390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# y_hat_avg = test.copy()\n",
    "# fit1 = ExponentialSmoothing(np.asarray(train['Close']) ,seasonal_periods=7 ,trend='add', seasonal='add',).fit()\n",
    "# y_hat_avg['Holt_Winter'] = fit1.forecast(len(test))\n",
    "\n",
    "y_hat_avg = test.copy()\n",
    "fit1 = ExponentialSmoothing(np.asarray(train['Close']) ,seasonal_periods=7 ,trend='add', seasonal='add',).fit()\n",
    "y_hat_avg['Holt_Winter'] = fit1.forecast(len(test))\n",
    "\n",
    "plt.figure(figsize=(16,8))\n",
    "plt.plot( train['Close'], label='Train')\n",
    "plt.plot(test['Close'], label='Test')\n",
    "plt.plot(y_hat_avg['Holt_Winter'], label='Holt_Winter')\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4800.823958339304\n"
     ]
    }
   ],
   "source": [
    "rms = sqrt(mean_squared_error(test.Close, y_hat_avg.Holt_Winter))\n",
    "print(rms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # y_hat_avg = test.copy()\n",
    "# # fit1 = sm.tsa.statespace.SARIMAX(train.Close, order=(2, 1, 2),seasonal_order=(0,1,1,7)).fit()\n",
    "# # y_hat_avg['SARIMA'] = fit1.predict(start=\"2017-06-06\", end=\"2017-11-03\", dynamic=True)\n",
    "\n",
    "# y_hat_avg = test.copy()\n",
    "# fit1 = sm.tsa.statespace.SARIMAX(train.Close, order=(2, 1, 4),seasonal_order=(0,1,1,7)).fit()\n",
    "# y_hat_avg['SARIMA'] = fit1.predict(start=\"2017-06-04\", end=\"2017-11-03\", dynamic=True)\n",
    "\n",
    "# # y_hat_avg = test.copy()\n",
    "# # fit1 = sm.tsa.statespace.SARIMAX(train.Close, order=(2, 1, 1)).fit()\n",
    "# # y_hat_avg['SARIMA'] = fit1.predict(start=\"2017-06-06\", end=\"2017-11-03\", dynamic=True)\n",
    "\n",
    "# # y_hat_avg = test.copy()\n",
    "# # fit1 = sm.tsa.statespace.SARIMAX(train.Close, order=(2, 1, 2),seasonal_order=(-3,0,1,3)).fit()\n",
    "# # y_hat_avg['SARIMA'] = fit1.predict(start=\"2017-06-06\", end=\"2017-11-03\", dynamic=True)\n",
    "\n",
    "# # y_hat_avg = test.copy()\n",
    "# # fit1 = sm.tsa.statespace.SARIMAX(train.Close, order=(2, 1, 4),seasonal_order=(0,1,1,7)).fit(disp=-1)\n",
    "# # y_hat_avg['SARIMA'] = fit1.predict(start=\"2017-06-06\", end=\"2017-11-03\", dynamic=True)\n",
    "\n",
    "# plt.figure(figsize=(16,8))\n",
    "# plt.plot( train['Close'], label='Train')\n",
    "# plt.plot(test['Close'], label='Test')\n",
    "# plt.plot(y_hat_avg['SARIMA'], label='SARIMA',linewidth=3)\n",
    "# plt.legend(loc='best')\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rms = sqrt(mean_squared_error(test.Close, y_hat_avg.SARIMA))\n",
    "# print(rms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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