13_fbprophet.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This is Facebook Prophet practice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Selim\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\tqdm\\auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Load the data\n",
    "df=pd.read_csv(\"./UDEMY_TSA_FINAL/Data/BeerWineLiquor.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>beer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/1992</td>\n",
       "      <td>1509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2/1/1992</td>\n",
       "      <td>1541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3/1/1992</td>\n",
       "      <td>1597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4/1/1992</td>\n",
       "      <td>1675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5/1/1992</td>\n",
       "      <td>1822</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "       date  beer\n",
       "0  1/1/1992  1509\n",
       "1  2/1/1992  1541\n",
       "2  3/1/1992  1597\n",
       "3  4/1/1992  1675\n",
       "4  5/1/1992  1822"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "### change the data format to ds, y\n",
    "df.columns=[\"ds\",\"y\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <td>1509</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2/1/1992</td>\n",
       "      <td>1541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3/1/1992</td>\n",
       "      <td>1597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4/1/1992</td>\n",
       "      <td>1675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5/1/1992</td>\n",
       "      <td>1822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319</th>\n",
       "      <td>8/1/2018</td>\n",
       "      <td>4898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>9/1/2018</td>\n",
       "      <td>4598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>321</th>\n",
       "      <td>10/1/2018</td>\n",
       "      <td>4737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322</th>\n",
       "      <td>11/1/2018</td>\n",
       "      <td>5130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>323</th>\n",
       "      <td>12/1/2018</td>\n",
       "      <td>6370</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>324 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds     y\n",
       "0     1/1/1992  1509\n",
       "1     2/1/1992  1541\n",
       "2     3/1/1992  1597\n",
       "3     4/1/1992  1675\n",
       "4     5/1/1992  1822\n",
       "..         ...   ...\n",
       "319   8/1/2018  4898\n",
       "320   9/1/2018  4598\n",
       "321  10/1/2018  4737\n",
       "322  11/1/2018  5130\n",
       "323  12/1/2018  6370\n",
       "\n",
       "[324 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"ds\"]=pd.to_datetime(df[\"ds\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     1992-01-01\n",
       "1     1992-02-01\n",
       "2     1992-03-01\n",
       "3     1992-04-01\n",
       "4     1992-05-01\n",
       "         ...    \n",
       "319   2018-08-01\n",
       "320   2018-09-01\n",
       "321   2018-10-01\n",
       "322   2018-11-01\n",
       "323   2018-12-01\n",
       "Name: ds, Length: 324, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#### create and fit the model\n",
    "# m=Prophet()\n",
    "# m.fit(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "22:34:43 - cmdstanpy - INFO - Chain [1] start processing\n",
      "22:34:43 - cmdstanpy - INFO - Chain [1] done processing\n"
     ]
    }
   ],
   "source": [
    "m = prophet.Prophet(seasonality_mode='multiplicative').fit(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "future=m.make_future_dataframe(periods=24,freq=\"MS\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>319</th>\n",
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       "      <th>321</th>\n",
       "      <td>2018-10-01</td>\n",
       "      <td>4737</td>\n",
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       "    <tr>\n",
       "      <th>322</th>\n",
       "      <td>2018-11-01</td>\n",
       "      <td>5130</td>\n",
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       "      <th>323</th>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>6370</td>\n",
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      "text/plain": [
       "            ds     y\n",
       "319 2018-08-01  4898\n",
       "320 2018-09-01  4598\n",
       "321 2018-10-01  4737\n",
       "322 2018-11-01  5130\n",
       "323 2018-12-01  6370"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>343</th>\n",
       "      <td>2020-08-01</td>\n",
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       "    <tr>\n",
       "      <th>344</th>\n",
       "      <td>2020-09-01</td>\n",
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       "      <th>345</th>\n",
       "      <td>2020-10-01</td>\n",
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       "      <th>346</th>\n",
       "      <td>2020-11-01</td>\n",
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       "    <tr>\n",
       "      <th>347</th>\n",
       "      <td>2020-12-01</td>\n",
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      ],
      "text/plain": [
       "            ds\n",
       "343 2020-08-01\n",
       "344 2020-09-01\n",
       "345 2020-10-01\n",
       "346 2020-11-01\n",
       "347 2020-12-01"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "future.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(324, 348)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df), len(future)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Predict and fill the values for future"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "forecast=m.predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
       "      <td>1992-01-01</td>\n",
       "      <td>1780.930970</td>\n",
       "      <td>1409.920120</td>\n",
       "      <td>1580.935991</td>\n",
       "      <td>1780.930970</td>\n",
       "      <td>1780.930970</td>\n",
       "      <td>-0.159155</td>\n",
       "      <td>-0.159155</td>\n",
       "      <td>-0.159155</td>\n",
       "      <td>-0.159155</td>\n",
       "      <td>-0.159155</td>\n",
       "      <td>-0.159155</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1497.487717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1992-02-01</td>\n",
       "      <td>1782.864053</td>\n",
       "      <td>1442.351910</td>\n",
       "      <td>1613.808931</td>\n",
       "      <td>1782.864053</td>\n",
       "      <td>1782.864053</td>\n",
       "      <td>-0.144135</td>\n",
       "      <td>-0.144135</td>\n",
       "      <td>-0.144135</td>\n",
       "      <td>-0.144135</td>\n",
       "      <td>-0.144135</td>\n",
       "      <td>-0.144135</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1525.891777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1992-03-01</td>\n",
       "      <td>1784.672421</td>\n",
       "      <td>1595.484452</td>\n",
       "      <td>1763.764370</td>\n",
       "      <td>1784.672421</td>\n",
       "      <td>1784.672421</td>\n",
       "      <td>-0.060558</td>\n",
       "      <td>-0.060558</td>\n",
       "      <td>-0.060558</td>\n",
       "      <td>-0.060558</td>\n",
       "      <td>-0.060558</td>\n",
       "      <td>-0.060558</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1676.595412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1992-04-01</td>\n",
       "      <td>1786.605504</td>\n",
       "      <td>1583.247331</td>\n",
       "      <td>1756.735371</td>\n",
       "      <td>1786.605504</td>\n",
       "      <td>1786.605504</td>\n",
       "      <td>-0.066089</td>\n",
       "      <td>-0.066089</td>\n",
       "      <td>-0.066089</td>\n",
       "      <td>-0.066089</td>\n",
       "      <td>-0.066089</td>\n",
       "      <td>-0.066089</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1668.530999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1992-05-01</td>\n",
       "      <td>1788.476229</td>\n",
       "      <td>1733.861731</td>\n",
       "      <td>1906.301048</td>\n",
       "      <td>1788.476229</td>\n",
       "      <td>1788.476229</td>\n",
       "      <td>0.018630</td>\n",
       "      <td>0.018630</td>\n",
       "      <td>0.018630</td>\n",
       "      <td>0.018630</td>\n",
       "      <td>0.018630</td>\n",
       "      <td>0.018630</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1821.796012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ds        trend   yhat_lower   yhat_upper  trend_lower  trend_upper  \\\n",
       "0 1992-01-01  1780.930970  1409.920120  1580.935991  1780.930970  1780.930970   \n",
       "1 1992-02-01  1782.864053  1442.351910  1613.808931  1782.864053  1782.864053   \n",
       "2 1992-03-01  1784.672421  1595.484452  1763.764370  1784.672421  1784.672421   \n",
       "3 1992-04-01  1786.605504  1583.247331  1756.735371  1786.605504  1786.605504   \n",
       "4 1992-05-01  1788.476229  1733.861731  1906.301048  1788.476229  1788.476229   \n",
       "\n",
       "   multiplicative_terms  multiplicative_terms_lower  \\\n",
       "0             -0.159155                   -0.159155   \n",
       "1             -0.144135                   -0.144135   \n",
       "2             -0.060558                   -0.060558   \n",
       "3             -0.066089                   -0.066089   \n",
       "4              0.018630                    0.018630   \n",
       "\n",
       "   multiplicative_terms_upper    yearly  yearly_lower  yearly_upper  \\\n",
       "0                   -0.159155 -0.159155     -0.159155     -0.159155   \n",
       "1                   -0.144135 -0.144135     -0.144135     -0.144135   \n",
       "2                   -0.060558 -0.060558     -0.060558     -0.060558   \n",
       "3                   -0.066089 -0.066089     -0.066089     -0.066089   \n",
       "4                    0.018630  0.018630      0.018630      0.018630   \n",
       "\n",
       "   additive_terms  additive_terms_lower  additive_terms_upper         yhat  \n",
       "0             0.0                   0.0                   0.0  1497.487717  \n",
       "1             0.0                   0.0                   0.0  1525.891777  \n",
       "2             0.0                   0.0                   0.0  1676.595412  \n",
       "3             0.0                   0.0                   0.0  1668.530999  \n",
       "4             0.0                   0.0                   0.0  1821.796012  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>trend</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>trend_lower</th>\n",
       "      <th>trend_upper</th>\n",
       "      <th>multiplicative_terms</th>\n",
       "      <th>multiplicative_terms_lower</th>\n",
       "      <th>multiplicative_terms_upper</th>\n",
       "      <th>yearly</th>\n",
       "      <th>yearly_lower</th>\n",
       "      <th>yearly_upper</th>\n",
       "      <th>additive_terms</th>\n",
       "      <th>additive_terms_lower</th>\n",
       "      <th>additive_terms_upper</th>\n",
       "      <th>yhat</th>\n",
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       "      <th>343</th>\n",
       "      <td>2020-08-01</td>\n",
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       "    <tr>\n",
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       "      <th>346</th>\n",
       "      <td>2020-11-01</td>\n",
       "      <td>5220.015373</td>\n",
       "      <td>5289.155350</td>\n",
       "      <td>5473.622706</td>\n",
       "      <td>5182.265535</td>\n",
       "      <td>5255.761320</td>\n",
       "      <td>0.030804</td>\n",
       "      <td>0.030804</td>\n",
       "      <td>0.030804</td>\n",
       "      <td>0.030804</td>\n",
       "      <td>0.030804</td>\n",
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       "    <tr>\n",
       "      <th>347</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>5235.238022</td>\n",
       "      <td>6981.299816</td>\n",
       "      <td>7192.711514</td>\n",
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      ],
      "text/plain": [
       "            ds        trend   yhat_lower   yhat_upper  trend_lower  \\\n",
       "343 2020-08-01  5173.332582  5162.810325  5339.621179  5143.595076   \n",
       "344 2020-09-01  5189.062653  4884.843333  5073.053106  5156.569398   \n",
       "345 2020-10-01  5204.285302  5030.397149  5217.448084  5169.131616   \n",
       "346 2020-11-01  5220.015373  5289.155350  5473.622706  5182.265535   \n",
       "347 2020-12-01  5235.238022  6981.299816  7192.711514  5195.053962   \n",
       "\n",
       "     trend_upper  multiplicative_terms  multiplicative_terms_lower  \\\n",
       "343  5202.936920              0.015074                    0.015074   \n",
       "344  5220.592245             -0.041161                   -0.041161   \n",
       "345  5238.372966             -0.016158                   -0.016158   \n",
       "346  5255.761320              0.030804                    0.030804   \n",
       "347  5272.841181              0.353794                    0.353794   \n",
       "\n",
       "     multiplicative_terms_upper    yearly  yearly_lower  yearly_upper  \\\n",
       "343                    0.015074  0.015074      0.015074      0.015074   \n",
       "344                   -0.041161 -0.041161     -0.041161     -0.041161   \n",
       "345                   -0.016158 -0.016158     -0.016158     -0.016158   \n",
       "346                    0.030804  0.030804      0.030804      0.030804   \n",
       "347                    0.353794  0.353794      0.353794      0.353794   \n",
       "\n",
       "     additive_terms  additive_terms_lower  additive_terms_upper         yhat  \n",
       "343             0.0                   0.0                   0.0  5251.313046  \n",
       "344             0.0                   0.0                   0.0  4975.475049  \n",
       "345             0.0                   0.0                   0.0  5120.192141  \n",
       "346             0.0                   0.0                   0.0  5380.810279  \n",
       "347             0.0                   0.0                   0.0  7087.433841  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ds', 'trend', 'yhat_lower', 'yhat_upper', 'trend_lower', 'trend_upper',\n",
       "       'multiplicative_terms', 'multiplicative_terms_lower',\n",
       "       'multiplicative_terms_upper', 'yearly', 'yearly_lower', 'yearly_upper',\n",
       "       'additive_terms', 'additive_terms_lower', 'additive_terms_upper',\n",
       "       'yhat'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>trend</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>343</th>\n",
       "      <td>2020-08-01</td>\n",
       "      <td>5173.332582</td>\n",
       "      <td>5162.810325</td>\n",
       "      <td>5339.621179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>344</th>\n",
       "      <td>2020-09-01</td>\n",
       "      <td>5189.062653</td>\n",
       "      <td>4884.843333</td>\n",
       "      <td>5073.053106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345</th>\n",
       "      <td>2020-10-01</td>\n",
       "      <td>5204.285302</td>\n",
       "      <td>5030.397149</td>\n",
       "      <td>5217.448084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>346</th>\n",
       "      <td>2020-11-01</td>\n",
       "      <td>5220.015373</td>\n",
       "      <td>5289.155350</td>\n",
       "      <td>5473.622706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>347</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>5235.238022</td>\n",
       "      <td>6981.299816</td>\n",
       "      <td>7192.711514</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds        trend   yhat_lower   yhat_upper\n",
       "343 2020-08-01  5173.332582  5162.810325  5339.621179\n",
       "344 2020-09-01  5189.062653  4884.843333  5073.053106\n",
       "345 2020-10-01  5204.285302  5030.397149  5217.448084\n",
       "346 2020-11-01  5220.015373  5289.155350  5473.622706\n",
       "347 2020-12-01  5235.238022  6981.299816  7192.711514"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast[['ds', 'trend', 'yhat_lower', 'yhat_upper']].tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "### plotting the foreacast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m.plot(forecast);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(15645.0, 18597.0)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import datetime\n",
    "\n",
    "m.plot(forecast);\n",
    "plt.xlim(forecast.ds[250].date(),forecast.ds[347].date())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(forecast.ds[347].date())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='ds'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "forecast.plot(x=\"ds\",y=\"yhat\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m.plot_components(forecast);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prophet Evaluations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "## train/test split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Selim\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\tqdm\\auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 588 entries, 0 to 587\n",
      "Data columns (total 2 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   DATE              588 non-null    object \n",
      " 1   TRFVOLUSM227NFWA  588 non-null    float64\n",
      "dtypes: float64(1), object(1)\n",
      "memory usage: 9.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df=pd.read_csv(\"./UDEMY_TSA_FINAL/Data/Miles_Traveled.csv\")\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>TRFVOLUSM227NFWA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1970-01-01</td>\n",
       "      <td>80173.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1970-02-01</td>\n",
       "      <td>77442.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1970-03-01</td>\n",
       "      <td>90223.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1970-04-01</td>\n",
       "      <td>89956.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1970-05-01</td>\n",
       "      <td>97972.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         DATE  TRFVOLUSM227NFWA\n",
       "0  1970-01-01           80173.0\n",
       "1  1970-02-01           77442.0\n",
       "2  1970-03-01           90223.0\n",
       "3  1970-04-01           89956.0\n",
       "4  1970-05-01           97972.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1970-01-01</td>\n",
       "      <td>80173.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1970-02-01</td>\n",
       "      <td>77442.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1970-03-01</td>\n",
       "      <td>90223.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1970-04-01</td>\n",
       "      <td>89956.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1970-05-01</td>\n",
       "      <td>97972.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ds        y\n",
       "0 1970-01-01  80173.0\n",
       "1 1970-02-01  77442.0\n",
       "2 1970-03-01  90223.0\n",
       "3 1970-04-01  89956.0\n",
       "4 1970-05-01  97972.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns=[\"ds\",\"y\"]\n",
    "df[\"ds\"]=pd.to_datetime(df[\"ds\"])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='ds'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(x=\"ds\",y=\"y\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(588, 576)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df), len(df)-12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "train=df.iloc[:576]\n",
    "test=df.iloc[576:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "m=prophet.Prophet()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "01:02:51 - cmdstanpy - INFO - Chain [1] start processing\n",
      "01:02:51 - cmdstanpy - INFO - Chain [1] done processing\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<prophet.forecaster.Prophet at 0x1bed6483bc8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.fit(train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "future=m.make_future_dataframe(periods=12,freq=\"MS\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "forecast=m.predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>trend_lower</th>\n",
       "      <th>trend_upper</th>\n",
       "      <th>additive_terms</th>\n",
       "      <th>additive_terms_lower</th>\n",
       "      <th>additive_terms_upper</th>\n",
       "      <th>yearly</th>\n",
       "      <th>yearly_lower</th>\n",
       "      <th>yearly_upper</th>\n",
       "      <th>multiplicative_terms</th>\n",
       "      <th>multiplicative_terms_lower</th>\n",
       "      <th>multiplicative_terms_upper</th>\n",
       "      <th>yhat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>583</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>263259.631706</td>\n",
       "      <td>273904.562817</td>\n",
       "      <td>285727.534340</td>\n",
       "      <td>263197.718545</td>\n",
       "      <td>263322.056267</td>\n",
       "      <td>16449.550366</td>\n",
       "      <td>16449.550366</td>\n",
       "      <td>16449.550366</td>\n",
       "      <td>16449.550366</td>\n",
       "      <td>16449.550366</td>\n",
       "      <td>16449.550366</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>279709.182072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>2018-09-01</td>\n",
       "      <td>263398.341584</td>\n",
       "      <td>256261.924815</td>\n",
       "      <td>268047.010819</td>\n",
       "      <td>263297.381929</td>\n",
       "      <td>263480.082871</td>\n",
       "      <td>-1667.533350</td>\n",
       "      <td>-1667.533350</td>\n",
       "      <td>-1667.533350</td>\n",
       "      <td>-1667.533350</td>\n",
       "      <td>-1667.533350</td>\n",
       "      <td>-1667.533350</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>261730.808234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585</th>\n",
       "      <td>2018-10-01</td>\n",
       "      <td>263532.576949</td>\n",
       "      <td>262981.726560</td>\n",
       "      <td>274005.264291</td>\n",
       "      <td>263393.682489</td>\n",
       "      <td>263632.449204</td>\n",
       "      <td>5309.074263</td>\n",
       "      <td>5309.074263</td>\n",
       "      <td>5309.074263</td>\n",
       "      <td>5309.074263</td>\n",
       "      <td>5309.074263</td>\n",
       "      <td>5309.074263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>268841.651212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586</th>\n",
       "      <td>2018-11-01</td>\n",
       "      <td>263671.286826</td>\n",
       "      <td>249399.937541</td>\n",
       "      <td>260785.824879</td>\n",
       "      <td>263488.887119</td>\n",
       "      <td>263805.506318</td>\n",
       "      <td>-8205.142435</td>\n",
       "      <td>-8205.142435</td>\n",
       "      <td>-8205.142435</td>\n",
       "      <td>-8205.142435</td>\n",
       "      <td>-8205.142435</td>\n",
       "      <td>-8205.142435</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>255466.144392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>587</th>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>263805.522192</td>\n",
       "      <td>251373.629159</td>\n",
       "      <td>262573.772556</td>\n",
       "      <td>263580.295523</td>\n",
       "      <td>263975.166830</td>\n",
       "      <td>-6918.629429</td>\n",
       "      <td>-6918.629429</td>\n",
       "      <td>-6918.629429</td>\n",
       "      <td>-6918.629429</td>\n",
       "      <td>-6918.629429</td>\n",
       "      <td>-6918.629429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>256886.892763</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds          trend     yhat_lower     yhat_upper    trend_lower  \\\n",
       "583 2018-08-01  263259.631706  273904.562817  285727.534340  263197.718545   \n",
       "584 2018-09-01  263398.341584  256261.924815  268047.010819  263297.381929   \n",
       "585 2018-10-01  263532.576949  262981.726560  274005.264291  263393.682489   \n",
       "586 2018-11-01  263671.286826  249399.937541  260785.824879  263488.887119   \n",
       "587 2018-12-01  263805.522192  251373.629159  262573.772556  263580.295523   \n",
       "\n",
       "       trend_upper  additive_terms  additive_terms_lower  \\\n",
       "583  263322.056267    16449.550366          16449.550366   \n",
       "584  263480.082871    -1667.533350          -1667.533350   \n",
       "585  263632.449204     5309.074263           5309.074263   \n",
       "586  263805.506318    -8205.142435          -8205.142435   \n",
       "587  263975.166830    -6918.629429          -6918.629429   \n",
       "\n",
       "     additive_terms_upper        yearly  yearly_lower  yearly_upper  \\\n",
       "583          16449.550366  16449.550366  16449.550366  16449.550366   \n",
       "584          -1667.533350  -1667.533350  -1667.533350  -1667.533350   \n",
       "585           5309.074263   5309.074263   5309.074263   5309.074263   \n",
       "586          -8205.142435  -8205.142435  -8205.142435  -8205.142435   \n",
       "587          -6918.629429  -6918.629429  -6918.629429  -6918.629429   \n",
       "\n",
       "     multiplicative_terms  multiplicative_terms_lower  \\\n",
       "583                   0.0                         0.0   \n",
       "584                   0.0                         0.0   \n",
       "585                   0.0                         0.0   \n",
       "586                   0.0                         0.0   \n",
       "587                   0.0                         0.0   \n",
       "\n",
       "     multiplicative_terms_upper           yhat  \n",
       "583                         0.0  279709.182072  \n",
       "584                         0.0  261730.808234  \n",
       "585                         0.0  268841.651212  \n",
       "586                         0.0  255466.144392  \n",
       "587                         0.0  256886.892763  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>583</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>286608.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>2018-09-01</td>\n",
       "      <td>260595.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585</th>\n",
       "      <td>2018-10-01</td>\n",
       "      <td>282174.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586</th>\n",
       "      <td>2018-11-01</td>\n",
       "      <td>258590.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>587</th>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>268413.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds         y\n",
       "583 2018-08-01  286608.0\n",
       "584 2018-09-01  260595.0\n",
       "585 2018-10-01  282174.0\n",
       "586 2018-11-01  258590.0\n",
       "587 2018-12-01  268413.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ax is the parameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='ds'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=forecast.plot(x=\"ds\",y=\"yhat\",label=\"predictions\",legend=True)\n",
    "\n",
    "test.plot(x=\"ds\",y=\"y\",label=\"true miles\",legend=True,ax=ax,xlim=('2018-01-01','2019-01-01'),ylim=(220000,300000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tools.eval_measures import rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions=forecast.iloc[-12:][\"yhat\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(576    243718.687623\n",
       " 577    235346.300721\n",
       " 578    262547.147937\n",
       " 579    262745.730889\n",
       " 580    272466.972940\n",
       " 581    272717.536061\n",
       " 582    279174.637816\n",
       " 583    279709.182072\n",
       " 584    261730.808234\n",
       " 585    268841.651212\n",
       " 586    255466.144392\n",
       " 587    256886.892763\n",
       " Name: yhat, dtype: float64,\n",
       " 576    245695.0\n",
       " 577    226660.0\n",
       " 578    268480.0\n",
       " 579    272475.0\n",
       " 580    286164.0\n",
       " 581    280877.0\n",
       " 582    288145.0\n",
       " 583    286608.0\n",
       " 584    260595.0\n",
       " 585    282174.0\n",
       " 586    258590.0\n",
       " 587    268413.0\n",
       " Name: y, dtype: float64)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions, test[\"y\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8723.114585667272"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmse(predictions,test[\"y\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Selim\\AppData\\Roaming\\Python\\Python37\\site-packages\\ipykernel_launcher.py:1: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "y    268739.666667\n",
       "dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prophet Diagnostics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from fbprophet.diagnostics import cross_validation,performance_metrics\n",
    "# from fbprophet.plot import plot_cross_validation_metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from prophet.diagnostics import cross_validation, performance_metrics\n",
    "from prophet.plot import plot_cross_validation_metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(588, 49.0)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df), len(df)/12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on class Timedelta in module pandas._libs.tslibs.timedeltas:\n",
      "\n",
      "class Timedelta(_Timedelta)\n",
      " |  Timedelta(value=<object object at 0x000001BECAD9DD40>, unit=None, **kwargs)\n",
      " |  \n",
      " |  Represents a duration, the difference between two dates or times.\n",
      " |  \n",
      " |  Timedelta is the pandas equivalent of python's ``datetime.timedelta``\n",
      " |  and is interchangeable with it in most cases.\n",
      " |  \n",
      " |  Parameters\n",
      " |  ----------\n",
      " |  value : Timedelta, timedelta, np.timedelta64, str, or int\n",
      " |  unit : str, default 'ns'\n",
      " |      Denote the unit of the input, if input is an integer.\n",
      " |  \n",
      " |      Possible values:\n",
      " |  \n",
      " |      * 'W', 'D', 'T', 'S', 'L', 'U', or 'N'\n",
      " |      * 'days' or 'day'\n",
      " |      * 'hours', 'hour', 'hr', or 'h'\n",
      " |      * 'minutes', 'minute', 'min', or 'm'\n",
      " |      * 'seconds', 'second', or 'sec'\n",
      " |      * 'milliseconds', 'millisecond', 'millis', or 'milli'\n",
      " |      * 'microseconds', 'microsecond', 'micros', or 'micro'\n",
      " |      * 'nanoseconds', 'nanosecond', 'nanos', 'nano', or 'ns'.\n",
      " |  \n",
      " |  **kwargs\n",
      " |      Available kwargs: {days, seconds, microseconds,\n",
      " |      milliseconds, minutes, hours, weeks}.\n",
      " |      Values for construction in compat with datetime.timedelta.\n",
      " |      Numpy ints and floats will be coerced to python ints and floats.\n",
      " |  \n",
      " |  Notes\n",
      " |  -----\n",
      " |  The ``.value`` attribute is always in ns.\n",
      " |  \n",
      " |  If the precision is higher than nanoseconds, the precision of the duration is\n",
      " |  truncated to nanoseconds.\n",
      " |  \n",
      " |  Method resolution order:\n",
      " |      Timedelta\n",
      " |      _Timedelta\n",
      " |      datetime.timedelta\n",
      " |      builtins.object\n",
      " |  \n",
      " |  Methods defined here:\n",
      " |  \n",
      " |  __abs__(self)\n",
      " |  \n",
      " |  __add__(self, other)\n",
      " |  \n",
      " |  __divmod__(self, other)\n",
      " |  \n",
      " |  __floordiv__(self, other)\n",
      " |  \n",
      " |  __inv__(self)\n",
      " |  \n",
      " |  __mod__(self, other)\n",
      " |  \n",
      " |  __mul__(self, other)\n",
      " |  \n",
      " |  __neg__(self)\n",
      " |  \n",
      " |  __new__(cls, value=<object object at 0x000001BECAD9DD40>, unit=None, **kwargs)\n",
      " |  \n",
      " |  __pos__(self)\n",
      " |  \n",
      " |  __radd__(self, other)\n",
      " |  \n",
      " |  __rdivmod__(self, other)\n",
      " |  \n",
      " |  __reduce__(self)\n",
      " |  \n",
      " |  __rfloordiv__(self, other)\n",
      " |  \n",
      " |  __rmod__(self, other)\n",
      " |  \n",
      " |  __rmul__ = __mul__(self, other)\n",
      " |  \n",
      " |  __rsub__(self, other)\n",
      " |  \n",
      " |  __rtruediv__(self, other)\n",
      " |  \n",
      " |  __setstate__(self, state)\n",
      " |  \n",
      " |  __sub__(self, other)\n",
      " |  \n",
      " |  __truediv__(self, other)\n",
      " |  \n",
      " |  ceil(self, freq)\n",
      " |      Return a new Timedelta ceiled to this resolution.\n",
      " |      \n",
      " |      Parameters\n",
      " |      ----------\n",
      " |      freq : str\n",
      " |          Frequency string indicating the ceiling resolution.\n",
      " |  \n",
      " |  floor(self, freq)\n",
      " |      Return a new Timedelta floored to this resolution.\n",
      " |      \n",
      " |      Parameters\n",
      " |      ----------\n",
      " |      freq : str\n",
      " |          Frequency string indicating the flooring resolution.\n",
      " |  \n",
      " |  round(self, freq)\n",
      " |      Round the Timedelta to the specified resolution.\n",
      " |      \n",
      " |      Parameters\n",
      " |      ----------\n",
      " |      freq : str\n",
      " |          Frequency string indicating the rounding resolution.\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      a new Timedelta rounded to the given resolution of `freq`\n",
      " |      \n",
      " |      Raises\n",
      " |      ------\n",
      " |      ValueError if the freq cannot be converted\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data descriptors defined here:\n",
      " |  \n",
      " |  __dict__\n",
      " |      dictionary for instance variables (if defined)\n",
      " |  \n",
      " |  __weakref__\n",
      " |      list of weak references to the object (if defined)\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data and other attributes defined here:\n",
      " |  \n",
      " |  max = Timedelta('106751 days 23:47:16.854775807')\n",
      " |  \n",
      " |  min = Timedelta('-106752 days +00:12:43.145224193')\n",
      " |  \n",
      " |  resolution = Timedelta('0 days 00:00:00.000000001')\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Methods inherited from _Timedelta:\n",
      " |  \n",
      " |  __bool__(self, /)\n",
      " |      self != 0\n",
      " |  \n",
      " |  __eq__(self, value, /)\n",
      " |      Return self==value.\n",
      " |  \n",
      " |  __ge__(self, value, /)\n",
      " |      Return self>=value.\n",
      " |  \n",
      " |  __gt__(self, value, /)\n",
      " |      Return self>value.\n",
      " |  \n",
      " |  __hash__(self, /)\n",
      " |      Return hash(self).\n",
      " |  \n",
      " |  __le__(self, value, /)\n",
      " |      Return self<=value.\n",
      " |  \n",
      " |  __lt__(self, value, /)\n",
      " |      Return self<value.\n",
      " |  \n",
      " |  __ne__(self, value, /)\n",
      " |      Return self!=value.\n",
      " |  \n",
      " |  __reduce_cython__(...)\n",
      " |  \n",
      " |  __repr__(self, /)\n",
      " |      Return repr(self).\n",
      " |  \n",
      " |  __setstate_cython__(...)\n",
      " |  \n",
      " |  __str__(self, /)\n",
      " |      Return str(self).\n",
      " |  \n",
      " |  isoformat(...)\n",
      " |      Format Timedelta as ISO 8601 Duration like\n",
      " |      ``P[n]Y[n]M[n]DT[n]H[n]M[n]S``, where the ``[n]`` s are replaced by the\n",
      " |      values. See https://en.wikipedia.org/wiki/ISO_8601#Durations.\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      str\n",
      " |      \n",
      " |      See Also\n",
      " |      --------\n",
      " |      Timestamp.isoformat : Function is used to convert the given\n",
      " |          Timestamp object into the ISO format.\n",
      " |      \n",
      " |      Notes\n",
      " |      -----\n",
      " |      The longest component is days, whose value may be larger than\n",
      " |      365.\n",
      " |      Every component is always included, even if its value is 0.\n",
      " |      Pandas uses nanosecond precision, so up to 9 decimal places may\n",
      " |      be included in the seconds component.\n",
      " |      Trailing 0's are removed from the seconds component after the decimal.\n",
      " |      We do not 0 pad components, so it's `...T5H...`, not `...T05H...`\n",
      " |      \n",
      " |      Examples\n",
      " |      --------\n",
      " |      >>> td = pd.Timedelta(days=6, minutes=50, seconds=3,\n",
      " |      ...                   milliseconds=10, microseconds=10, nanoseconds=12)\n",
      " |      \n",
      " |      >>> td.isoformat()\n",
      " |      'P6DT0H50M3.010010012S'\n",
      " |      >>> pd.Timedelta(hours=1, seconds=10).isoformat()\n",
      " |      'P0DT1H0M10S'\n",
      " |      >>> pd.Timedelta(days=500.5).isoformat()\n",
      " |      'P500DT12H0M0S'\n",
      " |  \n",
      " |  to_numpy(...)\n",
      " |      Convert the Timedelta to a NumPy timedelta64.\n",
      " |      \n",
      " |      .. versionadded:: 0.25.0\n",
      " |      \n",
      " |      This is an alias method for `Timedelta.to_timedelta64()`. The dtype and\n",
      " |      copy parameters are available here only for compatibility. Their values\n",
      " |      will not affect the return value.\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      numpy.timedelta64\n",
      " |      \n",
      " |      See Also\n",
      " |      --------\n",
      " |      Series.to_numpy : Similar method for Series.\n",
      " |  \n",
      " |  to_pytimedelta(...)\n",
      " |      Convert a pandas Timedelta object into a python timedelta object.\n",
      " |      \n",
      " |      Timedelta objects are internally saved as numpy datetime64[ns] dtype.\n",
      " |      Use to_pytimedelta() to convert to object dtype.\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      datetime.timedelta or numpy.array of datetime.timedelta\n",
      " |      \n",
      " |      See Also\n",
      " |      --------\n",
      " |      to_timedelta : Convert argument to Timedelta type.\n",
      " |      \n",
      " |      Notes\n",
      " |      -----\n",
      " |      Any nanosecond resolution will be lost.\n",
      " |  \n",
      " |  to_timedelta64(...)\n",
      " |      Return a numpy.timedelta64 object with 'ns' precision.\n",
      " |  \n",
      " |  view(...)\n",
      " |      Array view compatibility.\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data descriptors inherited from _Timedelta:\n",
      " |  \n",
      " |  asm8\n",
      " |      Return a numpy timedelta64 array scalar view.\n",
      " |      \n",
      " |      Provides access to the array scalar view (i.e. a combination of the\n",
      " |      value and the units) associated with the numpy.timedelta64().view(),\n",
      " |      including a 64-bit integer representation of the timedelta in\n",
      " |      nanoseconds (Python int compatible).\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      numpy timedelta64 array scalar view\n",
      " |          Array scalar view of the timedelta in nanoseconds.\n",
      " |      \n",
      " |      Examples\n",
      " |      --------\n",
      " |      >>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')\n",
      " |      >>> td.asm8\n",
      " |      numpy.timedelta64(86520000003042,'ns')\n",
      " |      \n",
      " |      >>> td = pd.Timedelta('2 min 3 s')\n",
      " |      >>> td.asm8\n",
      " |      numpy.timedelta64(123000000000,'ns')\n",
      " |      \n",
      " |      >>> td = pd.Timedelta('3 ms 5 us')\n",
      " |      >>> td.asm8\n",
      " |      numpy.timedelta64(3005000,'ns')\n",
      " |      \n",
      " |      >>> td = pd.Timedelta(42, unit='ns')\n",
      " |      >>> td.asm8\n",
      " |      numpy.timedelta64(42,'ns')\n",
      " |  \n",
      " |  components\n",
      " |      Return a components namedtuple-like.\n",
      " |  \n",
      " |  delta\n",
      " |      Return the timedelta in nanoseconds (ns), for internal compatibility.\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      int\n",
      " |          Timedelta in nanoseconds.\n",
      " |      \n",
      " |      Examples\n",
      " |      --------\n",
      " |      >>> td = pd.Timedelta('1 days 42 ns')\n",
      " |      >>> td.delta\n",
      " |      86400000000042\n",
      " |      \n",
      " |      >>> td = pd.Timedelta('3 s')\n",
      " |      >>> td.delta\n",
      " |      3000000000\n",
      " |      \n",
      " |      >>> td = pd.Timedelta('3 ms 5 us')\n",
      " |      >>> td.delta\n",
      " |      3005000\n",
      " |      \n",
      " |      >>> td = pd.Timedelta(42, unit='ns')\n",
      " |      >>> td.delta\n",
      " |      42\n",
      " |  \n",
      " |  freq\n",
      " |  \n",
      " |  is_populated\n",
      " |  \n",
      " |  nanoseconds\n",
      " |      Return the number of nanoseconds (n), where 0 <= n < 1 microsecond.\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      int\n",
      " |          Number of nanoseconds.\n",
      " |      \n",
      " |      See Also\n",
      " |      --------\n",
      " |      Timedelta.components : Return all attributes with assigned values\n",
      " |          (i.e. days, hours, minutes, seconds, milliseconds, microseconds,\n",
      " |          nanoseconds).\n",
      " |      \n",
      " |      Examples\n",
      " |      --------\n",
      " |      **Using string input**\n",
      " |      \n",
      " |      >>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')\n",
      " |      \n",
      " |      >>> td.nanoseconds\n",
      " |      42\n",
      " |      \n",
      " |      **Using integer input**\n",
      " |      \n",
      " |      >>> td = pd.Timedelta(42, unit='ns')\n",
      " |      >>> td.nanoseconds\n",
      " |      42\n",
      " |  \n",
      " |  resolution_string\n",
      " |      Return a string representing the lowest timedelta resolution.\n",
      " |      \n",
      " |      Each timedelta has a defined resolution that represents the lowest OR\n",
      " |      most granular level of precision. Each level of resolution is\n",
      " |      represented by a short string as defined below:\n",
      " |      \n",
      " |      Resolution:     Return value\n",
      " |      \n",
      " |      * Days:         'D'\n",
      " |      * Hours:        'H'\n",
      " |      * Minutes:      'T'\n",
      " |      * Seconds:      'S'\n",
      " |      * Milliseconds: 'L'\n",
      " |      * Microseconds: 'U'\n",
      " |      * Nanoseconds:  'N'\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      str\n",
      " |          Timedelta resolution.\n",
      " |      \n",
      " |      Examples\n",
      " |      --------\n",
      " |      >>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')\n",
      " |      >>> td.resolution_string\n",
      " |      'N'\n",
      " |      \n",
      " |      >>> td = pd.Timedelta('1 days 2 min 3 us')\n",
      " |      >>> td.resolution_string\n",
      " |      'U'\n",
      " |      \n",
      " |      >>> td = pd.Timedelta('2 min 3 s')\n",
      " |      >>> td.resolution_string\n",
      " |      'S'\n",
      " |      \n",
      " |      >>> td = pd.Timedelta(36, unit='us')\n",
      " |      >>> td.resolution_string\n",
      " |      'U'\n",
      " |  \n",
      " |  value\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data and other attributes inherited from _Timedelta:\n",
      " |  \n",
      " |  __array_priority__ = 100\n",
      " |  \n",
      " |  __pyx_vtable__ = <capsule object NULL>\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Methods inherited from datetime.timedelta:\n",
      " |  \n",
      " |  __getattribute__(self, name, /)\n",
      " |      Return getattr(self, name).\n",
      " |  \n",
      " |  total_seconds(...)\n",
      " |      Total seconds in the duration.\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data descriptors inherited from datetime.timedelta:\n",
      " |  \n",
      " |  days\n",
      " |      Number of days.\n",
      " |  \n",
      " |  microseconds\n",
      " |      Number of microseconds (>= 0 and less than 1 second).\n",
      " |  \n",
      " |  seconds\n",
      " |      Number of seconds (>= 0 and less than 1 day).\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(pd.Timedelta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for the 5 years training period\n",
    "initial=5*365\n",
    "initial= str(initial) + \" days\"\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "#fold every 5 years\n",
    "period=5*365\n",
    "period=str(period)+ \" days\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#forecast 1 year into horizon\n",
    "horizon=365\n",
    "horizon=str(horizon) + \" days\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "df_cv=cross_validation(m,initial=initial,period=period,horizon=horizon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
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       "      <td>117544.028188</td>\n",
       "      <td>120433.775631</td>\n",
       "      <td>119960.0</td>\n",
       "      <td>1976-12-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1977-04-01</td>\n",
       "      <td>120612.896843</td>\n",
       "      <td>119185.536313</td>\n",
       "      <td>122097.578463</td>\n",
       "      <td>121513.0</td>\n",
       "      <td>1976-12-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1977-05-01</td>\n",
       "      <td>127882.997333</td>\n",
       "      <td>126384.410555</td>\n",
       "      <td>129458.594325</td>\n",
       "      <td>128884.0</td>\n",
       "      <td>1976-12-11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ds           yhat     yhat_lower     yhat_upper         y     cutoff\n",
       "0 1977-01-01  108479.056712  107208.939321  109842.068527  102445.0 1976-12-11\n",
       "1 1977-02-01  102996.080620  101599.519615  104443.262389  102416.0 1976-12-11\n",
       "2 1977-03-01  118973.287825  117544.028188  120433.775631  119960.0 1976-12-11\n",
       "3 1977-04-01  120612.896843  119185.536313  122097.578463  121513.0 1976-12-11\n",
       "4 1977-05-01  127882.997333  126384.410555  129458.594325  128884.0 1976-12-11"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cv.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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",
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       "      <th>cutoff</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>2017-08-01</td>\n",
       "      <td>273470.864466</td>\n",
       "      <td>267836.428792</td>\n",
       "      <td>279514.654916</td>\n",
       "      <td>283184.0</td>\n",
       "      <td>2016-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>2017-09-01</td>\n",
       "      <td>255592.457995</td>\n",
       "      <td>249674.135678</td>\n",
       "      <td>261107.644066</td>\n",
       "      <td>262673.0</td>\n",
       "      <td>2016-12-01</td>\n",
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       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2017-10-01</td>\n",
       "      <td>262698.709357</td>\n",
       "      <td>256774.850390</td>\n",
       "      <td>268168.049948</td>\n",
       "      <td>278937.0</td>\n",
       "      <td>2016-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2017-11-01</td>\n",
       "      <td>249351.448979</td>\n",
       "      <td>243568.803640</td>\n",
       "      <td>254754.866338</td>\n",
       "      <td>257712.0</td>\n",
       "      <td>2016-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2017-12-01</td>\n",
       "      <td>250600.367195</td>\n",
       "      <td>244957.757218</td>\n",
       "      <td>256418.012698</td>\n",
       "      <td>266535.0</td>\n",
       "      <td>2016-12-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds           yhat     yhat_lower     yhat_upper         y  \\\n",
       "103 2017-08-01  273470.864466  267836.428792  279514.654916  283184.0   \n",
       "104 2017-09-01  255592.457995  249674.135678  261107.644066  262673.0   \n",
       "105 2017-10-01  262698.709357  256774.850390  268168.049948  278937.0   \n",
       "106 2017-11-01  249351.448979  243568.803640  254754.866338  257712.0   \n",
       "107 2017-12-01  250600.367195  244957.757218  256418.012698  266535.0   \n",
       "\n",
       "        cutoff  \n",
       "103 2016-12-01  \n",
       "104 2016-12-01  \n",
       "105 2016-12-01  \n",
       "106 2016-12-01  \n",
       "107 2016-12-01  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cv.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>horizon</th>\n",
       "      <th>mse</th>\n",
       "      <th>rmse</th>\n",
       "      <th>mae</th>\n",
       "      <th>mape</th>\n",
       "      <th>mdape</th>\n",
       "      <th>smape</th>\n",
       "      <th>coverage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52 days</td>\n",
       "      <td>2.392620e+07</td>\n",
       "      <td>4891.441802</td>\n",
       "      <td>4495.785193</td>\n",
       "      <td>0.027551</td>\n",
       "      <td>0.023503</td>\n",
       "      <td>0.027137</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53 days</td>\n",
       "      <td>2.139317e+07</td>\n",
       "      <td>4625.274740</td>\n",
       "      <td>4225.237984</td>\n",
       "      <td>0.024757</td>\n",
       "      <td>0.023503</td>\n",
       "      <td>0.024464</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>54 days</td>\n",
       "      <td>1.799877e+07</td>\n",
       "      <td>4242.495209</td>\n",
       "      <td>3700.027719</td>\n",
       "      <td>0.019866</td>\n",
       "      <td>0.022254</td>\n",
       "      <td>0.019710</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>55 days</td>\n",
       "      <td>2.263701e+07</td>\n",
       "      <td>4757.836906</td>\n",
       "      <td>4206.850433</td>\n",
       "      <td>0.022844</td>\n",
       "      <td>0.023503</td>\n",
       "      <td>0.022603</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57 days</td>\n",
       "      <td>2.060908e+07</td>\n",
       "      <td>4539.722156</td>\n",
       "      <td>3958.035585</td>\n",
       "      <td>0.021211</td>\n",
       "      <td>0.022254</td>\n",
       "      <td>0.021007</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>360 days</td>\n",
       "      <td>1.815642e+07</td>\n",
       "      <td>4261.035516</td>\n",
       "      <td>3740.132970</td>\n",
       "      <td>0.019540</td>\n",
       "      <td>0.019440</td>\n",
       "      <td>0.019550</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>361 days</td>\n",
       "      <td>1.727838e+07</td>\n",
       "      <td>4156.726773</td>\n",
       "      <td>3460.297498</td>\n",
       "      <td>0.018146</td>\n",
       "      <td>0.018944</td>\n",
       "      <td>0.018166</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>362 days</td>\n",
       "      <td>3.151940e+07</td>\n",
       "      <td>5614.213845</td>\n",
       "      <td>4379.294087</td>\n",
       "      <td>0.021916</td>\n",
       "      <td>0.024308</td>\n",
       "      <td>0.021817</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>364 days</td>\n",
       "      <td>2.970923e+07</td>\n",
       "      <td>5450.617688</td>\n",
       "      <td>4208.599878</td>\n",
       "      <td>0.021275</td>\n",
       "      <td>0.021428</td>\n",
       "      <td>0.021190</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>365 days</td>\n",
       "      <td>5.477122e+07</td>\n",
       "      <td>7400.757862</td>\n",
       "      <td>5620.605584</td>\n",
       "      <td>0.026498</td>\n",
       "      <td>0.024308</td>\n",
       "      <td>0.026600</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>99 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    horizon           mse         rmse          mae      mape     mdape  \\\n",
       "0   52 days  2.392620e+07  4891.441802  4495.785193  0.027551  0.023503   \n",
       "1   53 days  2.139317e+07  4625.274740  4225.237984  0.024757  0.023503   \n",
       "2   54 days  1.799877e+07  4242.495209  3700.027719  0.019866  0.022254   \n",
       "3   55 days  2.263701e+07  4757.836906  4206.850433  0.022844  0.023503   \n",
       "4   57 days  2.060908e+07  4539.722156  3958.035585  0.021211  0.022254   \n",
       "..      ...           ...          ...          ...       ...       ...   \n",
       "94 360 days  1.815642e+07  4261.035516  3740.132970  0.019540  0.019440   \n",
       "95 361 days  1.727838e+07  4156.726773  3460.297498  0.018146  0.018944   \n",
       "96 362 days  3.151940e+07  5614.213845  4379.294087  0.021916  0.024308   \n",
       "97 364 days  2.970923e+07  5450.617688  4208.599878  0.021275  0.021428   \n",
       "98 365 days  5.477122e+07  7400.757862  5620.605584  0.026498  0.024308   \n",
       "\n",
       "       smape  coverage  \n",
       "0   0.027137       0.4  \n",
       "1   0.024464       0.4  \n",
       "2   0.019710       0.5  \n",
       "3   0.022603       0.4  \n",
       "4   0.021007       0.5  \n",
       "..       ...       ...  \n",
       "94  0.019550       0.5  \n",
       "95  0.018166       0.5  \n",
       "96  0.021817       0.4  \n",
       "97  0.021190       0.5  \n",
       "98  0.026600       0.4  \n",
       "\n",
       "[99 rows x 8 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "performance_metrics(df_cv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_cross_validation_metric(df_cv,metric=\"rmse\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "mape is important"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_cross_validation_metric(df_cv,metric=\"mape\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trend Changes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.9"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}