TS-KATS-Time-Series-Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1d3aeb61",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from kats.consts import TimeSeriesData\n",
    "from kats.models.prophet import ProphetModel, ProphetParams\n",
    "from kats.models.theta import ThetaModel, ThetaParams\n",
    "from kats.models.sarima import SARIMAModel, SARIMAParams\n",
    "from kats.models.holtwinters import HoltWintersParams, HoltWintersModel\n",
    "from kats.models.ensemble.ensemble import EnsembleParams, BaseModelParams\n",
    "from kats.models.ensemble.kats_ensemble import KatsEnsemble\n",
    "from kats.models import arima,holtwinters,linear_model,prophet,quadratic_model,sarima,theta\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "742c67e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('dataset.txt',sep=',',parse_dates=['date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7791e608",
   "metadata": {},
   "outputs": [],
   "source": [
    "main=df[df.location=='Azerbaijan']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5c399109",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>iso_code</th>\n",
       "      <th>continent</th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_smoothed</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_smoothed</th>\n",
       "      <th>...</th>\n",
       "      <th>extreme_poverty</th>\n",
       "      <th>cardiovasc_death_rate</th>\n",
       "      <th>diabetes_prevalence</th>\n",
       "      <th>female_smokers</th>\n",
       "      <th>male_smokers</th>\n",
       "      <th>handwashing_facilities</th>\n",
       "      <th>hospital_beds_per_thousand</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>human_development_index</th>\n",
       "      <th>excess_mortality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6857</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-02</td>\n",
       "      <td>336223.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>68.857</td>\n",
       "      <td>4977.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.429</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>559.812</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.3</td>\n",
       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6858</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-03</td>\n",
       "      <td>336318.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>74.571</td>\n",
       "      <td>4977.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.429</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>559.812</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.3</td>\n",
       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6859</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-04</td>\n",
       "      <td>336417.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>83.000</td>\n",
       "      <td>4978.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.429</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>559.812</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.3</td>\n",
       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6860</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-05</td>\n",
       "      <td>336479.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>86.429</td>\n",
       "      <td>4978.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.143</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>559.812</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.3</td>\n",
       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6861</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-06</td>\n",
       "      <td>336557.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>85.143</td>\n",
       "      <td>4978.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.714</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>559.812</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.3</td>\n",
       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6862</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-07</td>\n",
       "      <td>336684.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>91.000</td>\n",
       "      <td>4979.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.714</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>559.812</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.3</td>\n",
       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6863</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-08</td>\n",
       "      <td>336788.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>95.143</td>\n",
       "      <td>4980.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.714</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>559.812</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.3</td>\n",
       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6864</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>336962.0</td>\n",
       "      <td>174.0</td>\n",
       "      <td>105.571</td>\n",
       "      <td>4982.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.714</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>559.812</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.3</td>\n",
       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6865</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-10</td>\n",
       "      <td>337098.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>111.429</td>\n",
       "      <td>4984.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>...</td>\n",
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       "      <td>559.812</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.3</td>\n",
       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6866</th>\n",
       "      <td>AZE</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2021-07-11</td>\n",
       "      <td>337254.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>119.571</td>\n",
       "      <td>4984.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.857</td>\n",
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       "      <td>42.5</td>\n",
       "      <td>83.241</td>\n",
       "      <td>4.7</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.756</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "     iso_code continent    location       date  total_cases  new_cases  \\\n",
       "6857      AZE      Asia  Azerbaijan 2021-07-02     336223.0      101.0   \n",
       "6858      AZE      Asia  Azerbaijan 2021-07-03     336318.0       95.0   \n",
       "6859      AZE      Asia  Azerbaijan 2021-07-04     336417.0       99.0   \n",
       "6860      AZE      Asia  Azerbaijan 2021-07-05     336479.0       62.0   \n",
       "6861      AZE      Asia  Azerbaijan 2021-07-06     336557.0       78.0   \n",
       "6862      AZE      Asia  Azerbaijan 2021-07-07     336684.0      127.0   \n",
       "6863      AZE      Asia  Azerbaijan 2021-07-08     336788.0      104.0   \n",
       "6864      AZE      Asia  Azerbaijan 2021-07-09     336962.0      174.0   \n",
       "6865      AZE      Asia  Azerbaijan 2021-07-10     337098.0      136.0   \n",
       "6866      AZE      Asia  Azerbaijan 2021-07-11     337254.0      156.0   \n",
       "\n",
       "      new_cases_smoothed  total_deaths  new_deaths  new_deaths_smoothed  ...  \\\n",
       "6857              68.857        4977.0         2.0                1.429  ...   \n",
       "6858              74.571        4977.0         0.0                1.429  ...   \n",
       "6859              83.000        4978.0         1.0                1.429  ...   \n",
       "6860              86.429        4978.0         0.0                1.143  ...   \n",
       "6861              85.143        4978.0         0.0                0.714  ...   \n",
       "6862              91.000        4979.0         1.0                0.714  ...   \n",
       "6863              95.143        4980.0         1.0                0.714  ...   \n",
       "6864             105.571        4982.0         2.0                0.714  ...   \n",
       "6865             111.429        4984.0         2.0                1.000  ...   \n",
       "6866             119.571        4984.0         0.0                0.857  ...   \n",
       "\n",
       "      extreme_poverty  cardiovasc_death_rate  diabetes_prevalence  \\\n",
       "6857              NaN                559.812                 7.11   \n",
       "6858              NaN                559.812                 7.11   \n",
       "6859              NaN                559.812                 7.11   \n",
       "6860              NaN                559.812                 7.11   \n",
       "6861              NaN                559.812                 7.11   \n",
       "6862              NaN                559.812                 7.11   \n",
       "6863              NaN                559.812                 7.11   \n",
       "6864              NaN                559.812                 7.11   \n",
       "6865              NaN                559.812                 7.11   \n",
       "6866              NaN                559.812                 7.11   \n",
       "\n",
       "      female_smokers  male_smokers  handwashing_facilities  \\\n",
       "6857             0.3          42.5                  83.241   \n",
       "6858             0.3          42.5                  83.241   \n",
       "6859             0.3          42.5                  83.241   \n",
       "6860             0.3          42.5                  83.241   \n",
       "6861             0.3          42.5                  83.241   \n",
       "6862             0.3          42.5                  83.241   \n",
       "6863             0.3          42.5                  83.241   \n",
       "6864             0.3          42.5                  83.241   \n",
       "6865             0.3          42.5                  83.241   \n",
       "6866             0.3          42.5                  83.241   \n",
       "\n",
       "      hospital_beds_per_thousand  life_expectancy  human_development_index  \\\n",
       "6857                         4.7             73.0                    0.756   \n",
       "6858                         4.7             73.0                    0.756   \n",
       "6859                         4.7             73.0                    0.756   \n",
       "6860                         4.7             73.0                    0.756   \n",
       "6861                         4.7             73.0                    0.756   \n",
       "6862                         4.7             73.0                    0.756   \n",
       "6863                         4.7             73.0                    0.756   \n",
       "6864                         4.7             73.0                    0.756   \n",
       "6865                         4.7             73.0                    0.756   \n",
       "6866                         4.7             73.0                    0.756   \n",
       "\n",
       "      excess_mortality  \n",
       "6857               NaN  \n",
       "6858               NaN  \n",
       "6859               NaN  \n",
       "6860               NaN  \n",
       "6861               NaN  \n",
       "6862               NaN  \n",
       "6863               NaN  \n",
       "6864               NaN  \n",
       "6865               NaN  \n",
       "6866               NaN  \n",
       "\n",
       "[10 rows x 60 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
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   "source": [
    "main.tail(10)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "282fdd6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "main=main[['date','new_cases','total_cases',\n",
    "           'new_deaths','total_deaths','new_tests',\n",
    "           'total_tests','new_vaccinations',\n",
    "           'total_vaccinations','people_vaccinated']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5dc69a3b",
   "metadata": {},
   "outputs": [
    {
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       "      <th>new_cases</th>\n",
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       "      <th>6857</th>\n",
       "      <td>2021-07-02</td>\n",
       "      <td>101.0</td>\n",
       "      <td>336223.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4977.0</td>\n",
       "      <td>9851.0</td>\n",
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       "      <td>3670729.0</td>\n",
       "      <td>2290808.0</td>\n",
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       "    <tr>\n",
       "      <th>6858</th>\n",
       "      <td>2021-07-03</td>\n",
       "      <td>95.0</td>\n",
       "      <td>336318.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4977.0</td>\n",
       "      <td>10428.0</td>\n",
       "      <td>3778410.0</td>\n",
       "      <td>69718.0</td>\n",
       "      <td>3740447.0</td>\n",
       "      <td>2321863.0</td>\n",
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       "    <tr>\n",
       "      <th>6859</th>\n",
       "      <td>2021-07-04</td>\n",
       "      <td>99.0</td>\n",
       "      <td>336417.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4978.0</td>\n",
       "      <td>8679.0</td>\n",
       "      <td>3787089.0</td>\n",
       "      <td>52317.0</td>\n",
       "      <td>3792764.0</td>\n",
       "      <td>2345077.0</td>\n",
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       "    <tr>\n",
       "      <th>6860</th>\n",
       "      <td>2021-07-05</td>\n",
       "      <td>62.0</td>\n",
       "      <td>336479.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4978.0</td>\n",
       "      <td>5951.0</td>\n",
       "      <td>3793040.0</td>\n",
       "      <td>769.0</td>\n",
       "      <td>3793533.0</td>\n",
       "      <td>2345371.0</td>\n",
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       "    <tr>\n",
       "      <th>6861</th>\n",
       "      <td>2021-07-06</td>\n",
       "      <td>78.0</td>\n",
       "      <td>336557.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4978.0</td>\n",
       "      <td>9952.0</td>\n",
       "      <td>3802992.0</td>\n",
       "      <td>61922.0</td>\n",
       "      <td>3855455.0</td>\n",
       "      <td>2371796.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6862</th>\n",
       "      <td>2021-07-07</td>\n",
       "      <td>127.0</td>\n",
       "      <td>336684.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4979.0</td>\n",
       "      <td>10025.0</td>\n",
       "      <td>3813017.0</td>\n",
       "      <td>55169.0</td>\n",
       "      <td>3910624.0</td>\n",
       "      <td>2396007.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6863</th>\n",
       "      <td>2021-07-08</td>\n",
       "      <td>104.0</td>\n",
       "      <td>336788.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4980.0</td>\n",
       "      <td>8709.0</td>\n",
       "      <td>3821726.0</td>\n",
       "      <td>53478.0</td>\n",
       "      <td>3964102.0</td>\n",
       "      <td>2417173.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6864</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>174.0</td>\n",
       "      <td>336962.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4982.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51510.0</td>\n",
       "      <td>4015612.0</td>\n",
       "      <td>2437929.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6865</th>\n",
       "      <td>2021-07-10</td>\n",
       "      <td>136.0</td>\n",
       "      <td>337098.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4984.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53606.0</td>\n",
       "      <td>4069218.0</td>\n",
       "      <td>2459102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6866</th>\n",
       "      <td>2021-07-11</td>\n",
       "      <td>156.0</td>\n",
       "      <td>337254.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4984.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38732.0</td>\n",
       "      <td>4107950.0</td>\n",
       "      <td>2474911.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date  new_cases  total_cases  new_deaths  total_deaths  new_tests  \\\n",
       "6857 2021-07-02      101.0     336223.0         2.0        4977.0     9851.0   \n",
       "6858 2021-07-03       95.0     336318.0         0.0        4977.0    10428.0   \n",
       "6859 2021-07-04       99.0     336417.0         1.0        4978.0     8679.0   \n",
       "6860 2021-07-05       62.0     336479.0         0.0        4978.0     5951.0   \n",
       "6861 2021-07-06       78.0     336557.0         0.0        4978.0     9952.0   \n",
       "6862 2021-07-07      127.0     336684.0         1.0        4979.0    10025.0   \n",
       "6863 2021-07-08      104.0     336788.0         1.0        4980.0     8709.0   \n",
       "6864 2021-07-09      174.0     336962.0         2.0        4982.0        NaN   \n",
       "6865 2021-07-10      136.0     337098.0         2.0        4984.0        NaN   \n",
       "6866 2021-07-11      156.0     337254.0         0.0        4984.0        NaN   \n",
       "\n",
       "      total_tests  new_vaccinations  total_vaccinations  people_vaccinated  \n",
       "6857    3767982.0           73621.0           3670729.0          2290808.0  \n",
       "6858    3778410.0           69718.0           3740447.0          2321863.0  \n",
       "6859    3787089.0           52317.0           3792764.0          2345077.0  \n",
       "6860    3793040.0             769.0           3793533.0          2345371.0  \n",
       "6861    3802992.0           61922.0           3855455.0          2371796.0  \n",
       "6862    3813017.0           55169.0           3910624.0          2396007.0  \n",
       "6863    3821726.0           53478.0           3964102.0          2417173.0  \n",
       "6864          NaN           51510.0           4015612.0          2437929.0  \n",
       "6865          NaN           53606.0           4069218.0          2459102.0  \n",
       "6866          NaN           38732.0           4107950.0          2474911.0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "78d15554",
   "metadata": {},
   "outputs": [],
   "source": [
    "main.fillna(0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3d8f630b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date                  0\n",
       "new_cases             0\n",
       "total_cases           0\n",
       "new_deaths            0\n",
       "total_deaths          0\n",
       "new_tests             0\n",
       "total_tests           0\n",
       "new_vaccinations      0\n",
       "total_vaccinations    0\n",
       "people_vaccinated     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "916421c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "main.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5ac84f6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "main.drop('index',axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1927666a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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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>new_cases</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_tests</th>\n",
       "      <th>total_tests</th>\n",
       "      <th>new_vaccinations</th>\n",
       "      <th>total_vaccinations</th>\n",
       "      <th>people_vaccinated</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>2021-07-02</td>\n",
       "      <td>101.0</td>\n",
       "      <td>336223.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4977.0</td>\n",
       "      <td>9851.0</td>\n",
       "      <td>3767982.0</td>\n",
       "      <td>73621.0</td>\n",
       "      <td>3670729.0</td>\n",
       "      <td>2290808.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>2021-07-03</td>\n",
       "      <td>95.0</td>\n",
       "      <td>336318.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4977.0</td>\n",
       "      <td>10428.0</td>\n",
       "      <td>3778410.0</td>\n",
       "      <td>69718.0</td>\n",
       "      <td>3740447.0</td>\n",
       "      <td>2321863.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>2021-07-04</td>\n",
       "      <td>99.0</td>\n",
       "      <td>336417.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4978.0</td>\n",
       "      <td>8679.0</td>\n",
       "      <td>3787089.0</td>\n",
       "      <td>52317.0</td>\n",
       "      <td>3792764.0</td>\n",
       "      <td>2345077.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>2021-07-05</td>\n",
       "      <td>62.0</td>\n",
       "      <td>336479.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4978.0</td>\n",
       "      <td>5951.0</td>\n",
       "      <td>3793040.0</td>\n",
       "      <td>769.0</td>\n",
       "      <td>3793533.0</td>\n",
       "      <td>2345371.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>2021-07-06</td>\n",
       "      <td>78.0</td>\n",
       "      <td>336557.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4978.0</td>\n",
       "      <td>9952.0</td>\n",
       "      <td>3802992.0</td>\n",
       "      <td>61922.0</td>\n",
       "      <td>3855455.0</td>\n",
       "      <td>2371796.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>2021-07-07</td>\n",
       "      <td>127.0</td>\n",
       "      <td>336684.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4979.0</td>\n",
       "      <td>10025.0</td>\n",
       "      <td>3813017.0</td>\n",
       "      <td>55169.0</td>\n",
       "      <td>3910624.0</td>\n",
       "      <td>2396007.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>2021-07-08</td>\n",
       "      <td>104.0</td>\n",
       "      <td>336788.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4980.0</td>\n",
       "      <td>8709.0</td>\n",
       "      <td>3821726.0</td>\n",
       "      <td>53478.0</td>\n",
       "      <td>3964102.0</td>\n",
       "      <td>2417173.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>174.0</td>\n",
       "      <td>336962.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4982.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>51510.0</td>\n",
       "      <td>4015612.0</td>\n",
       "      <td>2437929.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>2021-07-10</td>\n",
       "      <td>136.0</td>\n",
       "      <td>337098.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4984.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>53606.0</td>\n",
       "      <td>4069218.0</td>\n",
       "      <td>2459102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>2021-07-11</td>\n",
       "      <td>156.0</td>\n",
       "      <td>337254.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4984.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38732.0</td>\n",
       "      <td>4107950.0</td>\n",
       "      <td>2474911.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date  new_cases  total_cases  new_deaths  total_deaths  new_tests  \\\n",
       "488 2021-07-02      101.0     336223.0         2.0        4977.0     9851.0   \n",
       "489 2021-07-03       95.0     336318.0         0.0        4977.0    10428.0   \n",
       "490 2021-07-04       99.0     336417.0         1.0        4978.0     8679.0   \n",
       "491 2021-07-05       62.0     336479.0         0.0        4978.0     5951.0   \n",
       "492 2021-07-06       78.0     336557.0         0.0        4978.0     9952.0   \n",
       "493 2021-07-07      127.0     336684.0         1.0        4979.0    10025.0   \n",
       "494 2021-07-08      104.0     336788.0         1.0        4980.0     8709.0   \n",
       "495 2021-07-09      174.0     336962.0         2.0        4982.0        0.0   \n",
       "496 2021-07-10      136.0     337098.0         2.0        4984.0        0.0   \n",
       "497 2021-07-11      156.0     337254.0         0.0        4984.0        0.0   \n",
       "\n",
       "     total_tests  new_vaccinations  total_vaccinations  people_vaccinated  \n",
       "488    3767982.0           73621.0           3670729.0          2290808.0  \n",
       "489    3778410.0           69718.0           3740447.0          2321863.0  \n",
       "490    3787089.0           52317.0           3792764.0          2345077.0  \n",
       "491    3793040.0             769.0           3793533.0          2345371.0  \n",
       "492    3802992.0           61922.0           3855455.0          2371796.0  \n",
       "493    3813017.0           55169.0           3910624.0          2396007.0  \n",
       "494    3821726.0           53478.0           3964102.0          2417173.0  \n",
       "495          0.0           51510.0           4015612.0          2437929.0  \n",
       "496          0.0           53606.0           4069218.0          2459102.0  \n",
       "497          0.0           38732.0           4107950.0          2474911.0  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "742a34e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=main[['date','new_cases']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b1a5c49a",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.columns=['time','value']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4e5befa0",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=TimeSeriesData(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fab78620",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(cols=['value'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "feaf6ff9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
     ]
    },
    {
     "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>time</th>\n",
       "      <th>fcst</th>\n",
       "      <th>fcst_lower</th>\n",
       "      <th>fcst_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>160.138626</td>\n",
       "      <td>-885.649427</td>\n",
       "      <td>1228.817160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-07-13</td>\n",
       "      <td>418.509420</td>\n",
       "      <td>-711.830129</td>\n",
       "      <td>1384.322252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-07-14</td>\n",
       "      <td>417.400188</td>\n",
       "      <td>-676.374167</td>\n",
       "      <td>1541.114812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-07-15</td>\n",
       "      <td>421.277783</td>\n",
       "      <td>-770.590703</td>\n",
       "      <td>1516.086243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-07-16</td>\n",
       "      <td>398.696873</td>\n",
       "      <td>-722.972751</td>\n",
       "      <td>1544.290284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-07-17</td>\n",
       "      <td>389.118423</td>\n",
       "      <td>-732.354089</td>\n",
       "      <td>1450.208443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-07-18</td>\n",
       "      <td>407.921008</td>\n",
       "      <td>-749.516588</td>\n",
       "      <td>1467.960642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-07-19</td>\n",
       "      <td>128.521773</td>\n",
       "      <td>-1014.441300</td>\n",
       "      <td>1192.330396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-07-20</td>\n",
       "      <td>386.892568</td>\n",
       "      <td>-712.591175</td>\n",
       "      <td>1422.329886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-07-21</td>\n",
       "      <td>385.783335</td>\n",
       "      <td>-680.398952</td>\n",
       "      <td>1430.785128</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        time        fcst   fcst_lower   fcst_upper\n",
       "0 2021-07-12  160.138626  -885.649427  1228.817160\n",
       "1 2021-07-13  418.509420  -711.830129  1384.322252\n",
       "2 2021-07-14  417.400188  -676.374167  1541.114812\n",
       "3 2021-07-15  421.277783  -770.590703  1516.086243\n",
       "4 2021-07-16  398.696873  -722.972751  1544.290284\n",
       "5 2021-07-17  389.118423  -732.354089  1450.208443\n",
       "6 2021-07-18  407.921008  -749.516588  1467.960642\n",
       "7 2021-07-19  128.521773 -1014.441300  1192.330396\n",
       "8 2021-07-20  386.892568  -712.591175  1422.329886\n",
       "9 2021-07-21  385.783335  -680.398952  1430.785128"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parameters = ProphetParams(seasonality_mode='additive')\n",
    "model = ProphetModel(data, parameters)\n",
    "model.fit()\n",
    "forecast = model.predict(steps=30, freq=\"d\")\n",
    "forecast.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c9381859",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "acf6ae82",
   "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>time</th>\n",
       "      <th>fcst</th>\n",
       "      <th>fcst_lower</th>\n",
       "      <th>fcst_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>149.046138</td>\n",
       "      <td>-177.204827</td>\n",
       "      <td>475.297102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>2021-07-13</td>\n",
       "      <td>149.889049</td>\n",
       "      <td>-218.014206</td>\n",
       "      <td>517.792305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>2021-07-14</td>\n",
       "      <td>150.731961</td>\n",
       "      <td>-254.565360</td>\n",
       "      <td>556.029282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>2021-07-15</td>\n",
       "      <td>151.574873</td>\n",
       "      <td>-287.946494</td>\n",
       "      <td>591.096240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>2021-07-16</td>\n",
       "      <td>152.417785</td>\n",
       "      <td>-318.848748</td>\n",
       "      <td>623.684318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>2021-07-17</td>\n",
       "      <td>153.260697</td>\n",
       "      <td>-347.743553</td>\n",
       "      <td>654.264947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>2021-07-18</td>\n",
       "      <td>154.103608</td>\n",
       "      <td>-374.969517</td>\n",
       "      <td>683.176734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>2021-07-19</td>\n",
       "      <td>154.946520</td>\n",
       "      <td>-400.779568</td>\n",
       "      <td>710.672608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>2021-07-20</td>\n",
       "      <td>155.789432</td>\n",
       "      <td>-425.368549</td>\n",
       "      <td>736.947413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>2021-07-21</td>\n",
       "      <td>156.632344</td>\n",
       "      <td>-448.890333</td>\n",
       "      <td>762.155020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          time        fcst  fcst_lower  fcst_upper\n",
       "498 2021-07-12  149.046138 -177.204827  475.297102\n",
       "499 2021-07-13  149.889049 -218.014206  517.792305\n",
       "500 2021-07-14  150.731961 -254.565360  556.029282\n",
       "501 2021-07-15  151.574873 -287.946494  591.096240\n",
       "502 2021-07-16  152.417785 -318.848748  623.684318\n",
       "503 2021-07-17  153.260697 -347.743553  654.264947\n",
       "504 2021-07-18  154.103608 -374.969517  683.176734\n",
       "505 2021-07-19  154.946520 -400.779568  710.672608\n",
       "506 2021-07-20  155.789432 -425.368549  736.947413\n",
       "507 2021-07-21  156.632344 -448.890333  762.155020"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parameters = ThetaParams(m=1)\n",
    "model = ThetaModel(data=data, params=parameters)\n",
    "model.fit()\n",
    "forecast = model.predict(steps=100, alpha=0.2)\n",
    "forecast.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c335817e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "be3a7c0b",
   "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>time</th>\n",
       "      <th>fcst</th>\n",
       "      <th>fcst_lower</th>\n",
       "      <th>fcst_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>161.057756</td>\n",
       "      <td>129.038019</td>\n",
       "      <td>193.077493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>2021-07-13</td>\n",
       "      <td>168.279073</td>\n",
       "      <td>83.245276</td>\n",
       "      <td>253.312870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>2021-07-14</td>\n",
       "      <td>181.210320</td>\n",
       "      <td>43.162464</td>\n",
       "      <td>319.258176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>2021-07-15</td>\n",
       "      <td>188.431638</td>\n",
       "      <td>-2.630279</td>\n",
       "      <td>379.493554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>2021-07-16</td>\n",
       "      <td>201.362884</td>\n",
       "      <td>-42.713092</td>\n",
       "      <td>445.438860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>2021-07-17</td>\n",
       "      <td>208.584202</td>\n",
       "      <td>-88.505834</td>\n",
       "      <td>505.674238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>2021-07-18</td>\n",
       "      <td>221.515449</td>\n",
       "      <td>-128.588647</td>\n",
       "      <td>571.619544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>2021-07-19</td>\n",
       "      <td>228.736766</td>\n",
       "      <td>-174.381389</td>\n",
       "      <td>631.854921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>2021-07-20</td>\n",
       "      <td>241.668013</td>\n",
       "      <td>-214.464202</td>\n",
       "      <td>697.800228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>2021-07-21</td>\n",
       "      <td>248.889331</td>\n",
       "      <td>-260.256944</td>\n",
       "      <td>758.035605</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          time        fcst  fcst_lower  fcst_upper\n",
       "498 2021-07-12  161.057756  129.038019  193.077493\n",
       "499 2021-07-13  168.279073   83.245276  253.312870\n",
       "500 2021-07-14  181.210320   43.162464  319.258176\n",
       "501 2021-07-15  188.431638   -2.630279  379.493554\n",
       "502 2021-07-16  201.362884  -42.713092  445.438860\n",
       "503 2021-07-17  208.584202  -88.505834  505.674238\n",
       "504 2021-07-18  221.515449 -128.588647  571.619544\n",
       "505 2021-07-19  228.736766 -174.381389  631.854921\n",
       "506 2021-07-20  241.668013 -214.464202  697.800228\n",
       "507 2021-07-21  248.889331 -260.256944  758.035605"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parameters = HoltWintersParams(\n",
    "            trend=\"add\",\n",
    "            damped=False,\n",
    "            seasonal=\"add\",\n",
    "            seasonal_periods=2,\n",
    "        )\n",
    "model = HoltWintersModel(\n",
    "    data=data, \n",
    "    params=parameters)\n",
    "model.fit()\n",
    "forecast = model.predict(steps=30, alpha = 0.2)\n",
    "forecast.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3bfc0525",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d9d07416",
   "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>time</th>\n",
       "      <th>fcst</th>\n",
       "      <th>fcst_lower</th>\n",
       "      <th>fcst_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>206.413590</td>\n",
       "      <td>-259.881441</td>\n",
       "      <td>672.708620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>2021-07-13</td>\n",
       "      <td>88.320393</td>\n",
       "      <td>-434.422200</td>\n",
       "      <td>611.062985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>2021-07-14</td>\n",
       "      <td>170.593741</td>\n",
       "      <td>-426.194733</td>\n",
       "      <td>767.382215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>2021-07-15</td>\n",
       "      <td>76.694414</td>\n",
       "      <td>-613.949242</td>\n",
       "      <td>767.338070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>2021-07-16</td>\n",
       "      <td>55.368848</td>\n",
       "      <td>-674.489063</td>\n",
       "      <td>785.226759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>2021-07-17</td>\n",
       "      <td>133.123217</td>\n",
       "      <td>-678.833623</td>\n",
       "      <td>945.080056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>2021-07-18</td>\n",
       "      <td>81.341653</td>\n",
       "      <td>-769.494780</td>\n",
       "      <td>932.178085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>2021-07-19</td>\n",
       "      <td>200.300559</td>\n",
       "      <td>-710.837321</td>\n",
       "      <td>1111.438439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>2021-07-20</td>\n",
       "      <td>148.627664</td>\n",
       "      <td>-806.014747</td>\n",
       "      <td>1103.270075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>2021-07-21</td>\n",
       "      <td>17.011996</td>\n",
       "      <td>-983.859829</td>\n",
       "      <td>1017.883821</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          time        fcst  fcst_lower   fcst_upper\n",
       "498 2021-07-12  206.413590 -259.881441   672.708620\n",
       "499 2021-07-13   88.320393 -434.422200   611.062985\n",
       "500 2021-07-14  170.593741 -426.194733   767.382215\n",
       "501 2021-07-15   76.694414 -613.949242   767.338070\n",
       "502 2021-07-16   55.368848 -674.489063   785.226759\n",
       "503 2021-07-17  133.123217 -678.833623   945.080056\n",
       "504 2021-07-18   81.341653 -769.494780   932.178085\n",
       "505 2021-07-19  200.300559 -710.837321  1111.438439\n",
       "506 2021-07-20  148.627664 -806.014747  1103.270075\n",
       "507 2021-07-21   17.011996 -983.859829  1017.883821"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parameters = SARIMAParams(\n",
    "    p = 2, \n",
    "    d=1, \n",
    "    q=1, \n",
    "    trend = 'ct', \n",
    "    seasonal_order=(1,0,1,12)\n",
    "    )\n",
    "model = SARIMAModel(data=data, params=parameters)\n",
    "model.fit()\n",
    "forecast = model.predict(\n",
    "    steps=30, \n",
    "    freq=\"d\"\n",
    "    )\n",
    "forecast.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e4af0339",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6fb30d58",
   "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>time</th>\n",
       "      <th>fcst</th>\n",
       "      <th>fcst_lower</th>\n",
       "      <th>fcst_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>339.328054</td>\n",
       "      <td>-706.101400</td>\n",
       "      <td>1503.969684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-07-13</td>\n",
       "      <td>332.515005</td>\n",
       "      <td>-673.085402</td>\n",
       "      <td>1463.023564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-07-14</td>\n",
       "      <td>325.567700</td>\n",
       "      <td>-699.650862</td>\n",
       "      <td>1444.915861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-07-15</td>\n",
       "      <td>318.757274</td>\n",
       "      <td>-702.660975</td>\n",
       "      <td>1526.848868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-07-16</td>\n",
       "      <td>311.817952</td>\n",
       "      <td>-699.059047</td>\n",
       "      <td>1398.090310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-07-17</td>\n",
       "      <td>304.971157</td>\n",
       "      <td>-754.718770</td>\n",
       "      <td>1447.617262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-07-18</td>\n",
       "      <td>299.970835</td>\n",
       "      <td>-695.384119</td>\n",
       "      <td>1433.601777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-07-19</td>\n",
       "      <td>294.721011</td>\n",
       "      <td>-708.106509</td>\n",
       "      <td>1413.160574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-07-20</td>\n",
       "      <td>287.769840</td>\n",
       "      <td>-723.015638</td>\n",
       "      <td>1411.212343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-07-21</td>\n",
       "      <td>280.684412</td>\n",
       "      <td>-716.476276</td>\n",
       "      <td>1437.822566</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        time        fcst  fcst_lower   fcst_upper\n",
       "0 2021-07-12  339.328054 -706.101400  1503.969684\n",
       "1 2021-07-13  332.515005 -673.085402  1463.023564\n",
       "2 2021-07-14  325.567700 -699.650862  1444.915861\n",
       "3 2021-07-15  318.757274 -702.660975  1526.848868\n",
       "4 2021-07-16  311.817952 -699.059047  1398.090310\n",
       "5 2021-07-17  304.971157 -754.718770  1447.617262\n",
       "6 2021-07-18  299.970835 -695.384119  1433.601777\n",
       "7 2021-07-19  294.721011 -708.106509  1413.160574\n",
       "8 2021-07-20  287.769840 -723.015638  1411.212343\n",
       "9 2021-07-21  280.684412 -716.476276  1437.822566"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parameters = EnsembleParams(\n",
    "            [\n",
    "                BaseModelParams(\"prophet\", prophet.ProphetParams()),\n",
    "                BaseModelParams(\"linear\", linear_model.LinearModelParams()),\n",
    "                BaseModelParams(\"quadratic\", quadratic_model.QuadraticModelParams()),\n",
    "                BaseModelParams(\"theta\", theta.ThetaParams(m=12)),\n",
    "                BaseModelParams(\n",
    "                    \"sarima\",\n",
    "                    sarima.SARIMAParams(\n",
    "                        p=2,\n",
    "                        d=1,\n",
    "                        q=1,\n",
    "                        trend=\"ct\",\n",
    "                        seasonal_order=(1, 0, 1, 12),\n",
    "                        enforce_invertibility=False,\n",
    "                        enforce_stationarity=False,\n",
    "                    )\n",
    "                ),\n",
    "                BaseModelParams(\"arima\", arima.ARIMAParams(p=1, d=1, q=1))\n",
    "\n",
    "            ]\n",
    "        )\n",
    "\n",
    "KatsEnsembleParam = {\n",
    "    \"models\": parameters,\n",
    "    \"aggregation\": \"median\",\n",
    "    \"seasonality_length\": 1,\n",
    "    \"decomposition_method\": \"additive\",\n",
    "}\n",
    "\n",
    "model = KatsEnsemble(\n",
    "    data=data, \n",
    "    params=KatsEnsembleParam\n",
    "    )\n",
    "\n",
    "model.fit()\n",
    "\n",
    "forecast = model.predict(steps=30)\n",
    "\n",
    "model.aggregate().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "317a506f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.plot()"
   ]
  }
 ],
 "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}