Forecasting - Inflation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "248558a9",
   "metadata": {},
   "source": [
    "### Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fd9731a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from pandas.plotting import lag_plot\n",
    "from datetime import datetime as dt\n",
    "import seaborn as sns\n",
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "import statsmodels.graphics.tsaplots as tsa_plots\n",
    "from pandas import Grouper\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab77c24d",
   "metadata": {},
   "source": [
    "### Import Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "676f37c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Inflation, average consumer prices(%)</th>\n",
       "      <th>Inflation, end of period consumer prices(%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-01</th>\n",
       "      <td>11.346</td>\n",
       "      <td>12.819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-01-01</th>\n",
       "      <td>12.654</td>\n",
       "      <td>9.048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-01-01</th>\n",
       "      <td>7.736</td>\n",
       "      <td>10.420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-01-01</th>\n",
       "      <td>12.558</td>\n",
       "      <td>10.398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-01</th>\n",
       "      <td>6.517</td>\n",
       "      <td>5.144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985-01-01</th>\n",
       "      <td>6.251</td>\n",
       "      <td>8.920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986-01-01</th>\n",
       "      <td>8.889</td>\n",
       "      <td>7.464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987-01-01</th>\n",
       "      <td>9.059</td>\n",
       "      <td>9.743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988-01-01</th>\n",
       "      <td>7.214</td>\n",
       "      <td>5.040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989-01-01</th>\n",
       "      <td>4.569</td>\n",
       "      <td>6.639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-01-01</th>\n",
       "      <td>11.197</td>\n",
       "      <td>15.019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-01-01</th>\n",
       "      <td>13.483</td>\n",
       "      <td>13.388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992-01-01</th>\n",
       "      <td>9.863</td>\n",
       "      <td>5.831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-01-01</th>\n",
       "      <td>7.279</td>\n",
       "      <td>9.504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994-01-01</th>\n",
       "      <td>10.275</td>\n",
       "      <td>9.811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-01-01</th>\n",
       "      <td>9.962</td>\n",
       "      <td>8.820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996-01-01</th>\n",
       "      <td>9.432</td>\n",
       "      <td>10.632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997-01-01</th>\n",
       "      <td>6.842</td>\n",
       "      <td>9.039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998-01-01</th>\n",
       "      <td>13.127</td>\n",
       "      <td>8.988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-01-01</th>\n",
       "      <td>5.698</td>\n",
       "      <td>3.683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-01</th>\n",
       "      <td>3.831</td>\n",
       "      <td>2.934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-01-01</th>\n",
       "      <td>4.311</td>\n",
       "      <td>5.101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01</th>\n",
       "      <td>3.981</td>\n",
       "      <td>3.783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-01-01</th>\n",
       "      <td>3.864</td>\n",
       "      <td>3.989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-01</th>\n",
       "      <td>3.824</td>\n",
       "      <td>4.233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>4.404</td>\n",
       "      <td>4.882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-01-01</th>\n",
       "      <td>6.697</td>\n",
       "      <td>7.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-01-01</th>\n",
       "      <td>6.204</td>\n",
       "      <td>6.283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01</th>\n",
       "      <td>9.089</td>\n",
       "      <td>9.360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-01</th>\n",
       "      <td>12.314</td>\n",
       "      <td>10.538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>10.528</td>\n",
       "      <td>9.166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>9.500</td>\n",
       "      <td>8.781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01</th>\n",
       "      <td>10.000</td>\n",
       "      <td>10.488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>9.400</td>\n",
       "      <td>7.663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>5.800</td>\n",
       "      <td>5.272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-01</th>\n",
       "      <td>4.900</td>\n",
       "      <td>5.259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>4.500</td>\n",
       "      <td>3.569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>3.602</td>\n",
       "      <td>4.594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
       "      <td>3.428</td>\n",
       "      <td>2.465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01</th>\n",
       "      <td>4.762</td>\n",
       "      <td>6.668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>6.175</td>\n",
       "      <td>4.867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-01</th>\n",
       "      <td>5.557</td>\n",
       "      <td>5.491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01</th>\n",
       "      <td>4.876</td>\n",
       "      <td>4.910</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation, average consumer prices(%)  \\\n",
       "Year                                                \n",
       "1980-01-01                                 11.346   \n",
       "1981-01-01                                 12.654   \n",
       "1982-01-01                                  7.736   \n",
       "1983-01-01                                 12.558   \n",
       "1984-01-01                                  6.517   \n",
       "1985-01-01                                  6.251   \n",
       "1986-01-01                                  8.889   \n",
       "1987-01-01                                  9.059   \n",
       "1988-01-01                                  7.214   \n",
       "1989-01-01                                  4.569   \n",
       "1990-01-01                                 11.197   \n",
       "1991-01-01                                 13.483   \n",
       "1992-01-01                                  9.863   \n",
       "1993-01-01                                  7.279   \n",
       "1994-01-01                                 10.275   \n",
       "1995-01-01                                  9.962   \n",
       "1996-01-01                                  9.432   \n",
       "1997-01-01                                  6.842   \n",
       "1998-01-01                                 13.127   \n",
       "1999-01-01                                  5.698   \n",
       "2000-01-01                                  3.831   \n",
       "2001-01-01                                  4.311   \n",
       "2002-01-01                                  3.981   \n",
       "2003-01-01                                  3.864   \n",
       "2004-01-01                                  3.824   \n",
       "2005-01-01                                  4.404   \n",
       "2006-01-01                                  6.697   \n",
       "2007-01-01                                  6.204   \n",
       "2008-01-01                                  9.089   \n",
       "2009-01-01                                 12.314   \n",
       "2010-01-01                                 10.528   \n",
       "2011-01-01                                  9.500   \n",
       "2012-01-01                                 10.000   \n",
       "2013-01-01                                  9.400   \n",
       "2014-01-01                                  5.800   \n",
       "2015-01-01                                  4.900   \n",
       "2016-01-01                                  4.500   \n",
       "2017-01-01                                  3.602   \n",
       "2018-01-01                                  3.428   \n",
       "2019-01-01                                  4.762   \n",
       "2020-01-01                                  6.175   \n",
       "2021-01-01                                  5.557   \n",
       "2022-01-01                                  4.876   \n",
       "\n",
       "            Inflation, end of period consumer prices(%)  \n",
       "Year                                                     \n",
       "1980-01-01                                       12.819  \n",
       "1981-01-01                                        9.048  \n",
       "1982-01-01                                       10.420  \n",
       "1983-01-01                                       10.398  \n",
       "1984-01-01                                        5.144  \n",
       "1985-01-01                                        8.920  \n",
       "1986-01-01                                        7.464  \n",
       "1987-01-01                                        9.743  \n",
       "1988-01-01                                        5.040  \n",
       "1989-01-01                                        6.639  \n",
       "1990-01-01                                       15.019  \n",
       "1991-01-01                                       13.388  \n",
       "1992-01-01                                        5.831  \n",
       "1993-01-01                                        9.504  \n",
       "1994-01-01                                        9.811  \n",
       "1995-01-01                                        8.820  \n",
       "1996-01-01                                       10.632  \n",
       "1997-01-01                                        9.039  \n",
       "1998-01-01                                        8.988  \n",
       "1999-01-01                                        3.683  \n",
       "2000-01-01                                        2.934  \n",
       "2001-01-01                                        5.101  \n",
       "2002-01-01                                        3.783  \n",
       "2003-01-01                                        3.989  \n",
       "2004-01-01                                        4.233  \n",
       "2005-01-01                                        4.882  \n",
       "2006-01-01                                        7.001  \n",
       "2007-01-01                                        6.283  \n",
       "2008-01-01                                        9.360  \n",
       "2009-01-01                                       10.538  \n",
       "2010-01-01                                        9.166  \n",
       "2011-01-01                                        8.781  \n",
       "2012-01-01                                       10.488  \n",
       "2013-01-01                                        7.663  \n",
       "2014-01-01                                        5.272  \n",
       "2015-01-01                                        5.259  \n",
       "2016-01-01                                        3.569  \n",
       "2017-01-01                                        4.594  \n",
       "2018-01-01                                        2.465  \n",
       "2019-01-01                                        6.668  \n",
       "2020-01-01                                        4.867  \n",
       "2021-01-01                                        5.491  \n",
       "2022-01-01                                        4.910  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india = pd.read_csv('New India data _1980(csv).csv',index_col='Year',parse_dates=True,squeeze=True)\n",
    "india"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5d5c972b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(43, 2)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a4e5f6cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Inflation, average consumer prices(%)          float64\n",
       "Inflation, end of period consumer prices(%)    float64\n",
       "dtype: object"
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     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3067feae",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Inflation, average consumer prices(%)</th>\n",
       "      <th>Inflation, end of period consumer prices(%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-01</th>\n",
       "      <td>11.346</td>\n",
       "      <td>12.819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-01-01</th>\n",
       "      <td>12.654</td>\n",
       "      <td>9.048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-01-01</th>\n",
       "      <td>7.736</td>\n",
       "      <td>10.420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-01-01</th>\n",
       "      <td>12.558</td>\n",
       "      <td>10.398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-01</th>\n",
       "      <td>6.517</td>\n",
       "      <td>5.144</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "            Inflation, average consumer prices(%)  \\\n",
       "Year                                                \n",
       "1980-01-01                                 11.346   \n",
       "1981-01-01                                 12.654   \n",
       "1982-01-01                                  7.736   \n",
       "1983-01-01                                 12.558   \n",
       "1984-01-01                                  6.517   \n",
       "\n",
       "            Inflation, end of period consumer prices(%)  \n",
       "Year                                                     \n",
       "1980-01-01                                       12.819  \n",
       "1981-01-01                                        9.048  \n",
       "1982-01-01                                       10.420  \n",
       "1983-01-01                                       10.398  \n",
       "1984-01-01                                        5.144  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "43c920d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Inflation, average consumer prices(%)</th>\n",
       "      <th>Inflation, end of period consumer prices(%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
       "      <td>3.428</td>\n",
       "      <td>2.465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01</th>\n",
       "      <td>4.762</td>\n",
       "      <td>6.668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>6.175</td>\n",
       "      <td>4.867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-01</th>\n",
       "      <td>5.557</td>\n",
       "      <td>5.491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01</th>\n",
       "      <td>4.876</td>\n",
       "      <td>4.910</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "            Inflation, average consumer prices(%)  \\\n",
       "Year                                                \n",
       "2018-01-01                                  3.428   \n",
       "2019-01-01                                  4.762   \n",
       "2020-01-01                                  6.175   \n",
       "2021-01-01                                  5.557   \n",
       "2022-01-01                                  4.876   \n",
       "\n",
       "            Inflation, end of period consumer prices(%)  \n",
       "Year                                                     \n",
       "2018-01-01                                        2.465  \n",
       "2019-01-01                                        6.668  \n",
       "2020-01-01                                        4.867  \n",
       "2021-01-01                                        5.491  \n",
       "2022-01-01                                        4.910  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "89f32e6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Inflation, average consumer prices(%)          0\n",
       "Inflation, end of period consumer prices(%)    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "553b0ad4",
   "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>Inflation, average consumer prices(%)</th>\n",
       "      <th>Inflation, end of period consumer prices(%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>43.000000</td>\n",
       "      <td>43.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.569721</td>\n",
       "      <td>7.387140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.023729</td>\n",
       "      <td>2.992753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.428000</td>\n",
       "      <td>2.465000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.819000</td>\n",
       "      <td>4.975000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.842000</td>\n",
       "      <td>7.001000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.912500</td>\n",
       "      <td>9.432000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13.483000</td>\n",
       "      <td>15.019000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Inflation, average consumer prices(%)  \\\n",
       "count                              43.000000   \n",
       "mean                                7.569721   \n",
       "std                                 3.023729   \n",
       "min                                 3.428000   \n",
       "25%                                 4.819000   \n",
       "50%                                 6.842000   \n",
       "75%                                 9.912500   \n",
       "max                                13.483000   \n",
       "\n",
       "       Inflation, end of period consumer prices(%)  \n",
       "count                                    43.000000  \n",
       "mean                                      7.387140  \n",
       "std                                       2.992753  \n",
       "min                                       2.465000  \n",
       "25%                                       4.975000  \n",
       "50%                                       7.001000  \n",
       "75%                                       9.432000  \n",
       "max                                      15.019000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india.describe(include='all')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65098d82",
   "metadata": {},
   "source": [
    "### Data Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aafae002",
   "metadata": {},
   "source": [
    "#### Line Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f55bd7be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,7))\n",
    "plt.plot(india['Inflation, average consumer prices(%)'],'r')\n",
    "plt.title('Inflation v/s Time')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4339eaff",
   "metadata": {},
   "source": [
    "#### Checking DIstribution with *Histogram*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8ee1d16b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(india['Inflation, average consumer prices(%)'],)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19a73718",
   "metadata": {},
   "source": [
    "#### Boxplot "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "61dca148",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(india['Inflation, average consumer prices(%)'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d622ee4",
   "metadata": {},
   "source": [
    "### Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "eadd6963",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 43 entries, 1980-01-01 to 2022-01-01\n",
      "Data columns (total 2 columns):\n",
      " #   Column                                       Non-Null Count  Dtype  \n",
      "---  ------                                       --------------  -----  \n",
      " 0   Inflation, average consumer prices(%)        43 non-null     float64\n",
      " 1   Inflation, end of period consumer prices(%)  43 non-null     float64\n",
      "dtypes: float64(2)\n",
      "memory usage: 1.0 KB\n"
     ]
    }
   ],
   "source": [
    "india.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4f55fca6",
   "metadata": {},
   "outputs": [],
   "source": [
    "india.drop('Inflation, end of period consumer prices(%)',axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "322de001",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['1980-01-01', '1981-01-01', '1982-01-01', '1983-01-01',\n",
       "               '1984-01-01', '1985-01-01', '1986-01-01', '1987-01-01',\n",
       "               '1988-01-01', '1989-01-01', '1990-01-01', '1991-01-01',\n",
       "               '1992-01-01', '1993-01-01', '1994-01-01', '1995-01-01',\n",
       "               '1996-01-01', '1997-01-01', '1998-01-01', '1999-01-01',\n",
       "               '2000-01-01', '2001-01-01', '2002-01-01', '2003-01-01',\n",
       "               '2004-01-01', '2005-01-01', '2006-01-01', '2007-01-01',\n",
       "               '2008-01-01', '2009-01-01', '2010-01-01', '2011-01-01',\n",
       "               '2012-01-01', '2013-01-01', '2014-01-01', '2015-01-01',\n",
       "               '2016-01-01', '2017-01-01', '2018-01-01', '2019-01-01',\n",
       "               '2020-01-01', '2021-01-01', '2022-01-01'],\n",
       "              dtype='datetime64[ns]', name='Year', freq=None)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india.dropna\n",
    "india.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f2493302",
   "metadata": {},
   "outputs": [],
   "source": [
    "india['Year'] = pd.to_datetime(india.index,format='Y')\n",
    "india['Year'] = india['Year'].dt.strftime('%Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c12d07cd",
   "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>Inflation, average consumer prices(%)</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-01</th>\n",
       "      <td>11.346</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-01-01</th>\n",
       "      <td>12.654</td>\n",
       "      <td>1981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-01-01</th>\n",
       "      <td>7.736</td>\n",
       "      <td>1982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-01-01</th>\n",
       "      <td>12.558</td>\n",
       "      <td>1983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-01</th>\n",
       "      <td>6.517</td>\n",
       "      <td>1984</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation, average consumer prices(%)  Year\n",
       "Year                                                   \n",
       "1980-01-01                                 11.346  1980\n",
       "1981-01-01                                 12.654  1981\n",
       "1982-01-01                                  7.736  1982\n",
       "1983-01-01                                 12.558  1983\n",
       "1984-01-01                                  6.517  1984"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7acb7ba0",
   "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>Inflation_rate</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-01</th>\n",
       "      <td>11.346</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-01-01</th>\n",
       "      <td>12.654</td>\n",
       "      <td>1981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-01-01</th>\n",
       "      <td>7.736</td>\n",
       "      <td>1982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-01-01</th>\n",
       "      <td>12.558</td>\n",
       "      <td>1983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-01</th>\n",
       "      <td>6.517</td>\n",
       "      <td>1984</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate  Year\n",
       "Year                            \n",
       "1980-01-01          11.346  1980\n",
       "1981-01-01          12.654  1981\n",
       "1982-01-01           7.736  1982\n",
       "1983-01-01          12.558  1983\n",
       "1984-01-01           6.517  1984"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india.rename(columns={'Inflation, average consumer prices(%)':'Inflation_rate'},inplace=True)\n",
    "india.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53e9a462",
   "metadata": {},
   "source": [
    "### Upsampling to get Monthly data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "708905fc",
   "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>Inflation_rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-31</th>\n",
       "      <td>11.346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-02-29</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-04-30</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-05-31</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-30</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-31</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-30</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-31</th>\n",
       "      <td>4.876</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>505 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate\n",
       "Year                      \n",
       "1980-01-31          11.346\n",
       "1980-02-29             NaN\n",
       "1980-03-31             NaN\n",
       "1980-04-30             NaN\n",
       "1980-05-31             NaN\n",
       "...                    ...\n",
       "2021-09-30             NaN\n",
       "2021-10-31             NaN\n",
       "2021-11-30             NaN\n",
       "2021-12-31             NaN\n",
       "2022-01-31           4.876\n",
       "\n",
       "[505 rows x 1 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_month = india.resample('M').mean()\n",
    "india_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ae2f697f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>Inflation_rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-31</th>\n",
       "      <td>11.34600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-02-29</th>\n",
       "      <td>11.45500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.56400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-04-30</th>\n",
       "      <td>11.67300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-05-31</th>\n",
       "      <td>11.78200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-30</th>\n",
       "      <td>5.10300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-31</th>\n",
       "      <td>5.04625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-30</th>\n",
       "      <td>4.98950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>4.93275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-31</th>\n",
       "      <td>4.87600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>505 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate\n",
       "Year                      \n",
       "1980-01-31        11.34600\n",
       "1980-02-29        11.45500\n",
       "1980-03-31        11.56400\n",
       "1980-04-30        11.67300\n",
       "1980-05-31        11.78200\n",
       "...                    ...\n",
       "2021-09-30         5.10300\n",
       "2021-10-31         5.04625\n",
       "2021-11-30         4.98950\n",
       "2021-12-31         4.93275\n",
       "2022-01-31         4.87600\n",
       "\n",
       "[505 rows x 1 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_month_interpolated = india_month.interpolate(method='linear')\n",
    "india_month_interpolated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6a6893f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Inflation_rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-31</th>\n",
       "      <td>11.346000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-02-29</th>\n",
       "      <td>11.455000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.564000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-04-30</th>\n",
       "      <td>11.673000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-05-31</th>\n",
       "      <td>11.782000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-06-30</th>\n",
       "      <td>11.891000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-07-31</th>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-08-31</th>\n",
       "      <td>12.109000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-09-30</th>\n",
       "      <td>12.218000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-10-31</th>\n",
       "      <td>12.327000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-11-30</th>\n",
       "      <td>12.436000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-12-31</th>\n",
       "      <td>12.545000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-01-31</th>\n",
       "      <td>12.654000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-02-28</th>\n",
       "      <td>12.244167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-03-31</th>\n",
       "      <td>11.834333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-04-30</th>\n",
       "      <td>11.424500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-05-31</th>\n",
       "      <td>11.014667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-06-30</th>\n",
       "      <td>10.604833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-07-31</th>\n",
       "      <td>10.195000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-08-31</th>\n",
       "      <td>9.785167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-09-30</th>\n",
       "      <td>9.375333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-10-31</th>\n",
       "      <td>8.965500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-11-30</th>\n",
       "      <td>8.555667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-12-31</th>\n",
       "      <td>8.145833</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate\n",
       "Year                      \n",
       "1980-01-31       11.346000\n",
       "1980-02-29       11.455000\n",
       "1980-03-31       11.564000\n",
       "1980-04-30       11.673000\n",
       "1980-05-31       11.782000\n",
       "1980-06-30       11.891000\n",
       "1980-07-31       12.000000\n",
       "1980-08-31       12.109000\n",
       "1980-09-30       12.218000\n",
       "1980-10-31       12.327000\n",
       "1980-11-30       12.436000\n",
       "1980-12-31       12.545000\n",
       "1981-01-31       12.654000\n",
       "1981-02-28       12.244167\n",
       "1981-03-31       11.834333\n",
       "1981-04-30       11.424500\n",
       "1981-05-31       11.014667\n",
       "1981-06-30       10.604833\n",
       "1981-07-31       10.195000\n",
       "1981-08-31        9.785167\n",
       "1981-09-30        9.375333\n",
       "1981-10-31        8.965500\n",
       "1981-11-30        8.555667\n",
       "1981-12-31        8.145833"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_month_interpolated.head(24)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "aeabbb73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(505, 1)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_month_interpolated.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e49530b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>Inflation_rate</th>\n",
       "      <th>t</th>\n",
       "      <th>t_squared</th>\n",
       "      <th>log_inflation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-31</th>\n",
       "      <td>11.346</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.428865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-02-29</th>\n",
       "      <td>11.455</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2.438426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.564</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2.447897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-04-30</th>\n",
       "      <td>11.673</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>2.457278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-05-31</th>\n",
       "      <td>11.782</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>2.466573</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate  t  t_squared  log_inflation\n",
       "Year                                                   \n",
       "1980-01-31          11.346  0          0       2.428865\n",
       "1980-02-29          11.455  1          1       2.438426\n",
       "1980-03-31          11.564  2          4       2.447897\n",
       "1980-04-30          11.673  3          9       2.457278\n",
       "1980-05-31          11.782  4         16       2.466573"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_month_interpolated[\"t\"] = np.arange(0,505)\n",
    "india_month_interpolated[\"t_squared\"] = india_month_interpolated[\"t\"]*india_month_interpolated[\"t\"]\n",
    "india_month_interpolated[\"log_inflation\"] = np.log(india_month_interpolated['Inflation_rate'])\n",
    "india_month_interpolated.columns\n",
    "india_month_interpolated.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "54aa5572",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Inflation_rate</th>\n",
       "      <th>t</th>\n",
       "      <th>t_squared</th>\n",
       "      <th>log_inflation</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-31</th>\n",
       "      <td>11.346</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.428865</td>\n",
       "      <td>1980-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-02-29</th>\n",
       "      <td>11.455</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2.438426</td>\n",
       "      <td>1980-02-29</td>\n",
       "      <td>Feb</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.564</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2.447897</td>\n",
       "      <td>1980-03-31</td>\n",
       "      <td>Mar</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-04-30</th>\n",
       "      <td>11.673</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>2.457278</td>\n",
       "      <td>1980-04-30</td>\n",
       "      <td>Apr</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-05-31</th>\n",
       "      <td>11.782</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>2.466573</td>\n",
       "      <td>1980-05-31</td>\n",
       "      <td>May</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate  t  t_squared  log_inflation       Year Month  year\n",
       "Year                                                                          \n",
       "1980-01-31          11.346  0          0       2.428865 1980-01-31   Jan  1980\n",
       "1980-02-29          11.455  1          1       2.438426 1980-02-29   Feb  1980\n",
       "1980-03-31          11.564  2          4       2.447897 1980-03-31   Mar  1980\n",
       "1980-04-30          11.673  3          9       2.457278 1980-04-30   Apr  1980\n",
       "1980-05-31          11.782  4         16       2.466573 1980-05-31   May  1980"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_month_interpolated['Year']=pd.to_datetime(india_month_interpolated.index,format='Y')\n",
    "india_month_interpolated['Month']=india_month_interpolated['Year'].dt.strftime('%b')\n",
    "india_month_interpolated['year']=india_month_interpolated['Year'].dt.strftime('%Y')\n",
    "india_month_interpolated.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "de2f82d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20,7))\n",
    "plt.plot(india_month_interpolated['Inflation_rate'])\n",
    "plt.title('Inflation between 1980 - 2022',size = 20)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Inflation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "aa5c6f66",
   "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>Inflation_rate</th>\n",
       "      <th>t</th>\n",
       "      <th>t_squared</th>\n",
       "      <th>log_inflation</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-31</th>\n",
       "      <td>11.34600</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.428865</td>\n",
       "      <td>1980-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-02-29</th>\n",
       "      <td>11.45500</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2.438426</td>\n",
       "      <td>1980-02-29</td>\n",
       "      <td>Feb</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.56400</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2.447897</td>\n",
       "      <td>1980-03-31</td>\n",
       "      <td>Mar</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-04-30</th>\n",
       "      <td>11.67300</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>2.457278</td>\n",
       "      <td>1980-04-30</td>\n",
       "      <td>Apr</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-05-31</th>\n",
       "      <td>11.78200</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>2.466573</td>\n",
       "      <td>1980-05-31</td>\n",
       "      <td>May</td>\n",
       "      <td>1980</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-30</th>\n",
       "      <td>5.10300</td>\n",
       "      <td>500</td>\n",
       "      <td>250000</td>\n",
       "      <td>1.629829</td>\n",
       "      <td>2021-09-30</td>\n",
       "      <td>Sep</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-31</th>\n",
       "      <td>5.04625</td>\n",
       "      <td>501</td>\n",
       "      <td>251001</td>\n",
       "      <td>1.618645</td>\n",
       "      <td>2021-10-31</td>\n",
       "      <td>Oct</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-30</th>\n",
       "      <td>4.98950</td>\n",
       "      <td>502</td>\n",
       "      <td>252004</td>\n",
       "      <td>1.607336</td>\n",
       "      <td>2021-11-30</td>\n",
       "      <td>Nov</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>4.93275</td>\n",
       "      <td>503</td>\n",
       "      <td>253009</td>\n",
       "      <td>1.595897</td>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-31</th>\n",
       "      <td>4.87600</td>\n",
       "      <td>504</td>\n",
       "      <td>254016</td>\n",
       "      <td>1.584325</td>\n",
       "      <td>2022-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>505 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate    t  t_squared  log_inflation       Year Month  \\\n",
       "Year                                                                         \n",
       "1980-01-31        11.34600    0          0       2.428865 1980-01-31   Jan   \n",
       "1980-02-29        11.45500    1          1       2.438426 1980-02-29   Feb   \n",
       "1980-03-31        11.56400    2          4       2.447897 1980-03-31   Mar   \n",
       "1980-04-30        11.67300    3          9       2.457278 1980-04-30   Apr   \n",
       "1980-05-31        11.78200    4         16       2.466573 1980-05-31   May   \n",
       "...                    ...  ...        ...            ...        ...   ...   \n",
       "2021-09-30         5.10300  500     250000       1.629829 2021-09-30   Sep   \n",
       "2021-10-31         5.04625  501     251001       1.618645 2021-10-31   Oct   \n",
       "2021-11-30         4.98950  502     252004       1.607336 2021-11-30   Nov   \n",
       "2021-12-31         4.93275  503     253009       1.595897 2021-12-31   Dec   \n",
       "2022-01-31         4.87600  504     254016       1.584325 2022-01-31   Jan   \n",
       "\n",
       "            year  \n",
       "Year              \n",
       "1980-01-31  1980  \n",
       "1980-02-29  1980  \n",
       "1980-03-31  1980  \n",
       "1980-04-30  1980  \n",
       "1980-05-31  1980  \n",
       "...          ...  \n",
       "2021-09-30  2021  \n",
       "2021-10-31  2021  \n",
       "2021-11-30  2021  \n",
       "2021-12-31  2021  \n",
       "2022-01-31  2022  \n",
       "\n",
       "[505 rows x 7 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_month_interpolated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "596e1440",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\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>Inflation_rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-06-30</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-09-30</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-12-31</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-03-31</th>\n",
       "      <td>12.654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-31</th>\n",
       "      <td>5.557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-30</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-30</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-31</th>\n",
       "      <td>4.876</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>169 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate\n",
       "Year                      \n",
       "1980-03-31          11.346\n",
       "1980-06-30             NaN\n",
       "1980-09-30             NaN\n",
       "1980-12-31             NaN\n",
       "1981-03-31          12.654\n",
       "...                    ...\n",
       "2021-03-31           5.557\n",
       "2021-06-30             NaN\n",
       "2021-09-30             NaN\n",
       "2021-12-31             NaN\n",
       "2022-03-31           4.876\n",
       "\n",
       "[169 rows x 1 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quarterly_inflation = india.resample('Q').mean()\n",
    "quarterly_inflation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4af6ba29",
   "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>Inflation_rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.34600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-06-30</th>\n",
       "      <td>11.67300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-09-30</th>\n",
       "      <td>12.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-12-31</th>\n",
       "      <td>12.32700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-03-31</th>\n",
       "      <td>12.65400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-31</th>\n",
       "      <td>5.55700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-30</th>\n",
       "      <td>5.38675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-30</th>\n",
       "      <td>5.21650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>5.04625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-31</th>\n",
       "      <td>4.87600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>169 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate\n",
       "Year                      \n",
       "1980-03-31        11.34600\n",
       "1980-06-30        11.67300\n",
       "1980-09-30        12.00000\n",
       "1980-12-31        12.32700\n",
       "1981-03-31        12.65400\n",
       "...                    ...\n",
       "2021-03-31         5.55700\n",
       "2021-06-30         5.38675\n",
       "2021-09-30         5.21650\n",
       "2021-12-31         5.04625\n",
       "2022-03-31         4.87600\n",
       "\n",
       "[169 rows x 1 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_quarter_interpolated =quarterly_inflation.interpolate(method='linear')\n",
    "india_quarter_interpolated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "5b81ac1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20,7))\n",
    "plt.plot(india_quarter_interpolated['Inflation_rate'])\n",
    "plt.title(' Quarterly Inflation between 1980 - 2022',size = 20)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Inflation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b917146",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "903def7f",
   "metadata": {},
   "source": [
    "#### Yearly Boxplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "793932a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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00uwCmBLD3kGxfAfH/Pz8KNIBAAAA1qHVauXYlpP5oRte1Uj8N9x6Uy65cmsjsYHR2LN9V171Nd858bg3ve8PJx5zXLY0nQAAAAAAAADUZWYXAACwbsOsJ59YUx4AAIDR0+wCAADWrdPpZP9dd6Ts2F5rfFWdTpJ85OH7640/tFhrHAAAwDTqdrs5sXi0kSUF7118KNvKYxOPOw6aXQAAwEDKju05/8avbST2qVve20hcAAAAppdmFwAAAADAEB545EDecOtNtcYeOvZgkmTHJbtrx77kyutqjQWa12q1crJ6Sl71Nd858dg3ve8Ps7V1+cTjjoNmFwAAAABATe12e6jxD504mSS55MqttcZfcuV1Q+cAMOs0uwAAAAAAatq7d+9Q4/ft25ckmZ+fH0U6AJuSZhcAAAAAADC0A0cfyM0feEOtsQ+eOJQk2b1tR6241+WSWnGnwYHFh3PT+/5w4HEPnjiSJNm97dLaca+72jKGAAAAAAAAQy+nebLzUJJk69MGb1pdl0tmdjnPYfI+2XkkSbK1ZsPquqsvn9nr9mSaXQAAAAAAwFAs6VnPMNdts16zc9nSdAIAAAAAAABQl5ldAAAAAABjsrCwkE6ns+Lx5WPLMzTOpd1uDz1rBmAj0+wCAAAAAGjI3Nxc0ykAzDzNLgAAANhgzhx6KI+9+ffqjV3sbXS+ZftlteJm1+DjADYyM7KAYaw2O9TM0M/S7AIAAIANpN1uDzW+c/Rw7zx1mla7Lhs6PgCTs9YSi91uN0nSarVWfM5meSMdppGZoZ+l2QUAAAAbyLBvOC7fGTw/Pz+KdACYYUtLS02nAJtek83khYWFvOMd71jx+KOPPpqqqmqfv5SSiy66aMXjz3/+89f9/6/ZBQAArFu32011dDGnbnlvI/GrQ4vpPlEaiQ0AsNGs9SayGyCAWaHZBQAAAACwAa21TOFa1rMf0GoscQizbe/evTPzM6zZBTAj1voD1YaUAExCq9XKoQuqnH/j1zYS/9Qt701r18p7RgAA8FmdTicfv/OeXL19T63x55/emiQ50T058Nj7Fw/UiglQh2YXwAZhQ0oAAADgya7evic/9txXTjzuL77n5onHZLoNeyO3m7hZjWYXwIxQzAEAAIBBdLvdHD9yopHG0/1H7s3F2TbxuMwuN3IzDM0uAAAAAABgrNzIzThpdgEAAAAAbECtVisncrKxZQy3tbZOPO5mt9ZSgd1uN0nve+NcLBXIrNLsAgAAAADYoO5fPFB7GcODxx9Mkuy8eHetuM9sXVcrLuOztLTUdAowFppdAAAAAAAbULvdHmr8Zzonk6TWDK1ntq4bOj6DW2tW1r59+5Ik8/Pzk0gHJkazC4ChrTVFfvnY8h9UT2aKPAAAAIzesK+1NUaAWaHZBcDYzc3NNZ0CAAAA8CTD3ryauIEVmA6aXQAMzR+1AAAAsPG4eRWYFZpdAAAAAACb0DTfvLrWrLNut5skabVaKz7HrDPYPDS7AAAAAACYKUtLS02nAEwRzS4AAAAAAKbKWjOylvcRm5+fn0Q6wJTT7AIAAAZSHVrMqVveW2/s4okkSdm+rXbs7Lq61ligZ61loZaPLb+J+GSWhAIAYNpodgEAAOvWbreHGt852nsTvV23YbXr6qFzAFY3NzfXdAoAADAQzS4AAGDdhp3NYbkZNou1Zk91u90kSavVOufxcc6eMisLAGbXWn9jrGWtGdxrMcObaaXZBQAA0LBhGyOJNx5mzdLSUtMpAAAzqNPp5J47Pp49l9RbKWHrqV5L4OSnTww89sCx+2vFhEnQ7AIAAJhyGiOzZ63Go1mOAGx2ZijVt+eSq/PvvvJHJx731R/85YnHhPXS7AIAADaFaZ49pTECAGw2nU4nn7jjnjz9kj21xl9wamuS5LFPnxx47KePHagVE5heml0AAAAZ7+wpdy5vPL6mADC8p1+yJ//2K//dxOO+9oOvnnhMYLw0uwAAgE2hydlTnU4n+++6M2XHZbXGV9WZJMlHHv7M4GMPPVIrJqvrfU3vStmxq9b4qup9/MjDhwYfe+jhWjEBAGCj0uwCAAA2hGmeabO8RGJdZfslQ40fNj7nVnbsyoUv/PaJx338zX888ZgAADDNNLsAAIAN4bOzpy6tNf6zs6ceGHzsoSO1YgIAADA8zS4AAGDDKDsuzfkv+vqJxz31pneterzVauXQBVtywQufP6GMPuuJN78jrV1XTjwuAADApGh2AQAATEB16JE88eZ31Bu7eCxJveUMq0OPJJpdI9ftdlMdPdrIkoLVoYfTfeLxiccFgFHqdrs5cexEXvvBV0889qeP3Ztt3W0TjwuMT6PNrlLKeUk+nOT+qqpe0GQuAADAbOs1HxbXnGU1DtWhI+k+Ua14vN1uD3X+ztETvfPUaVrtunLo+AAATIdek/B4Xv3BX5547HuP3Z9t3YsnHhfWo+mZXS9LcmeSpzacBwAAwNjs3bt3qPH79u1LkszPz48iHUagtzTlhbnwhd8+8diPv/mP09q1Y+JxAWCUWq1WHjt9Mv/2K//dxGO/9oOvzlNaWyceFxifxppdpZSnJfmWJDcn+cmm8gAAAEZnYWEhnU5nxePLx5abN+fSbrdrNYd6zYfS2J5drV1X1R7f5HUbNrdut5ukd/0nnRsAwGbTarVy8vSJ/Luv/NGJx371B385W1uWf2Q6NTmz6xeS/NskKy46X0p5aZKXJsmePXsmkxUAADA2c3NzTacwk8Z53dbTzFpaWlrx+PKx1Z7T7XZXjDHLjbDq0MO19+yqFo8kScr2S2vFjZldAADwvzTS7CqlvCDJQ1VV3V5Ked5Kz6uq6vVJXp8k119//coL4AMAAFOh6aZFdehI7T27qsXjSZKyffB9CKpDR5IhZnY1ed1uu+22HDx0KLlguJeHJ544ueqxg0cXP/fAE6fS7XYb/76pY/h92I70zlOnabVrh33YAADgLE3N7PqaJC8qpfzTJE9J8tRSyu9UVfXdDeUDAADMuOGbD72ZR+06TatdV2k+bDL2YQMAgOnRSLOrqqpXJHlFkvRndu3T6AIAAIah+VDPc57znOGWMTzVOzZ3wcqbvM/Nza24p5cmIQBsXp8+diCv/eCra4196NEHkyRXXLS7Vtxn5LpacYHp1OSeXQAAADRsrSbhevb0SrJiMyupvy/XwsJC3vGOd6x4/PHHH8+ZM2dWPL58bMuWLSs+Z8uWLbnwwgvPeez5z3/+TC6xCACzYNgbXp7o9JZQfsrTV77hZiXPyHVuuIENpvFmV1VV707y7obTAAAANri1mjbLx5ZneJ1L3abNLJvm/9/Tp0+nqtbe3nm1hth6xtcx7PfbZvxeA2BzMSsfGKXGm10AAADTYG5urukUeJK9e/eu+kZYk7POhuX7DQAARkezCwAA2BTMktl4pvlrOs25AQDARqPZBQAAAAAAM+LAsfvz6g/+cq2xDz56MEmy+6KdteJel2fWigvjptkFAAAAAAAzoN1uDzX+ZOczSZKtT9828Njr8syh48O4lHFtxjtq119/ffXhD3+46TQAAAAAABiztfbmXD62WvOlqb05p9m+ffuSJPPz8w1nAoMrpdxeVdX15zpmZhcAAAAAADNlbm6u6RSAKaLZBQAAAADAVDEjCxiEZhcAAAAAAKzTWkssdrvdJEmr1VrxOZZYhNHS7AIAAAAAgL71NLOWlpZWPL58bLXndLvdFWNohMHgNLsAAAAAAKDvtttuy+GDh3Ph+RfWGr+lKkmSM4+fWfE5Jx4/kU8c+cTnPP74qcfT7XY1u2BAml0AAAAAAHCWC8+/MNdc8vSJx7332KcnHhM2gi1NJwAAAAAAANOi1WqlDDH+wUcfyoOPPlRrbMnqe30B52ZmFwAAAAAA9LXb7VWPr7ln1xO9YydPPrHic+bm5s7Z1Louz1gzPvC5SlVVTeewLtdff3314Q9/uOk0AAAAAADYxBYWFtLpdFY83u12k6w+Q6vdbo9lX661cls+tlJDbVx5wSiUUm6vqur6cx0zswsAAAAAANZplptBc3NzTacAY6HZBQAAAAAAG8AsN+JgGFuaTgAAAAAAAADq0uwCAAAAAABgZml2AQAAAAAAMLM0uwAAAAAAAJhZml0AAAAAAADMLM0uAAAAAAAAZpZmFwAAAAAAADNLswsAAAAAAICZpdkFAAAAAADAzNLsAgAAAAAAYGZpdgEAAAAAADCzNLsAAAAAAACYWZpdAAAAAAAAzCzNLgAAAAAAAGaWZhcAAAAAAAAzq1RV1XQO61JKeTjJvSM63c4kB0d0rlGTWz1yq0du9citHrnVM625TWteidzqkls9cqtHbvXIrR651SO3wU1rXonc6pJbPXKrR271yK0eudUzrblNa17J6HO7pqqqXec6MDPNrlEqpXy4qqrrm87jXORWj9zqkVs9cqtHbvVMa27Tmlcit7rkVo/c6pFbPXKrR271yG1w05pXIre65FaP3OqRWz1yq0du9UxrbtOaVzLZ3CxjCAAAAAAAwMzS7AIAAAAAAGBmbdZm1+ubTmAVcqtHbvXIrR651SO3eqY1t2nNK5FbXXKrR271yK0eudUjt3rkNrhpzSuRW11yq0du9citHrnVI7d6pjW3ac0rmWBum3LPLgAAAAAAADaGzTqzCwAAAAAAgA1AswsAAAAAAICZtWGaXaWUXy+lPFRK+ehZj31xKeUvSikfKaW8uZTy1P7jF5RS/mv/8TtLKa84a8yX9x+/p5Tyn0spZYpyu7mU8ulSyvFhcxplbqWUi0opby2l3FVK+Vgp5TXTkFf/2NtKKX/Tz+tXSinnTUtuZ41909nnmobcSinvLqXcXUr56/5/V0xRbltLKa8vpXy8/z33bdOQWynlkrOu11+XUg6WUn5hGnLrH3tJ//H9/Z+LnVOU23f28/pYKeW1w+ZVI7etpZTf6D/+N6WU5501pumasFpuTdeEc+ZWxlATRpVb/1jTdWHF3M4a21RdWO26NV0XVsut6bqw0s/CyOvCCK9Z0zVhtdzGUROeXkp5V+nVn4+VUl7Wf/zyUso7Symf6H+87Kwxryi93/13l1K+8azHR1oXRpzbSOvCqHIr43mtMMrrNtK6MMrczjo+krow4us20row4txGVhdG+HMwjpowyms20row4txGWhcGza2UsqP//OOllF960rkarQlr5NZoTVgptzIFNWGN69ZoTVgtt7PO2UhNWOO6NVoT1shtpK8VRviz0HhdWOO6NVoX1sit6brwDaWU2/vX5/ZSyj8+61wjqwsjzqvpmnDO3Mo43j+qqmpD/JfkuUm+LMlHz3rsQ0m+rv/5Dyb5uf7n35XkD/qfX5TkU0mu7f/7L5N8VZKS5M+SfPMU5fbsJFclOT5N163/+df3H9+a5LZhr9sIr9lT+x9Lkj9J8uJpuGZnjfvWJL939rmmIbck705y/ai+z0ac288muan/+ZYkO6cltyed8/Ykz52G3JKcn+Sh5WuV5LVJfmZKctuR5ECSXf1j/zXJDRPO7UeT/Eb/8yv6X7st/X83XRNWy63pmnDO3DKGmjDi69Z0XVgxt/5jTdaF1a7bu9NsXVgtt6brwqpf07PGD10XRpFXpqMmrJTbuGrCVUm+rP/5JUk+nuRZ/f/3l/cff3mS/9D//FlJ/ibJhUk+L0knyXn9YyOtCyPObaR1YVS5ZTyvFUZ53UZaF0aZW//4yOrCiK/buzPCujDi3EZWF0b99TzrvKOoCaP6GR15XRhhbiOvCzVy25bka5P8SJJfetK5mq4Jq+XWdE04Z26Zjpqw2nVruiasmFv/eJM1YbXr9u40WxNWy22krxVG/TU967xN1IWVfk6noS6slNs01IUvTdLqf/6FSe4/61wjqwsjzqvpmnDO3DKOmjCK/8Fp+S+9N07PfoF9NEnpf/70JHf0P39Jkjf3f3h39L8gl/e/UHedNf4lSX51GnJ70rlG9sbmqHPrP+91Sf7lNOWV5IL+c75zWq5ZkouTvLf/y2Akb2qOMLd3Z8Rvao4wt08n2TaNuZ019hn9PMs05Nb//n84yTXpFdxfSfLSKcntK5L8j7PGf0+S/3fCuf1yku8+63m3JvlHmY6acM7cnnSupmrCmrn1Hx9JTRjDdWuqLqyYW5qvC6vl9u40WxdWy63purCe77eR1YVh88p01ISVchtbTXhSnrck+YYkdye5qv/YVUnu7n/+iiSvOOv5b0/vRevY6sKwuT3pHCOtC6PMrf/4yOrCiK/bSOvCKHLLmOrCiHJ7d8ZQF0aU21jqwgi/10b6WmHY3DLGujCC3MZeF9bK7aznfX/+7huujdeElXJ70rFGasJ6cusfn3hNWOd1a6QmrJZbGq4Ja+T27jRYE9bIbWw1YYTfb43UhZVyyxTUhVVym5q60H+8JDmU3s0aY60LdfN60uON1oTVcusfG7ombJhlDFfw0SQv6n/+Hem9yE6SP05yIskD6XWD56uqOpzk6iT3nTX+vv5j05DbJNXOrZRyaZIXpvemxVTkVUp5e3p3JBzrP3cc6uT2c0n+Y5JHx5TTMLklyW/0p1L/1DDTbkeZW//7K0l+rpTyP0spf1RK2T0NuT1p7EuS/GHV/03ddG5VVT2RZG+SjyTppvfH8a9NQ25J7kny90op15ZSzk/yz84aM6nc/ibJjaWU80spn5fky/vHpqEmrJTbJNXObcw1oXZuDdeF1XJrui6s9TVtsi6cM7cpqQvr+TkdZ10YKK8pqQkrXbOx14RSyrXp3Vn4wSS7q6p6IEn6H5eX3Lk6vTccli3//h9rXRgyt7EaVW7jqAujyG1cdWEEuY2tLozoazqWujBMbuOsCyP8GR15TRgmt3HXhSGv21jrwjpzW8k01IRGjCq3BmvCWudosiaspumasJYma8JKYy/tfzqW1woj/Dltqi6c05TUhZVMW134tiR/VVXV4xljXRgyr7EaVW6jqgkbvdn1g0l+tJRye3pT6k72H/9HSU4naaU3Rf5fl1I+P73O4pON683qQXObpFq59X/J/H6S/1xV1SenJa+qqr4xvW7yhUn+ccZjoNxKKV+S5Lqqqv77mPKpnVv/2D+vquofJnlO/7/vmZLczk/ytCTvq6rqy5L8RZL5KcntbC9O72dhXAb9frsgvT9UvrR/bH96d082nltVVY/0c/vD9KYrfyrJqQnn9uvp/RHy4SS/kOT9/RymoSaslNsk1cptAjWhdm4N14Vz5jYldWG169Z0XVgpt2moC+v5OR1nXRj0e20aasI5cxt3TSilXJzekkQ/UVXV0dWeeo7HqlUen4bcxmZUuY2jLowqt3HUhWFzG2ddGNF1G0tdGEFuY6kLI/4ZHWlNGMH32tjqwrC5jbMuDJDbiqc4x2OTrgkTN6rcGq4Jq2q4Jqw0/kvSfE1YTdM1YSVje60w4p/TpurCSuOnoS6c0zTVhVLKP0jyH5L88PJD50p5CvIam1HlNsqacP4wg6ddVVV3JXl+kpRSnpnkW/qHvivJ2/qd6odKKe9Lcn16PyRPO+sUT0uvgz0NuY3rjcJR5vb6JJ+oquoXpiyvVFX1WCnlTUluTPLOKchtR5IvL6V8Kr2fwytKKe+uqup5U5DbJ6uqur8/9lgp5ffSa1T81hTk9kfp3cW0/AfeHyX5F6POq2Zun+w/94uTnF9V1e3jyKtmbjv64zr9Mf8tvbVzpyG3T1ZV9eb0lohIKeWl6TXFJpZbVVWnkvyr5eeVUt6f5BNJHknDNWGV3CZmiNzGWhOGzK2xurBKbl+XhuvCatet6bqwSm6H0nBdWOv7bdx1oUZeX9I/3lhNWON7bSw1of+i/U+S/G5VVW/sP/xgKeWqqqoeKKVcld5d3EmvEXf2HaLLv//vyxjqwohyG4sR5zbSujDq6zbKujCi3L4qY6gLo7pu46gLI8pt5HVhlN9ro64JI8rtS5LR14URfq+NvC4MmNtKpqEmTNSIc2uyJqypwZqwkmmoCSuagpqwkrG8Vhjl91vDdWElX5I0XhdWNA11oZTytPS+r753+TplDHVhRHmNxYhzG1lN2NAzu0opV/Q/bknyqvTWGE16S2j949KzLb1N2u6qetPrjpVSnl1KKUm+N701JxvPbRw5jDK3UspNSbYn+YlpyauUcnH/B2u5Q/xPM6ZrWeN7baGqqlZVVdemt+Hix8fxhmad3EpvSaGd/TEXJHlBessQNZ5bVVVVegXtef3n3ZDkjmnI7ayhL8l4Z3XVye3+JM8qpezqP+8bktw5JbmdPeayJP9HkjdMMrdSykX9nFJK+Yb0ZhfcMQ01YaXcxpHDKHObRE2ok9s01IVVvt8arwurXLfG68Iq163xurCOn9Ox1oUaeTVeE9b4/THymtD/Hf5rSe6squrnzzr0piTf1//8+/LZ3/FvSvLiUsqFpbfM4jOS/OU46sKochsmh0nkNuq6MKrcxlEXRvj9NvK6MMLrNvK6MMLrNtK6MIaf0ZHVhBHmNvK6MOLfHyOtCzVyO6cpqQkTM8rcpqAmrHSeaagJ5zQlNWGl80xDTTincbxWGMPPaZN1YSXTUBdWO1ejdaH0ltt7a3p7Tb5v+cmjrgujymscRpnbqGtC7c2+pu2/9H4xPJDkifQ6qf8iycuSfLz/32uS/7VB9sXpdfM/lt4vuX9z1nmuT++XcifJLy2PmZLcXtsff6b/8WemIbf0OtVVer/4/rr/3w9NQV67k3wovem2H0vyi+ndLdH4NXvS+a7NiDYXHdF125bk9rOu2+uSnDcNufWPXZPkPf38bk2yZ1py6x//ZJK/N4qv54iv24+k9zO6P70/9nZMUW6/33/sjiQvbuC6XZveJpp3JvkfSa456zxN14TVcmu6Jpwzt4yhJowwt2moCyt+Tc8637Vppi6sdN2moS6s9rPQdF1Y9WuaEdaFEV6zpmvCarmNoyZ8bXq/l/bns7+X/ml6M59vTW9W2a1JLj9rzCvT+91/d5JvPuvxkdaFEec20rowqtwyntcKo8pt5HVhlF/Ts45fmxHUhRFet5HXhRH/LIysLoz665nR1oRRXrOR1oUR5zbSulAzt08lOZzkeHq/X5/Vf3waasJKuU1DTfic3DI9NeFcuU1LTTjn1/Ss49emuZpwrus2LTXhnNctI36tMOqvaZqvCytdt2moCyvl1mhdSO8mvhNnPfevk1zRPzayujDivBqtCSvlljHUhOUXnAAAAAAAADBzNvQyhgAAAAAAAGxsml0AAAAAAADMLM0uAAAAAAAAZpZmFwAAAAAAADNLswsAAAAAAICZpdkFAAAAAADAzNLsAgAA2EBKKec1nQMAAMAkaXYBAAA0pJTyc6WUl53175tLKT9eSvk3pZQPlVL2l1J+9qzjf1pKub2U8rFSykvPevx4KeX/LqV8MMlXTfh/AwAAoFGaXQAAAM35tSTflySllC1JXpzkwSTPSPKPknxJki8vpTy3//wfrKrqy5Ncn+THSyk7+o9vS/LRqqq+sqqq904wfwAAgMad33QCAAAAm1VVVZ8qpRwqpXxpkt1J/irJVyR5fv/zJLk4vebXe9JrcP1v/cef3n/8UJLTSf5kkrkDAABMC80uAACAZr0hyfcnuTLJrye5Icm/r6rqV89+UinleUn+SZKvqqrq0VLKu5M8pX/4saqqTk8oXwAAgKliGUMAAIBm/fck35TejK639//7wVLKxUlSSrm6lHJFku1JHuk3uv5ekmc3lTAAAMA0MbMLAACgQVVVnSylvCvJkf7srHeUUv5+kr8opSTJ8STfneRtSX6klLI/yd1JPtBUzgAAANOkVFXVdA4AAACbVillS5L/meQ7qqr6RNP5AAAAzBrLGAIAADSklPKsJPckuVWjCwAAoB4zuwAAAAAAAJhZZnYBAAAAAAAwszS7AAAAAAAAmFmaXQAAAAAAAMwszS4AAAAAAABmlmYXAAAAAAAAM+v/B77MBEObXFvtAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 2160x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30,7))\n",
    "sns.boxplot(data=india_month_interpolated,x='year',y= 'Inflation_rate')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8335e67",
   "metadata": {},
   "source": [
    "#### Monthly Boxplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3adc0d05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,7))\n",
    "sns.boxplot(data=india_month_interpolated,x='Month',y= 'Inflation_rate')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "96a0d27c",
   "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>Inflation_rate</th>\n",
       "      <th>t</th>\n",
       "      <th>t_squared</th>\n",
       "      <th>log_inflation</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-31</th>\n",
       "      <td>11.34600</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.428865</td>\n",
       "      <td>1980-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-02-29</th>\n",
       "      <td>11.45500</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2.438426</td>\n",
       "      <td>1980-02-29</td>\n",
       "      <td>Feb</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.56400</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2.447897</td>\n",
       "      <td>1980-03-31</td>\n",
       "      <td>Mar</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-04-30</th>\n",
       "      <td>11.67300</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>2.457278</td>\n",
       "      <td>1980-04-30</td>\n",
       "      <td>Apr</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-05-31</th>\n",
       "      <td>11.78200</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>2.466573</td>\n",
       "      <td>1980-05-31</td>\n",
       "      <td>May</td>\n",
       "      <td>1980</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-30</th>\n",
       "      <td>5.10300</td>\n",
       "      <td>500</td>\n",
       "      <td>250000</td>\n",
       "      <td>1.629829</td>\n",
       "      <td>2021-09-30</td>\n",
       "      <td>Sep</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-31</th>\n",
       "      <td>5.04625</td>\n",
       "      <td>501</td>\n",
       "      <td>251001</td>\n",
       "      <td>1.618645</td>\n",
       "      <td>2021-10-31</td>\n",
       "      <td>Oct</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-30</th>\n",
       "      <td>4.98950</td>\n",
       "      <td>502</td>\n",
       "      <td>252004</td>\n",
       "      <td>1.607336</td>\n",
       "      <td>2021-11-30</td>\n",
       "      <td>Nov</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>4.93275</td>\n",
       "      <td>503</td>\n",
       "      <td>253009</td>\n",
       "      <td>1.595897</td>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-31</th>\n",
       "      <td>4.87600</td>\n",
       "      <td>504</td>\n",
       "      <td>254016</td>\n",
       "      <td>1.584325</td>\n",
       "      <td>2022-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>505 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate    t  t_squared  log_inflation       Year Month  \\\n",
       "Year                                                                         \n",
       "1980-01-31        11.34600    0          0       2.428865 1980-01-31   Jan   \n",
       "1980-02-29        11.45500    1          1       2.438426 1980-02-29   Feb   \n",
       "1980-03-31        11.56400    2          4       2.447897 1980-03-31   Mar   \n",
       "1980-04-30        11.67300    3          9       2.457278 1980-04-30   Apr   \n",
       "1980-05-31        11.78200    4         16       2.466573 1980-05-31   May   \n",
       "...                    ...  ...        ...            ...        ...   ...   \n",
       "2021-09-30         5.10300  500     250000       1.629829 2021-09-30   Sep   \n",
       "2021-10-31         5.04625  501     251001       1.618645 2021-10-31   Oct   \n",
       "2021-11-30         4.98950  502     252004       1.607336 2021-11-30   Nov   \n",
       "2021-12-31         4.93275  503     253009       1.595897 2021-12-31   Dec   \n",
       "2022-01-31         4.87600  504     254016       1.584325 2022-01-31   Jan   \n",
       "\n",
       "            year  \n",
       "Year              \n",
       "1980-01-31  1980  \n",
       "1980-02-29  1980  \n",
       "1980-03-31  1980  \n",
       "1980-04-30  1980  \n",
       "1980-05-31  1980  \n",
       "...          ...  \n",
       "2021-09-30  2021  \n",
       "2021-10-31  2021  \n",
       "2021-11-30  2021  \n",
       "2021-12-31  2021  \n",
       "2022-01-31  2022  \n",
       "\n",
       "[505 rows x 7 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_month_interpolated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9a3b72bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "lag_plot(india_month_interpolated['Inflation_rate'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a3e9fd5",
   "metadata": {},
   "source": [
    "### ACF abd PACF plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "415e383d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AfU/82iFuDnyzblWpBIVyhalSZdZQL5bm7hMvpynvsDdw4Jt1RDJ4mVw2+MzYJIVSXbCXk6tVzLLkwDdrgSTAy0ylR+VT1enioTB/aSq57vvx0YMdrq3lhQPfbJEiIg3wmSE+VUymC/N0s5h1igPfrE410Evps06eem6cQrnMZPFQt4v7xK0XOfAtlyKCyWKFyWKZyVL50Odi0g1TvZkI4OkXJjpcW7NsOPCtb1Uq8bIwnyxWmEy7XXyUbnnjwLeed3CqlB6pzwz2QqnS6aqZdRUHvvWEYjl5jO1Eocx4Ifn90lSJSgSP7PFt/WYL4cC3rlIsV6YDfaJYZryQHL0XSi/vf6m4T8ZsURz41hGFUmVGqFeP3ou+2cisZRz41lJTpTKThQrjxdJ0d8xk0cFu1gkOfMvMRKHMwUKJg1MlxgslyhV48MkXOl0tM0tlEviSLgSuBwaBmyLi2rrl7wCuSSdfAv5DRDycRdnWGdVB0/FCKf1dnvHsl5JvNTXrOk0HvqRB4AbgAmAPcL+kOyPi0ZrVngB+NyKel3QRsBU4p9myrfWqNyi9NJUcuSdH8GXKDnSznpPFEf7ZwK6IeBxA0u3AJcB04EfE/65Z/8fAhgzKtYzVh3v1yN3hbtYfsgj89cDumuk9zH30fiXwvdkWStoCbAE46aSTMqiezaYSweiLUw53s5zIIvDVYF7D1JD0eySB/4bZNhYRW0m6fBgZGXH6ZOjgVImxySIHJoq8OFkiCHbtf6nT1TKzNski8PcAG2umNwB761eS9NvATcBFEfFcBuXaPMYLJQ5MFBmbKPHiZHHGpZDRuE02sz6WReDfD5wq6RTgaeBS4O21K0g6Cfg28M6I+HkGZVoD44USYxPJUfzYRNHXupvZDE0HfkSUJF0N3EVyWebNEbFD0lXp8huBjwPHAH8jCaAUESPNlp13E4XydLiPTRYbPn7AzKwqk+vwI2IbsK1u3o01n98DvCeLsvJsslhmbCLpg3fAm9li+U7bLlYN+GSgteTH/ZpZUxz4XWSymHTRTBSTyyN/8tQLna6SmfURB34HVQO+OtA6VUyO4ItlH8mbWfYc+G00W8CbmbWDA7+FHPBm1k0c+BlywJtZN3PgN8EBb2a9xIG/CL6Kxsx6mQN/Dr6Kxsz6iQO/hrtozKyfOfBJXvzxk90vOODNrK8NdLoC3SACh72Z9T0HvplZTjjwzcxywoFvZpYTDnwzs5xw4JuZ5YQD38wsJxz4ZmY54cA3M8uJTAJf0oWSHpO0S9KHGiyXpM+lyx+R9JosyjUzs4VrOvAlDQI3ABcBm4HLJG2uW+0i4NT0ZwvwhWbLNTOzxVFENLcB6bXAJyLizen0hwEi4i9q1vlb4J6IuC2dfgw4LyL2zbXto08+PS74yM2LrtOj+8YA2Hzi6gV/Z2yyuOB1n3xuHICTj1m5uIp1yfbbUYb3ofPbb0cZvb79dpSxlO2vWj7EgLSk8u646nUPRMRIo2VZPDxtPbC7ZnoPcM4C1lkPvCzwJW0hOQtg1YmvWFKFFhP0S9HKP752bL8dZXgfOr/9dpTR69tvRxnt2IeFyiLwGzVD9acNC1knmRmxFdgKMDIyEt/4969trnYLUKkE9z3x65aXY2a2EGduXMOK4cElffeOq2ZflsWg7R5gY830BmDvEtYxM7MWyiLw7wdOlXSKpGHgUuDOunXuBC5Pr9Y5FzgwX/+9mZllq+kunYgoSboauAsYBG6OiB2SrkqX3whsAy4GdgHjwLubLdfMzBYnkzdeRcQ2klCvnXdjzecA3ptFWWZmtjS+09bMLCcc+GZmOeHANzPLCQe+mVlOOPDNzHLCgW9mlhMOfECCtUcsZ/ky/+cws/6VyXX4vU4SrzxuFQCTxTJjk0XGJkqMTRaZKlY6XDszs2w48OsctmyQw5YNctwRybQbADPrFw78ebgBMLN+4cBfpIYNwESRsckiByZKFEpuAMysOznwmzTdAKw+DHADYGbdy4GfMTcAZtatHPgt5gbAzLqFA7/N3ACYWac48DvMDYCZtYsDv8vM1gAcSBuBQqnhu9/NzOblwO9y9Q3ARKF6H4AbADNbHAd+j1kxPMiK4UGOTxuA8UJp+iawsYkixbIbADNrzIHf41YOD7FyeIgTjjzUAByYOHQncMkNgJmlmgp8SUcD3wA2Ab8E3hYRz9etsxH4CnACUAG2RsT1zZRrs6s2ACceCRHBeNoFdGCiyIuTJTcAZjnW7POAPwTcHRGnAnen0/VKwAcj4nTgXOC9kjY3Wa4tgCQOXz7EiUeu4FUnrGbk5KP4JxuO5ORjVnLU4ctYNqhOV9HM2qjZLp1LgPPSz7cA9wDX1K4QEfuAfennFyXtBNYDjzZZti2SJFYtH2LV8iHWsQJIrgI6OFXi4FSZg4USB6dKHgcw61PNBv7xaaATEfskHTfXypI2AWcB982xzhZgC8BJJ53UZPVsPtWrgI5ZdWhetREYL5R5acqNgFm/mDfwJf2IpP+93kcXU5CkVcC3gA9ExNhs60XEVmArwMjIiFOmA6YbgZp5k8Uy44WkIXAjYNab5g38iHjTbMskPSPpxPTo/kRg/yzrLSMJ+69FxLeXXFvrmGojcPThw9PzpkrlpCsobQTGCyXfF2DWxZrt0rkTuAK4Nv39nfoVJAn4IrAzIj7bZHnWRZYPDbJ8aPZG4GChxEShzFSpQrgdMOu4ZgP/WuAOSVcCTwH/GkDSOuCmiLgYeD3wTuCnkh5Kv/eRiNjWZNnWhRo1ApVKMJF2CU0UyunnkhsCszZrKvAj4jng/Abz9wIXp5//AfD1fzk2MJBcHnr48pl/brUNQXWMYKKYfHZDYJY932lrHTNXQzBZqj8jcENg1iwHvnWdgQFN3zFcKyI5I5goHGoAkjOCCuWKWwKz+TjwrWdIhxqCY+qWFUoVJktJIzBVrDCZNgSTpbIfJ2GWcuBbXxgeGmB4aIDVhy172bJiuaYBKJaZKh367HsJLE8c+Nb3lg0OsGxwgCMOe/myUrnCZKnaIMxsFHxPgfUbB77l2tDgAKsGB1i1/OX/FMqVSIO/wlSpwlSxwlQpua9gqlShWPZlpdZbHPhmsxicHjxuvDwipsN/qpSMHRTKhxqGQqmCx5KtmzjwzZZI0vQjJ+DlYwdAenZw6KygUNc4eEDZ2smBb9ZC1cHkI2ZZXionwV8sBVPl5KygWA4KaeNQKCcDy+46siw48M06aGhwgKHBARiG2c4SIoJCudKwMSiUDi3zvQg2Hwe+WZeTNP2MormUyocahKn0zKCQDi5Xf5cq4W6kHHPgm/WJ5GwBVgzPPqYAyaMrCuWkASiWI/196HO1cSiWw2cNfcaBb5YzAwPisIHqYPPcGjUOhVJypuAzh97jwDezWS2mcYgIiuWgVEkah1L5UMNQmj6TmLncJxDt5cA3s0xIYnhIDDOw4O+Uqw1CJabHIEqV5KqlYuVQQ1GuJPNL5XAj0QQHvpl1zOCAGByY/+yhVqWSNAZJY5GMM5RqupVKdcuq67rLyYFvZj1mYEAsX2QjAUmX02yNQjmCSiWoRDJdieRMYvpzhWSd6fXoyQFtB76Z5YIklg2KZDhi8Q1GI+WaRiJiZqNQThuGStQ0JJVkuhxBRFCu1DQqNY2MWvSOQAe+mdkSDQ6IQaqNSPdb+OiKmZn1tKYCX9LRkn4o6Rfp76PmWHdQ0k8kfbeZMs3MbGmaPcL/EHB3RJwK3J1Oz+b9wM4myzMzsyVqNvAvAW5JP98C/FGjlSRtAP4QuKnJ8szMbImaDfzjI2IfQPr7uFnWuw74T0Blvg1K2iJpu6Tto6OjTVbPzMyq5r1KR9KPgBMaLProQgqQ9BZgf0Q8IOm8+daPiK3AVoCRkZHeu9DVzKxLzRv4EfGm2ZZJekbSiRGxT9KJwP4Gq70eeKuki4HDgNWSbo2If7PkWpuZ2aI126VzJ3BF+vkK4Dv1K0TEhyNiQ0RsAi4F/rvD3sys/ZoN/GuBCyT9ArggnUbSOknbmq2cmZllR9HFL8uUNAo8ucSvHws8m2F12q3X6w/eh27R6/vQ6/WH9u7DyRGxttGCrg78ZkjaHhEjna7HUvV6/cH70C16fR96vf7QPfvgRyuYmeWEA9/MLCf6OfC3droCTer1+oP3oVv0+j70ev2hS/ahb/vwzcxspn4+wjczsxoOfDOznOi7wJd0oaTHJO2SNNfjmruSpI2S/oeknZJ2SHp/p+u0FL3+/gNJayR9U9L/Tf9fvLbTdVosSX+S/g39TNJtkg7rdJ3mI+lmSfsl/axm3oLfu9ENZtmHT6d/S49I+m+S1nSibn0V+JIGgRuAi4DNwGWSNne2VotWAj4YEacD5wLv7cF9gN5//8H1wPcj4lXAGfTYvkhaD/xHYCQifovkJa6XdrZWC/Jl4MK6eYt570Y3+DIv34cfAr8VEb8N/Bz4cLsrBX0W+MDZwK6IeDwiCsDtJM/s7xkRsS8iHkw/v0gSNOs7W6vF6fX3H0haDfwO8EWAiChExAsdrdTSDAErJA0BK4G9Ha7PvCLiXuDXdbMX9N6NbtFoHyLiBxFRSid/DGxoe8Xov8BfD+yumd5Dj4VlLUmbgLOA+zpclcW6jgW+/6BL/QYwCnwp7Za6SdLhna7UYkTE08BfAU8B+4ADEfGDztZqyRb63o1e8W+B73Wi4H4LfDWY15PXnUpaBXwL+EBEjHW6PgtV+/6DTtelCUPAa4AvRMRZwEG6vxthhrSf+xLgFGAdcLgkP6W2wyR9lKTb9mudKL/fAn8PsLFmegM9cBpbT9IykrD/WkR8u9P1WaTq+w9+SdKl9vuSbu1slRZtD7AnIqpnVt8kaQB6yZuAJyJiNCKKwLeB13W4Tkv1TPq+DeZ470bXk3QF8BbgHdGhG6D6LfDvB06VdIqkYZJBqjs7XKdFkSSSvuOdEfHZTtdnsfrh/QcR8Stgt6TT0lnnA492sEpL8RRwrqSV6d/U+fTYwHONed+70e0kXQhcA7w1IsY7VY++Cvx0UORq4C6SP+47ImJHZ2u1aK8H3klyZPxQ+nNxpyuVQ+8DvibpEeBM4FOdrc7ipGcn3wQeBH5K8m+9K27vn4uk24B/BE6TtEfSlczy3o1uNcs+fB44Avhh+m/6xo7UzY9WMDPLh746wjczs9k58M3McsKBb2aWEw58M7OccOCbmeWEA9/MLCcc+GZmOfH/AWzUt0u0JaJ2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEICAYAAABS0fM3AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAdIElEQVR4nO3dfZRcdZ3n8fenOzQkJDE8JDFPEMScTIJniGwvAXHGYMRJ8CE4Zx5g3YAuboZZcdTj2RXRZdDjMJ5xfGJgzWYkgsiDiKA5bHgyM1nGGWXzYAN5MBKR0E2HdBMSm5CGJt3f/aNuM5VKdbqqq6qrO7/P65w6Xfd37+/eb3U693Pv71bVVURgZmbpaqh3AWZmVl8OAjOzxDkIzMwS5yAwM0ucg8DMLHEOAjOzxDkIbFSQdEDSW0pYbrakkDRmOOoaqSR9RNLPKuj/oKQrqlmTjVwOAqsKSc9K6s522HskfVfS+CGua72kj+W3RcT4iHimOtW+sY19ko4vs19Iemu16hgJJF0v6fv5bRGxNCJuq1dNNrwcBFZNH4iI8cA5wH8EvlBOZ+XU/G9S0mzgD4AAPljr7VWq2NlN6mc8Vl0OAqu6iHgeeBB4m6STJD0gqTM7An9A0sz+ZbMj87+R9K/AQeB2cjvpm7Kzi5uy5d44Epf0Pkm/lNQlqVXS9WWWeDnwC+BW4LDhj8KzkfwhFkmPZc1PZLX9edb+XyXtlPSSpDWSpuf1P0vSo9m8PZKuzdqPl/RNSe3Z45v9ZyeSFklqk/RZSS8A382O2u+V9H1JXcBHJL1J0i2Sdkt6XtKXJTUWe8GSvpX9rrokbZL0B1n7EuBa4M+z1/RE4e9BUoOkL0jaJalD0vckvSmb1z8Ud4Wk5yS9KOnzZf57WJ05CKzqJM0CLgZ+Se5v7LvA6cBpQDdwU0GX5cAKYALwEeBfgKuz4aCri2ziFXI780nA+4C/lHRJGSVeDtyRPf5I0tRSOkXEH2ZPz85q+4GkdwN/C/wZMA3YBdwNIGkC8FPgIWA68FZgXbaOzwPnAQuAs4FzOfwM6s3AyeR+byuytmXAveRe9x3AbcChbL1vB94LHDaklmdDtq2TgTuBH0o6ISIeAm4AfpC9prOL9P1I9rgQeAswniP/Dd8JzAUWA9dJmjdAHTYCOQismn4saT/wM+D/AjdExN6I+FFEHIyIl4G/Ad5V0O/WiNgaEYci4vXBNhIR6yPiqYjoi4gngbuKrLMoSe8kt3O9JyI2Ab8B/lPJr/BIHwZWR8TmiHgN+Bxwfjb89H7ghYj4WkS8GhEvR8Tjef2+FBEdEdEJfJFcIPbrA/46Il6LiO6s7ecR8eOI6AMmAkuBT0XEKxHRAXwDuLRYkRHx/ezf4lBEfA04ntyOu9TX+PWIeCYiDmSv8dKC4akvRkR3RDwBPEEu3GyU8DijVdMlEfHT/AZJ48jtoJYAJ2XNEyQ1RkRvNt1azkYkLQS+ArwNaCK3U/thid2vAB6JiBez6Tuztm+UU0Oe6cDm/omIOCBpLzADmEUuaAbqtytvelfW1q8zIl4t6JP/ezodOA7YLam/rYEBfpeSPkPubGE6uWsjE4FTB3xVg9c6Bsg/k3oh7/lBcmcNNkr4jMBq7TPkjjwXRsREoH94RXnLFH4F7mBfiXsnsAaYFRFvAlYWrK8oSWPJDeG8S9IL2fj7p4GzJfUfwb4CjMvr9uZBVttObqfcv40TgVOA58ntlM8spR+5YbP2vOliv4P8tlbgNeDUiJiUPSZGxFmFnbLrAZ8l99pPiohJwO/499/ZYL/vYrUeAvYM0s9GCQeB1doEctcF9ks6GfjrEvrsITcWfbR1vhQRr0o6l9KHdi4BeoH55MbLFwDzyF2TuDxbpgX4Y0njsovTVw5S253ARyUtyC723gA8HhHPAg8Ab5b0qezi8ITsbAZyw1lfkDRZ0qnAdcBhb+E8mojYDTwCfE3SxOyC7pmSig2RTSC34+4Exki6jtwZQf5rmn2Ud2zdBXxa0hnKvSW4/5rCoVLrtZHNQWC19k1gLPAiuXfqPFRCn28Bf5K9y+jGIvP/G/AlSS+T24HeU2ItVwDfjYjnIuKF/ge5C58fzsa8vwH0kNs53kbuomy+64HbJO2X9GcRsQ74n8CPgN3kzgAuBciuiVwEfIDc0MnT5C64AnwZ2Ag8CTxFbnjpyyW+jn6Xkxsa2wbsI3cheVqR5R4m9y6uX5Mb1nmVw4eQ+ofV9krazJFWk3s312PAb7P+nyizVhvB5BvTmJmlzWcEZmaJcxCYmSXOQWBmljgHgZlZ4kblB8pOPfXUmD17dr3LMDMbVTZt2vRiREwubB+VQTB79mw2btxY7zLMzEYVSbuKtXtoyMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscVUJAkmrs1vYbRlgviTdmN3O70lJ5+TNWyJpRzbvmmrUU0xvX7Bu+x5uXPc067bvobfP37FkZgbVe/voreS+wfF7A8xfCszJHguBbwMLs/ur3kzuGxrbgA2S1kTEtirVBeRCYPktj9PSup/unl7GNjWyYNYkbr9yIY0Ng36NfVnbWb+jg63tXZw1fSKL5k6p6vrNzGqhKkEQEY9lt+YbyDLge5H7qtNfSJokaRowG9gZEc8ASLo7W7aqQbB+Rwctrfs52JO7IdbBnl5aWvezfkcHi+eVdLvaQQ1X2JiZVdtwXSOYweHff96WtQ3UfgRJKyRtlLSxs7OzrI1vbe+iu6f3sLbunl62tXeVtZ6jyQ+b4PCwMTMbyYYrCIodEsdR2o9sjFgVEc0R0Tx58hGfkD6qs6ZPZGxT42FtY5samT994gA9yjccYWNmVgvDFQRt5G7k3W8mufugDtReVYvmTmHBrEn0j9CMy4ZtFs2dUrVtDEfYmJnVwnAFwRrg8uzdQ+cBv8vuuboBmJPdC7WJ3C3+1lR7440N4vYrF/LWKeOZOWks/3DZ26s+dj8cYWNmVgtVuVgs6S5gEXCqpDZyNyg/DiAiVgJrgYuBncBB4KPZvEOSriZ3T9VGYHVEbK1GTYUaG8RJ45o4aRxVu0BcuP7br1zI0m89xsHXevnisrP8riEzGxWq9a6hywaZH8DHB5i3llxQjHq1Dhszs1rwJ4vNzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscVUJAklLJO2QtFPSNUXm/3dJLdlji6ReSSdn856V9FQ2b2M16jEzs9JVfPN6SY3AzcBFQBuwQdKaiNjWv0xEfBX4arb8B4BPR8RLeau5MCJerLQWMzMrXzXOCM4FdkbEMxHRA9wNLDvK8pcBd1Vhu2ZmVgXVCIIZQGvedFvWdgRJ44AlwI/ymgN4RNImSSuqUI+ZmZWh4qEhQEXaYoBlPwD8a8Gw0AUR0S5pCvCopF9FxGNHbCQXEisATjvttEprNjOzTDXOCNqAWXnTM4H2AZa9lIJhoYhoz352APeTG2o6QkSsiojmiGiePHlyxUWbmVlONYJgAzBH0hmSmsjt7NcULiTpTcC7gJ/ktZ0oaUL/c+C9wJYq1GRmZiWqeGgoIg5Juhp4GGgEVkfEVklXZfNXZot+CHgkIl7J6z4VuF9Sfy13RsRDldZkZmalq8Y1AiJiLbC2oG1lwfStwK0Fbc8AZ1ejBjMzGxp/stjMLHEOAjOzxDkIzMwS5yAwM0ucg8DMLHEOAjOzxDkIzMwS5yAwM0ucg8DMLHEOAjOzxDkIzMwS5yAwM0ucg8DMLHEOAjOzxDkIzMwS5yAwM0ucg8DMLHEOAjOzxDkIzMwS5yAwM0tcVYJA0hJJOyTtlHRNkfmLJP1OUkv2uK7UvmZmVltjKl2BpEbgZuAioA3YIGlNRGwrWPRfIuL9Q+xrZmY1Uo0zgnOBnRHxTET0AHcDy4ahr5mZVUE1gmAG0Jo33Za1FTpf0hOSHpR0Vpl9kbRC0kZJGzs7O6tQtpmZQXWCQEXaomB6M3B6RJwN/APw4zL65hojVkVEc0Q0T548eai1mplZgWoEQRswK296JtCev0BEdEXEgez5WuA4SaeW0tfMzGqrGkGwAZgj6QxJTcClwJr8BSS9WZKy5+dm291bSl8zM6utit81FBGHJF0NPAw0AqsjYqukq7L5K4E/Af5S0iGgG7g0IgIo2rfSmszMrHQVBwG8MdyztqBtZd7zm4CbSu1rZmbDx58sNjNLnIPAzCxxDgIzs8Q5CMzMEucgMDNLnIPAzCxxDgIzs8Q5CMzMEucgMDNLnIPAzCxxDgIzs8Q5CMzMEucgMDNLnIPAzCxxDgIzs8Q5CMzMEucgMDNLnIPAzCxxDgIzs8RVJQgkLZG0Q9JOSdcUmf9hSU9mj3+TdHbevGclPSWpRdLGatRjZmalq/jm9ZIagZuBi4A2YIOkNRGxLW+x3wLvioh9kpYCq4CFefMvjIgXK63FzMzKV40zgnOBnRHxTET0AHcDy/IXiIh/i4h92eQvgJlV2K6ZmVVBNYJgBtCaN92WtQ3kSuDBvOkAHpG0SdKKgTpJWiFpo6SNnZ2dFRVsZmb/ruKhIUBF2qLogtKF5ILgnXnNF0REu6QpwKOSfhURjx2xwohV5IaUaG5uLrp+MzMrXzXOCNqAWXnTM4H2woUk/T7wHWBZROztb4+I9uxnB3A/uaEmMzMbJtUIgg3AHElnSGoCLgXW5C8g6TTgPmB5RPw6r/1ESRP6nwPvBbZUoSYzMytRxUNDEXFI0tXAw0AjsDoitkq6Kpu/ErgOOAX4X5IADkVEMzAVuD9rGwPcGREPVVqTmZmVrhrXCIiItcDagraVec8/BnysSL9ngLML283MbPj4k8VmZolzEJiZJc5BYGaWOAeBmVniHARmZolzEJiZJc5BYGaWOAeBmVniHARmZomryieLzcysdL19wfodHWxt7+Ks6RNZNHcKjQ3Fvsh5eDgIzMyGUW9fsPyWx2lp3U93Ty9jmxpZMGsSt1+5sG5h4KEhM7MCvX3Buu17uHHd06zbvofevurdAmX9jg5aWvdzsKeXAA729NLSup/1Ozqqto1y+YzAzEadWg6t1PqIfWt7F909vYe1dff0sq29i8Xzpla8/qFwEAzi57/ZO/hCebpefX1I/cyOFX19QUvrfp7d+wqzTzmRBbMm0VDFIY++vuCGB7ezs+MAPYf6aBrTwFunjOfapfOqsp3Nu/axadc+XjvUB+SO2Dft2sfK9b/hnNNPqnj9jRJNYxreWD9A05gGGqSS9hvnn3lKxTUUchCYJaaWO+pa76QBWlr3s7PjwBs70tcO9bGz4wAtrfursqN+du8r9OTtpAF6DvXx7N5XqrL+BbMm8dYp49m2u4sIOD77HS2YNanidQ+Vg8AsIbXeUdd6Jw2131HPPuXEokfss085seJ1AzQ0iGuXzuOz9z3Ja6/38pF3nFH1s6aya6rbls2sqL6+YPOufdy3uY3Nu/bRV8ULlfk76uDwHXU1HG0nXS39O+p81dxR9x+xK9sv1+KIvaFBTDhhDKdOOJ5zTj+priEAPiMwG1FqfcQ+2o+mofZDKyPxiL3WfEZgVoZaHq1D7Y/Yj5Wj6WuXzmPGpLFMHt/EX717TlWvQfRvYyQdsdeazwjMSjQcF0JH+4XK4Tqa7t9RTzhhTNWuPaSsKmcEkpZI2iFpp6RrisyXpBuz+U9KOqfUvmYjRa2P1qH2R+w+mrZiKg4CSY3AzcBSYD5wmaT5BYstBeZkjxXAt8voa1ayWg7dDMeF0BQvVFr9KaKy/yiSzgeuj4g/yqY/BxARf5u3zP8G1kfEXdn0DmARMHuwvsWcfPq8uOja1WXXum13FwDzp00suU//B8RKtWvvQQBOP2VcWf2schHBcy910/16LxEgwdjjGjnt5LFIle/sXn71EM/v7yb/v4wEMyaNZcIJ1RtljQh+++JB+iKYOvEExh/fWJX689X673Q4/h+M9tcw1PVPPOG4IW/znqvesSkimgvbq/HXOwNozZtuAxaWsMyMEvsCIGkFubMJxk87c0iFlhMAQ1XrABipf5wjYRsHXut9IwQAIqD79V4OvNZblR31+OMbGXtc4xFBM/74xorXnU8Sb5lcvXfZFFPrv9PhOBAa7a9hJB0sViMIih2qFJ5mDLRMKX1zjRGrgFUAzc3N8YO/OL+cGodspH1VxJce2ArAde8/a1Suv5bbuG9zG/duaju8MeD8t5zCH58zsyrbqPXXJ5gNppKvmLjnquLt1QiCNmBW3vRMoL3EZZpK6GtWkuF4D3tDgzjn9JP8ThU7plTjXUMbgDmSzpDUBFwKrClYZg1wefbuofOA30XE7hL7mpWk/0Lr8WMaECPjO1zMRoOKzwgi4pCkq4GHgUZgdURslXRVNn8lsBa4GNgJHAQ+erS+ldZkaep/a6SHbszKU5W3OkTEWnI7+/y2lXnPA/h4qX3NhspDN2bl81dMmJklzkFgw6qvL3j51UN0vvxaTb6rx8zK5yCwYdP/XT3P7+/mxQM93PhPT3PDg9sdBmZ15iCwYdP/XT39H/iqxXf1mFn5/O2jg6jF/UEr0f/x8lrVVcv1b3j2paLf1dMXMeJ+z2Yp8RmBDZuzpk9kbNPhX8cwtqmR+dNr/9UfZjYwB4ENm0Vzp7Bg1iTGNTUiYFxTIwtmTWLR3Cn1Ls0saR4asmHT2CBuv3Ih63d0sK29i/nTJ7Jo7hQa/YEvs7pyENiwamwQi+dNZfG8qfUuxcwyHhoyM0ucg8DMLHEOAjOzxDkIzMwS5yAwM0ucg8DMLHEOAjOzxDkIzMwS5yAwM0ucg8DMLHEVBYGkkyU9Kunp7OcRN4qVNEvSP0vaLmmrpE/mzbte0vOSWrLHxZXUY2Zm5av0jOAaYF1EzAHWZdOFDgGfiYh5wHnAxyXNz5v/jYhYkD18E/s66u0L9h3s4fl93azbvode3znMLAmVBsEy4Lbs+W3AJYULRMTuiNicPX8Z2A7MqHC7VmW9fcHyWx5nZ8cB2vZ384m7fsnyWx53GJgloNIgmBoRuyG3wweO+sXykmYDbwcez2u+WtKTklYXG1rK67tC0kZJGzs7Oyss2wqt39FBS+t++vf7B3t6aWndz/odHfUtzMxqbtAgkPRTSVuKPJaVsyFJ44EfAZ+KiK6s+dvAmcACYDfwtYH6R8SqiGiOiObJkyeXs2krwdb2Lrp7eg9r6+7pZVt71wA9zOxYMej9CCLiPQPNk7RH0rSI2C1pGlD08FHSceRC4I6IuC9v3XvylvlH4IFyirfq6b+N5MG8MPBtJM3SUOnQ0Brgiuz5FcBPCheQJOAWYHtEfL1g3rS8yQ8BWyqsx4bIt5E0S1eldyj7CnCPpCuB54A/BZA0HfhORFwMXAAsB56S1JL1uzZ7h9DfSVoABPAs8BcV1mND5NtImqWroiCIiL3A4iLt7cDF2fOfAUX3JhGxvJLtW3X5NpJmafIni83MEucgMDNLnIPAzCxxDgIzs8Q5CMzMEucgMDNLnIPAzCxxDgIzs8Q5CMzMEucgMDNLnIPAzCxxDgIzs8Q5CMzMEucgMDNLnIPAzCxxDgIzs8Q5CMzMEucgMDNLnIPAzCxxFQWBpJMlPSrp6eznSQMs96ykpyS1SNpYbn8zM6udSs8IrgHWRcQcYF02PZALI2JBRDQPsb+ZmdVApUGwDLgte34bcMkw9zczswpVGgRTI2I3QPZzygDLBfCIpE2SVgyhv5mZ1ciYwRaQ9FPgzUVmfb6M7VwQEe2SpgCPSvpVRDxWRn+yAFkBcNppp5XT1czMjmLQIIiI9ww0T9IeSdMiYrekaUDHAOtoz352SLofOBd4DCipf9Z3FbAKoLm5OQar28zMSlPp0NAa4Irs+RXATwoXkHSipAn9z4H3AltK7W9mZrVVaRB8BbhI0tPARdk0kqZLWpstMxX4maQngP8H/J+IeOho/c3MbPgMOjR0NBGxF1hcpL0duDh7/gxwdjn9zcxs+PiTxWZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B8Eo0tsX7DvYw/P7ulm3fQ+9fVHvkszsGFBREEg6WdKjkp7Ofp5UZJm5klryHl2SPpXNu17S83nzLq6knmNZb1+w/JbH2dlxgLb93Xzirl+y/JbHHQZmVrFKzwiuAdZFxBxgXTZ9mIjYERELImIB8B+Ag8D9eYt8o39+RKytsJ5j1vodHbS07qd/v3+wp5eW1v2s39FR38LMbNSrNAiWAbdlz28DLhlk+cXAbyJiV4XbTc7W9i66e3oPa+vu6WVbe1edKjKzY0WlQTA1InYDZD+nDLL8pcBdBW1XS3pS0upiQ0v9JK2QtFHSxs7OzsqqHoXOmj6RsU2Nh7WNbWpk/vSJdarIzI4VgwaBpJ9K2lLksaycDUlqAj4I/DCv+dvAmcACYDfwtYH6R8SqiGiOiObJkyeXs+ljwqK5U1gwaxLjmhoRMK6pkQWzJrFo7mDZa2Z2dGMGWyAi3jPQPEl7JE2LiN2SpgFHG7BeCmyOiD15637juaR/BB4orez0NDaI269cyPodHWxr72L+9IksmjuFxgbVuzQzG+UGDYJBrAGuAL6S/fzJUZa9jIJhof4QySY/BGypsJ5jWmODWDxvKovnTa13KWZ2DKn0GsFXgIskPQ1clE0jabqkN94BJGlcNv++gv5/J+kpSU8CFwKfrrAeMzMrU0VnBBGxl9w7gQrb24GL86YPAqcUWW55Jds3M7PK+ZPFZmaJcxCYmSXOQWBmljhFjL7vqpHUCQz108mnAi9WsZx68Guov9FeP/g1jATDXf/pEXHEB7FGZRBUQtLGiGiudx2V8Guov9FeP/g1jAQjpX4PDZmZJc5BYGaWuBSDYFW9C6gCv4b6G+31g1/DSDAi6k/uGoGZmR0uxTMCMzPL4yAwM0tcUkEgaYmkHZJ2SjritpojmaRZkv5Z0nZJWyV9st41DZWkRkm/lDQqv3Zc0iRJ90r6VfbvcX69ayqHpE9nf0NbJN0l6YR61zSY7MZVHZK25LUNes/0kWSA1/DV7O/oSUn3S5pUj9qSCQJJjcDN5O6LMB+4TNL8+lZVlkPAZyJiHnAe8PFRVn++TwLb611EBb4FPBQRvweczSh6LZJmAH8FNEfE24BGcncOHOluBZYUtA16z/QR5laOfA2PAm+LiN8Hfg18briLgoSCADgX2BkRz0RED3A3uXsujwoRsTsiNmfPXya385lR36rKJ2km8D7gO/WuZSgkTQT+ELgFICJ6ImJ/XYsq3xhgrKQxwDigvc71DCoiHgNeKmgu957pdVXsNUTEIxFxKJv8BTBz2AsjrSCYAbTmTbcxCnekAJJmA28HHq9zKUPxTeB/AH11rmOo3gJ0At/Nhre+I+nEehdVqoh4Hvh74Dlyt4f9XUQ8Ut+qhqzce6aPdP8FeLAeG04pCIrd03HUvXdW0njgR8CnIqKr3vWUQ9L7gY6I2FTvWiowBjgH+HZEvB14hZE/JPGGbBx9GXAGMB04UdJ/rm9VJunz5IZ/76jH9lMKgjZgVt70TEbBKXE+SceRC4E7IqLwbm+jwQXAByU9S25o7t2Svl/fksrWBrRFRP/Z2L3kgmG0eA/w24jojIjXyd018B11rmmo9mT3SqeEe6aPWJKuAN4PfDjq9MGulIJgAzBH0hmSmshdIFtT55pKJknkxqW3R8TX613PUETE5yJiZkTMJvf7/6eIGFVHoxHxAtAqaW7WtBjYVseSyvUccJ6kcdnf1GJG0cXuAv33TIfB75k+IklaAnwW+GB2J8e6SCYIsgsyVwMPk/vDvycitta3qrJcACwndxTdkj0uHqyT1cQngDuye20vAG6obzmly85k7gU2A0+R2weMiK85OBpJdwE/B+ZKapN0JQPcM32kGuA13ARMAB7N/k+vrEtt/ooJM7O0JXNGYGZmxTkIzMwS5yAwM0ucg8DMLHEOAjOzxDkIzMwS5yAwM0vc/wfo9MsvJICiGAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.graphics.tsaplots as tsa_plots\n",
    "tsa_plots.plot_acf(india_month_interpolated.Inflation_rate,lags=12)\n",
    "tsa_plots.plot_pacf(india_month_interpolated.Inflation_rate,lags=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4dc0272e",
   "metadata": {},
   "source": [
    "### Time series decomposition plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "a60375d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 2160x1080 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30,15))\n",
    "decompose_ts_add = seasonal_decompose(india_month_interpolated['Inflation_rate'],period=12)\n",
    "decompose_ts_add.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "38976f99",
   "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>Inflation_rate</th>\n",
       "      <th>t</th>\n",
       "      <th>t_squared</th>\n",
       "      <th>log_inflation</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>year</th>\n",
       "      <th>Apr</th>\n",
       "      <th>Aug</th>\n",
       "      <th>Dec</th>\n",
       "      <th>Feb</th>\n",
       "      <th>Jan</th>\n",
       "      <th>Jul</th>\n",
       "      <th>Jun</th>\n",
       "      <th>Mar</th>\n",
       "      <th>May</th>\n",
       "      <th>Nov</th>\n",
       "      <th>Oct</th>\n",
       "      <th>Sep</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-31</th>\n",
       "      <td>11.346</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.428865</td>\n",
       "      <td>1980-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>1980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-02-29</th>\n",
       "      <td>11.455</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2.438426</td>\n",
       "      <td>1980-02-29</td>\n",
       "      <td>Feb</td>\n",
       "      <td>1980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.564</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2.447897</td>\n",
       "      <td>1980-03-31</td>\n",
       "      <td>Mar</td>\n",
       "      <td>1980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-04-30</th>\n",
       "      <td>11.673</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>2.457278</td>\n",
       "      <td>1980-04-30</td>\n",
       "      <td>Apr</td>\n",
       "      <td>1980</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-05-31</th>\n",
       "      <td>11.782</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>2.466573</td>\n",
       "      <td>1980-05-31</td>\n",
       "      <td>May</td>\n",
       "      <td>1980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate  t  t_squared  log_inflation       Year Month  \\\n",
       "Year                                                                       \n",
       "1980-01-31          11.346  0          0       2.428865 1980-01-31   Jan   \n",
       "1980-02-29          11.455  1          1       2.438426 1980-02-29   Feb   \n",
       "1980-03-31          11.564  2          4       2.447897 1980-03-31   Mar   \n",
       "1980-04-30          11.673  3          9       2.457278 1980-04-30   Apr   \n",
       "1980-05-31          11.782  4         16       2.466573 1980-05-31   May   \n",
       "\n",
       "            year  Apr  Aug  Dec  Feb  Jan  Jul  Jun  Mar  May  Nov  Oct  Sep  \n",
       "Year                                                                          \n",
       "1980-01-31  1980    0    0    0    0    1    0    0    0    0    0    0    0  \n",
       "1980-02-29  1980    0    0    0    1    0    0    0    0    0    0    0    0  \n",
       "1980-03-31  1980    0    0    0    0    0    0    0    1    0    0    0    0  \n",
       "1980-04-30  1980    1    0    0    0    0    0    0    0    0    0    0    0  \n",
       "1980-05-31  1980    0    0    0    0    0    0    0    0    1    0    0    0  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummies=pd.DataFrame(pd.get_dummies(india_month_interpolated['Month']))\n",
    "india_month_interpolated=pd.concat([india_month_interpolated,dummies],axis=1)\n",
    "india_month_interpolated.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "1a93dd5e",
   "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>Month</th>\n",
       "      <th>Apr</th>\n",
       "      <th>Aug</th>\n",
       "      <th>Dec</th>\n",
       "      <th>Feb</th>\n",
       "      <th>Jan</th>\n",
       "      <th>Jul</th>\n",
       "      <th>Jun</th>\n",
       "      <th>Mar</th>\n",
       "      <th>May</th>\n",
       "      <th>Nov</th>\n",
       "      <th>Oct</th>\n",
       "      <th>Sep</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980</th>\n",
       "      <td>11.67300</td>\n",
       "      <td>12.109000</td>\n",
       "      <td>12.545000</td>\n",
       "      <td>11.455000</td>\n",
       "      <td>11.346</td>\n",
       "      <td>12.0000</td>\n",
       "      <td>11.891000</td>\n",
       "      <td>11.564000</td>\n",
       "      <td>11.782000</td>\n",
       "      <td>12.436000</td>\n",
       "      <td>12.32700</td>\n",
       "      <td>12.218000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>11.42450</td>\n",
       "      <td>9.785167</td>\n",
       "      <td>8.145833</td>\n",
       "      <td>12.244167</td>\n",
       "      <td>12.654</td>\n",
       "      <td>10.1950</td>\n",
       "      <td>10.604833</td>\n",
       "      <td>11.834333</td>\n",
       "      <td>11.014667</td>\n",
       "      <td>8.555667</td>\n",
       "      <td>8.96550</td>\n",
       "      <td>9.375333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>8.94150</td>\n",
       "      <td>10.548833</td>\n",
       "      <td>12.156167</td>\n",
       "      <td>8.137833</td>\n",
       "      <td>7.736</td>\n",
       "      <td>10.1470</td>\n",
       "      <td>9.745167</td>\n",
       "      <td>8.539667</td>\n",
       "      <td>9.343333</td>\n",
       "      <td>11.754333</td>\n",
       "      <td>11.35250</td>\n",
       "      <td>10.950667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>11.04775</td>\n",
       "      <td>9.034083</td>\n",
       "      <td>7.020417</td>\n",
       "      <td>12.054583</td>\n",
       "      <td>12.558</td>\n",
       "      <td>9.5375</td>\n",
       "      <td>10.040917</td>\n",
       "      <td>11.551167</td>\n",
       "      <td>10.544333</td>\n",
       "      <td>7.523833</td>\n",
       "      <td>8.02725</td>\n",
       "      <td>8.530667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>6.45050</td>\n",
       "      <td>6.361833</td>\n",
       "      <td>6.273167</td>\n",
       "      <td>6.494833</td>\n",
       "      <td>6.517</td>\n",
       "      <td>6.3840</td>\n",
       "      <td>6.406167</td>\n",
       "      <td>6.472667</td>\n",
       "      <td>6.428333</td>\n",
       "      <td>6.295333</td>\n",
       "      <td>6.31750</td>\n",
       "      <td>6.339667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>6.91050</td>\n",
       "      <td>7.789833</td>\n",
       "      <td>8.669167</td>\n",
       "      <td>6.470833</td>\n",
       "      <td>6.251</td>\n",
       "      <td>7.5700</td>\n",
       "      <td>7.350167</td>\n",
       "      <td>6.690667</td>\n",
       "      <td>7.130333</td>\n",
       "      <td>8.449333</td>\n",
       "      <td>8.22950</td>\n",
       "      <td>8.009667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>8.93150</td>\n",
       "      <td>8.988167</td>\n",
       "      <td>9.044833</td>\n",
       "      <td>8.903167</td>\n",
       "      <td>8.889</td>\n",
       "      <td>8.9740</td>\n",
       "      <td>8.959833</td>\n",
       "      <td>8.917333</td>\n",
       "      <td>8.945667</td>\n",
       "      <td>9.030667</td>\n",
       "      <td>9.01650</td>\n",
       "      <td>9.002333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>8.59775</td>\n",
       "      <td>7.982750</td>\n",
       "      <td>7.367750</td>\n",
       "      <td>8.905250</td>\n",
       "      <td>9.059</td>\n",
       "      <td>8.1365</td>\n",
       "      <td>8.290250</td>\n",
       "      <td>8.751500</td>\n",
       "      <td>8.444000</td>\n",
       "      <td>7.521500</td>\n",
       "      <td>7.67525</td>\n",
       "      <td>7.829000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>6.55275</td>\n",
       "      <td>5.671083</td>\n",
       "      <td>4.789417</td>\n",
       "      <td>6.993583</td>\n",
       "      <td>7.214</td>\n",
       "      <td>5.8915</td>\n",
       "      <td>6.111917</td>\n",
       "      <td>6.773167</td>\n",
       "      <td>6.332333</td>\n",
       "      <td>5.009833</td>\n",
       "      <td>5.23025</td>\n",
       "      <td>5.450667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>6.22600</td>\n",
       "      <td>8.435333</td>\n",
       "      <td>10.644667</td>\n",
       "      <td>5.121333</td>\n",
       "      <td>4.569</td>\n",
       "      <td>7.8830</td>\n",
       "      <td>7.330667</td>\n",
       "      <td>5.673667</td>\n",
       "      <td>6.778333</td>\n",
       "      <td>10.092333</td>\n",
       "      <td>9.54000</td>\n",
       "      <td>8.987667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>11.76850</td>\n",
       "      <td>12.530500</td>\n",
       "      <td>13.292500</td>\n",
       "      <td>11.387500</td>\n",
       "      <td>11.197</td>\n",
       "      <td>12.3400</td>\n",
       "      <td>12.149500</td>\n",
       "      <td>11.578000</td>\n",
       "      <td>11.959000</td>\n",
       "      <td>13.102000</td>\n",
       "      <td>12.91150</td>\n",
       "      <td>12.721000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>12.57800</td>\n",
       "      <td>11.371333</td>\n",
       "      <td>10.164667</td>\n",
       "      <td>13.181333</td>\n",
       "      <td>13.483</td>\n",
       "      <td>11.6730</td>\n",
       "      <td>11.974667</td>\n",
       "      <td>12.879667</td>\n",
       "      <td>12.276333</td>\n",
       "      <td>10.466333</td>\n",
       "      <td>10.76800</td>\n",
       "      <td>11.069667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>9.21700</td>\n",
       "      <td>8.355667</td>\n",
       "      <td>7.494333</td>\n",
       "      <td>9.647667</td>\n",
       "      <td>9.863</td>\n",
       "      <td>8.5710</td>\n",
       "      <td>8.786333</td>\n",
       "      <td>9.432333</td>\n",
       "      <td>9.001667</td>\n",
       "      <td>7.709667</td>\n",
       "      <td>7.92500</td>\n",
       "      <td>8.140333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>8.02800</td>\n",
       "      <td>9.026667</td>\n",
       "      <td>10.025333</td>\n",
       "      <td>7.528667</td>\n",
       "      <td>7.279</td>\n",
       "      <td>8.7770</td>\n",
       "      <td>8.527333</td>\n",
       "      <td>7.778333</td>\n",
       "      <td>8.277667</td>\n",
       "      <td>9.775667</td>\n",
       "      <td>9.52600</td>\n",
       "      <td>9.276333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>10.19675</td>\n",
       "      <td>10.092417</td>\n",
       "      <td>9.988083</td>\n",
       "      <td>10.248917</td>\n",
       "      <td>10.275</td>\n",
       "      <td>10.1185</td>\n",
       "      <td>10.144583</td>\n",
       "      <td>10.222833</td>\n",
       "      <td>10.170667</td>\n",
       "      <td>10.014167</td>\n",
       "      <td>10.04025</td>\n",
       "      <td>10.066333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>9.82950</td>\n",
       "      <td>9.652833</td>\n",
       "      <td>9.476167</td>\n",
       "      <td>9.917833</td>\n",
       "      <td>9.962</td>\n",
       "      <td>9.6970</td>\n",
       "      <td>9.741167</td>\n",
       "      <td>9.873667</td>\n",
       "      <td>9.785333</td>\n",
       "      <td>9.520333</td>\n",
       "      <td>9.56450</td>\n",
       "      <td>9.608667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>8.78450</td>\n",
       "      <td>7.921167</td>\n",
       "      <td>7.057833</td>\n",
       "      <td>9.216167</td>\n",
       "      <td>9.432</td>\n",
       "      <td>8.1370</td>\n",
       "      <td>8.352833</td>\n",
       "      <td>9.000333</td>\n",
       "      <td>8.568667</td>\n",
       "      <td>7.273667</td>\n",
       "      <td>7.48950</td>\n",
       "      <td>7.705333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>8.41325</td>\n",
       "      <td>10.508250</td>\n",
       "      <td>12.603250</td>\n",
       "      <td>7.365750</td>\n",
       "      <td>6.842</td>\n",
       "      <td>9.9845</td>\n",
       "      <td>9.460750</td>\n",
       "      <td>7.889500</td>\n",
       "      <td>8.937000</td>\n",
       "      <td>12.079500</td>\n",
       "      <td>11.55575</td>\n",
       "      <td>11.032000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>11.26975</td>\n",
       "      <td>8.793417</td>\n",
       "      <td>6.317083</td>\n",
       "      <td>12.507917</td>\n",
       "      <td>13.127</td>\n",
       "      <td>9.4125</td>\n",
       "      <td>10.031583</td>\n",
       "      <td>11.888833</td>\n",
       "      <td>10.650667</td>\n",
       "      <td>6.936167</td>\n",
       "      <td>7.55525</td>\n",
       "      <td>8.174333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>5.23125</td>\n",
       "      <td>4.608917</td>\n",
       "      <td>3.986583</td>\n",
       "      <td>5.542417</td>\n",
       "      <td>5.698</td>\n",
       "      <td>4.7645</td>\n",
       "      <td>4.920083</td>\n",
       "      <td>5.386833</td>\n",
       "      <td>5.075667</td>\n",
       "      <td>4.142167</td>\n",
       "      <td>4.29775</td>\n",
       "      <td>4.453333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>3.95100</td>\n",
       "      <td>4.111000</td>\n",
       "      <td>4.271000</td>\n",
       "      <td>3.871000</td>\n",
       "      <td>3.831</td>\n",
       "      <td>4.0710</td>\n",
       "      <td>4.031000</td>\n",
       "      <td>3.911000</td>\n",
       "      <td>3.991000</td>\n",
       "      <td>4.231000</td>\n",
       "      <td>4.19100</td>\n",
       "      <td>4.151000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>4.22850</td>\n",
       "      <td>4.118500</td>\n",
       "      <td>4.008500</td>\n",
       "      <td>4.283500</td>\n",
       "      <td>4.311</td>\n",
       "      <td>4.1460</td>\n",
       "      <td>4.173500</td>\n",
       "      <td>4.256000</td>\n",
       "      <td>4.201000</td>\n",
       "      <td>4.036000</td>\n",
       "      <td>4.06350</td>\n",
       "      <td>4.091000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>3.95175</td>\n",
       "      <td>3.912750</td>\n",
       "      <td>3.873750</td>\n",
       "      <td>3.971250</td>\n",
       "      <td>3.981</td>\n",
       "      <td>3.9225</td>\n",
       "      <td>3.932250</td>\n",
       "      <td>3.961500</td>\n",
       "      <td>3.942000</td>\n",
       "      <td>3.883500</td>\n",
       "      <td>3.89325</td>\n",
       "      <td>3.903000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>3.85400</td>\n",
       "      <td>3.840667</td>\n",
       "      <td>3.827333</td>\n",
       "      <td>3.860667</td>\n",
       "      <td>3.864</td>\n",
       "      <td>3.8440</td>\n",
       "      <td>3.847333</td>\n",
       "      <td>3.857333</td>\n",
       "      <td>3.850667</td>\n",
       "      <td>3.830667</td>\n",
       "      <td>3.83400</td>\n",
       "      <td>3.837333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>3.96900</td>\n",
       "      <td>4.162333</td>\n",
       "      <td>4.355667</td>\n",
       "      <td>3.872333</td>\n",
       "      <td>3.824</td>\n",
       "      <td>4.1140</td>\n",
       "      <td>4.065667</td>\n",
       "      <td>3.920667</td>\n",
       "      <td>4.017333</td>\n",
       "      <td>4.307333</td>\n",
       "      <td>4.25900</td>\n",
       "      <td>4.210667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>4.97725</td>\n",
       "      <td>5.741583</td>\n",
       "      <td>6.505917</td>\n",
       "      <td>4.595083</td>\n",
       "      <td>4.404</td>\n",
       "      <td>5.5505</td>\n",
       "      <td>5.359417</td>\n",
       "      <td>4.786167</td>\n",
       "      <td>5.168333</td>\n",
       "      <td>6.314833</td>\n",
       "      <td>6.12375</td>\n",
       "      <td>5.932667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>6.57375</td>\n",
       "      <td>6.409417</td>\n",
       "      <td>6.245083</td>\n",
       "      <td>6.655917</td>\n",
       "      <td>6.697</td>\n",
       "      <td>6.4505</td>\n",
       "      <td>6.491583</td>\n",
       "      <td>6.614833</td>\n",
       "      <td>6.532667</td>\n",
       "      <td>6.286167</td>\n",
       "      <td>6.32725</td>\n",
       "      <td>6.368333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>6.92525</td>\n",
       "      <td>7.886917</td>\n",
       "      <td>8.848583</td>\n",
       "      <td>6.444417</td>\n",
       "      <td>6.204</td>\n",
       "      <td>7.6465</td>\n",
       "      <td>7.406083</td>\n",
       "      <td>6.684833</td>\n",
       "      <td>7.165667</td>\n",
       "      <td>8.608167</td>\n",
       "      <td>8.36775</td>\n",
       "      <td>8.127333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>9.89525</td>\n",
       "      <td>10.970250</td>\n",
       "      <td>12.045250</td>\n",
       "      <td>9.357750</td>\n",
       "      <td>9.089</td>\n",
       "      <td>10.7015</td>\n",
       "      <td>10.432750</td>\n",
       "      <td>9.626500</td>\n",
       "      <td>10.164000</td>\n",
       "      <td>11.776500</td>\n",
       "      <td>11.50775</td>\n",
       "      <td>11.239000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>11.86750</td>\n",
       "      <td>11.272167</td>\n",
       "      <td>10.676833</td>\n",
       "      <td>12.165167</td>\n",
       "      <td>12.314</td>\n",
       "      <td>11.4210</td>\n",
       "      <td>11.569833</td>\n",
       "      <td>12.016333</td>\n",
       "      <td>11.718667</td>\n",
       "      <td>10.825667</td>\n",
       "      <td>10.97450</td>\n",
       "      <td>11.123333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>10.27100</td>\n",
       "      <td>9.928333</td>\n",
       "      <td>9.585667</td>\n",
       "      <td>10.442333</td>\n",
       "      <td>10.528</td>\n",
       "      <td>10.0140</td>\n",
       "      <td>10.099667</td>\n",
       "      <td>10.356667</td>\n",
       "      <td>10.185333</td>\n",
       "      <td>9.671333</td>\n",
       "      <td>9.75700</td>\n",
       "      <td>9.842667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>9.62500</td>\n",
       "      <td>9.791667</td>\n",
       "      <td>9.958333</td>\n",
       "      <td>9.541667</td>\n",
       "      <td>9.500</td>\n",
       "      <td>9.7500</td>\n",
       "      <td>9.708333</td>\n",
       "      <td>9.583333</td>\n",
       "      <td>9.666667</td>\n",
       "      <td>9.916667</td>\n",
       "      <td>9.87500</td>\n",
       "      <td>9.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>9.85000</td>\n",
       "      <td>9.650000</td>\n",
       "      <td>9.450000</td>\n",
       "      <td>9.950000</td>\n",
       "      <td>10.000</td>\n",
       "      <td>9.7000</td>\n",
       "      <td>9.750000</td>\n",
       "      <td>9.900000</td>\n",
       "      <td>9.800000</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>9.55000</td>\n",
       "      <td>9.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>8.50000</td>\n",
       "      <td>7.300000</td>\n",
       "      <td>6.100000</td>\n",
       "      <td>9.100000</td>\n",
       "      <td>9.400</td>\n",
       "      <td>7.6000</td>\n",
       "      <td>7.900000</td>\n",
       "      <td>8.800000</td>\n",
       "      <td>8.200000</td>\n",
       "      <td>6.400000</td>\n",
       "      <td>6.70000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>5.57500</td>\n",
       "      <td>5.275000</td>\n",
       "      <td>4.975000</td>\n",
       "      <td>5.725000</td>\n",
       "      <td>5.800</td>\n",
       "      <td>5.3500</td>\n",
       "      <td>5.425000</td>\n",
       "      <td>5.650000</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>5.050000</td>\n",
       "      <td>5.12500</td>\n",
       "      <td>5.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>4.80000</td>\n",
       "      <td>4.666667</td>\n",
       "      <td>4.533333</td>\n",
       "      <td>4.866667</td>\n",
       "      <td>4.900</td>\n",
       "      <td>4.7000</td>\n",
       "      <td>4.733333</td>\n",
       "      <td>4.833333</td>\n",
       "      <td>4.766667</td>\n",
       "      <td>4.566667</td>\n",
       "      <td>4.60000</td>\n",
       "      <td>4.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>4.27550</td>\n",
       "      <td>3.976167</td>\n",
       "      <td>3.676833</td>\n",
       "      <td>4.425167</td>\n",
       "      <td>4.500</td>\n",
       "      <td>4.0510</td>\n",
       "      <td>4.125833</td>\n",
       "      <td>4.350333</td>\n",
       "      <td>4.200667</td>\n",
       "      <td>3.751667</td>\n",
       "      <td>3.82650</td>\n",
       "      <td>3.901333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>3.55850</td>\n",
       "      <td>3.500500</td>\n",
       "      <td>3.442500</td>\n",
       "      <td>3.587500</td>\n",
       "      <td>3.602</td>\n",
       "      <td>3.5150</td>\n",
       "      <td>3.529500</td>\n",
       "      <td>3.573000</td>\n",
       "      <td>3.544000</td>\n",
       "      <td>3.457000</td>\n",
       "      <td>3.47150</td>\n",
       "      <td>3.486000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>3.76150</td>\n",
       "      <td>4.206167</td>\n",
       "      <td>4.650833</td>\n",
       "      <td>3.539167</td>\n",
       "      <td>3.428</td>\n",
       "      <td>4.0950</td>\n",
       "      <td>3.983833</td>\n",
       "      <td>3.650333</td>\n",
       "      <td>3.872667</td>\n",
       "      <td>4.539667</td>\n",
       "      <td>4.42850</td>\n",
       "      <td>4.317333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>5.11525</td>\n",
       "      <td>5.586250</td>\n",
       "      <td>6.057250</td>\n",
       "      <td>4.879750</td>\n",
       "      <td>4.762</td>\n",
       "      <td>5.4685</td>\n",
       "      <td>5.350750</td>\n",
       "      <td>4.997500</td>\n",
       "      <td>5.233000</td>\n",
       "      <td>5.939500</td>\n",
       "      <td>5.82175</td>\n",
       "      <td>5.704000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>6.02050</td>\n",
       "      <td>5.814500</td>\n",
       "      <td>5.608500</td>\n",
       "      <td>6.123500</td>\n",
       "      <td>6.175</td>\n",
       "      <td>5.8660</td>\n",
       "      <td>5.917500</td>\n",
       "      <td>6.072000</td>\n",
       "      <td>5.969000</td>\n",
       "      <td>5.660000</td>\n",
       "      <td>5.71150</td>\n",
       "      <td>5.763000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>5.38675</td>\n",
       "      <td>5.159750</td>\n",
       "      <td>4.932750</td>\n",
       "      <td>5.500250</td>\n",
       "      <td>5.557</td>\n",
       "      <td>5.2165</td>\n",
       "      <td>5.273250</td>\n",
       "      <td>5.443500</td>\n",
       "      <td>5.330000</td>\n",
       "      <td>4.989500</td>\n",
       "      <td>5.04625</td>\n",
       "      <td>5.103000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.876</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Month       Apr        Aug        Dec        Feb     Jan      Jul        Jun  \\\n",
       "year                                                                           \n",
       "1980   11.67300  12.109000  12.545000  11.455000  11.346  12.0000  11.891000   \n",
       "1981   11.42450   9.785167   8.145833  12.244167  12.654  10.1950  10.604833   \n",
       "1982    8.94150  10.548833  12.156167   8.137833   7.736  10.1470   9.745167   \n",
       "1983   11.04775   9.034083   7.020417  12.054583  12.558   9.5375  10.040917   \n",
       "1984    6.45050   6.361833   6.273167   6.494833   6.517   6.3840   6.406167   \n",
       "1985    6.91050   7.789833   8.669167   6.470833   6.251   7.5700   7.350167   \n",
       "1986    8.93150   8.988167   9.044833   8.903167   8.889   8.9740   8.959833   \n",
       "1987    8.59775   7.982750   7.367750   8.905250   9.059   8.1365   8.290250   \n",
       "1988    6.55275   5.671083   4.789417   6.993583   7.214   5.8915   6.111917   \n",
       "1989    6.22600   8.435333  10.644667   5.121333   4.569   7.8830   7.330667   \n",
       "1990   11.76850  12.530500  13.292500  11.387500  11.197  12.3400  12.149500   \n",
       "1991   12.57800  11.371333  10.164667  13.181333  13.483  11.6730  11.974667   \n",
       "1992    9.21700   8.355667   7.494333   9.647667   9.863   8.5710   8.786333   \n",
       "1993    8.02800   9.026667  10.025333   7.528667   7.279   8.7770   8.527333   \n",
       "1994   10.19675  10.092417   9.988083  10.248917  10.275  10.1185  10.144583   \n",
       "1995    9.82950   9.652833   9.476167   9.917833   9.962   9.6970   9.741167   \n",
       "1996    8.78450   7.921167   7.057833   9.216167   9.432   8.1370   8.352833   \n",
       "1997    8.41325  10.508250  12.603250   7.365750   6.842   9.9845   9.460750   \n",
       "1998   11.26975   8.793417   6.317083  12.507917  13.127   9.4125  10.031583   \n",
       "1999    5.23125   4.608917   3.986583   5.542417   5.698   4.7645   4.920083   \n",
       "2000    3.95100   4.111000   4.271000   3.871000   3.831   4.0710   4.031000   \n",
       "2001    4.22850   4.118500   4.008500   4.283500   4.311   4.1460   4.173500   \n",
       "2002    3.95175   3.912750   3.873750   3.971250   3.981   3.9225   3.932250   \n",
       "2003    3.85400   3.840667   3.827333   3.860667   3.864   3.8440   3.847333   \n",
       "2004    3.96900   4.162333   4.355667   3.872333   3.824   4.1140   4.065667   \n",
       "2005    4.97725   5.741583   6.505917   4.595083   4.404   5.5505   5.359417   \n",
       "2006    6.57375   6.409417   6.245083   6.655917   6.697   6.4505   6.491583   \n",
       "2007    6.92525   7.886917   8.848583   6.444417   6.204   7.6465   7.406083   \n",
       "2008    9.89525  10.970250  12.045250   9.357750   9.089  10.7015  10.432750   \n",
       "2009   11.86750  11.272167  10.676833  12.165167  12.314  11.4210  11.569833   \n",
       "2010   10.27100   9.928333   9.585667  10.442333  10.528  10.0140  10.099667   \n",
       "2011    9.62500   9.791667   9.958333   9.541667   9.500   9.7500   9.708333   \n",
       "2012    9.85000   9.650000   9.450000   9.950000  10.000   9.7000   9.750000   \n",
       "2013    8.50000   7.300000   6.100000   9.100000   9.400   7.6000   7.900000   \n",
       "2014    5.57500   5.275000   4.975000   5.725000   5.800   5.3500   5.425000   \n",
       "2015    4.80000   4.666667   4.533333   4.866667   4.900   4.7000   4.733333   \n",
       "2016    4.27550   3.976167   3.676833   4.425167   4.500   4.0510   4.125833   \n",
       "2017    3.55850   3.500500   3.442500   3.587500   3.602   3.5150   3.529500   \n",
       "2018    3.76150   4.206167   4.650833   3.539167   3.428   4.0950   3.983833   \n",
       "2019    5.11525   5.586250   6.057250   4.879750   4.762   5.4685   5.350750   \n",
       "2020    6.02050   5.814500   5.608500   6.123500   6.175   5.8660   5.917500   \n",
       "2021    5.38675   5.159750   4.932750   5.500250   5.557   5.2165   5.273250   \n",
       "2022    0.00000   0.000000   0.000000   0.000000   4.876   0.0000   0.000000   \n",
       "\n",
       "Month        Mar        May        Nov       Oct        Sep  \n",
       "year                                                         \n",
       "1980   11.564000  11.782000  12.436000  12.32700  12.218000  \n",
       "1981   11.834333  11.014667   8.555667   8.96550   9.375333  \n",
       "1982    8.539667   9.343333  11.754333  11.35250  10.950667  \n",
       "1983   11.551167  10.544333   7.523833   8.02725   8.530667  \n",
       "1984    6.472667   6.428333   6.295333   6.31750   6.339667  \n",
       "1985    6.690667   7.130333   8.449333   8.22950   8.009667  \n",
       "1986    8.917333   8.945667   9.030667   9.01650   9.002333  \n",
       "1987    8.751500   8.444000   7.521500   7.67525   7.829000  \n",
       "1988    6.773167   6.332333   5.009833   5.23025   5.450667  \n",
       "1989    5.673667   6.778333  10.092333   9.54000   8.987667  \n",
       "1990   11.578000  11.959000  13.102000  12.91150  12.721000  \n",
       "1991   12.879667  12.276333  10.466333  10.76800  11.069667  \n",
       "1992    9.432333   9.001667   7.709667   7.92500   8.140333  \n",
       "1993    7.778333   8.277667   9.775667   9.52600   9.276333  \n",
       "1994   10.222833  10.170667  10.014167  10.04025  10.066333  \n",
       "1995    9.873667   9.785333   9.520333   9.56450   9.608667  \n",
       "1996    9.000333   8.568667   7.273667   7.48950   7.705333  \n",
       "1997    7.889500   8.937000  12.079500  11.55575  11.032000  \n",
       "1998   11.888833  10.650667   6.936167   7.55525   8.174333  \n",
       "1999    5.386833   5.075667   4.142167   4.29775   4.453333  \n",
       "2000    3.911000   3.991000   4.231000   4.19100   4.151000  \n",
       "2001    4.256000   4.201000   4.036000   4.06350   4.091000  \n",
       "2002    3.961500   3.942000   3.883500   3.89325   3.903000  \n",
       "2003    3.857333   3.850667   3.830667   3.83400   3.837333  \n",
       "2004    3.920667   4.017333   4.307333   4.25900   4.210667  \n",
       "2005    4.786167   5.168333   6.314833   6.12375   5.932667  \n",
       "2006    6.614833   6.532667   6.286167   6.32725   6.368333  \n",
       "2007    6.684833   7.165667   8.608167   8.36775   8.127333  \n",
       "2008    9.626500  10.164000  11.776500  11.50775  11.239000  \n",
       "2009   12.016333  11.718667  10.825667  10.97450  11.123333  \n",
       "2010   10.356667  10.185333   9.671333   9.75700   9.842667  \n",
       "2011    9.583333   9.666667   9.916667   9.87500   9.833333  \n",
       "2012    9.900000   9.800000   9.500000   9.55000   9.600000  \n",
       "2013    8.800000   8.200000   6.400000   6.70000   7.000000  \n",
       "2014    5.650000   5.500000   5.050000   5.12500   5.200000  \n",
       "2015    4.833333   4.766667   4.566667   4.60000   4.633333  \n",
       "2016    4.350333   4.200667   3.751667   3.82650   3.901333  \n",
       "2017    3.573000   3.544000   3.457000   3.47150   3.486000  \n",
       "2018    3.650333   3.872667   4.539667   4.42850   4.317333  \n",
       "2019    4.997500   5.233000   5.939500   5.82175   5.704000  \n",
       "2020    6.072000   5.969000   5.660000   5.71150   5.763000  \n",
       "2021    5.443500   5.330000   4.989500   5.04625   5.103000  \n",
       "2022    0.000000   0.000000   0.000000   0.00000   0.000000  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inflation_pivot =pd.pivot_table(data= india_month_interpolated,values='Inflation_rate',index='year',columns='Month').fillna(0)\n",
    "inflation_pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "bb26c1c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,15))\n",
    "sns.heatmap(inflation_pivot,annot=True,fmt='g')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "471751c2",
   "metadata": {},
   "source": [
    "### Data Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a3277de",
   "metadata": {},
   "source": [
    "### Dividing the Data into Train and Test Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "be550d5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(505, 19)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india_month_interpolated.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "8b6e2ca6",
   "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>Inflation_rate</th>\n",
       "      <th>t</th>\n",
       "      <th>t_squared</th>\n",
       "      <th>log_inflation</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>year</th>\n",
       "      <th>Apr</th>\n",
       "      <th>Aug</th>\n",
       "      <th>Dec</th>\n",
       "      <th>Feb</th>\n",
       "      <th>Jan</th>\n",
       "      <th>Jul</th>\n",
       "      <th>Jun</th>\n",
       "      <th>Mar</th>\n",
       "      <th>May</th>\n",
       "      <th>Nov</th>\n",
       "      <th>Oct</th>\n",
       "      <th>Sep</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-31</th>\n",
       "      <td>11.3460</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.428865</td>\n",
       "      <td>1980-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>1980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-02-29</th>\n",
       "      <td>11.4550</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2.438426</td>\n",
       "      <td>1980-02-29</td>\n",
       "      <td>Feb</td>\n",
       "      <td>1980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-03-31</th>\n",
       "      <td>11.5640</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2.447897</td>\n",
       "      <td>1980-03-31</td>\n",
       "      <td>Mar</td>\n",
       "      <td>1980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-04-30</th>\n",
       "      <td>11.6730</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>2.457278</td>\n",
       "      <td>1980-04-30</td>\n",
       "      <td>Apr</td>\n",
       "      <td>1980</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980-05-31</th>\n",
       "      <td>11.7820</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>2.466573</td>\n",
       "      <td>1980-05-31</td>\n",
       "      <td>May</td>\n",
       "      <td>1980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "      <td>...</td>\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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-31</th>\n",
       "      <td>3.5150</td>\n",
       "      <td>450</td>\n",
       "      <td>202500</td>\n",
       "      <td>1.257040</td>\n",
       "      <td>2017-07-31</td>\n",
       "      <td>Jul</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-31</th>\n",
       "      <td>3.5005</td>\n",
       "      <td>451</td>\n",
       "      <td>203401</td>\n",
       "      <td>1.252906</td>\n",
       "      <td>2017-08-31</td>\n",
       "      <td>Aug</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-30</th>\n",
       "      <td>3.4860</td>\n",
       "      <td>452</td>\n",
       "      <td>204304</td>\n",
       "      <td>1.248755</td>\n",
       "      <td>2017-09-30</td>\n",
       "      <td>Sep</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-31</th>\n",
       "      <td>3.4715</td>\n",
       "      <td>453</td>\n",
       "      <td>205209</td>\n",
       "      <td>1.244587</td>\n",
       "      <td>2017-10-31</td>\n",
       "      <td>Oct</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-30</th>\n",
       "      <td>3.4570</td>\n",
       "      <td>454</td>\n",
       "      <td>206116</td>\n",
       "      <td>1.240401</td>\n",
       "      <td>2017-11-30</td>\n",
       "      <td>Nov</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>455 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate    t  t_squared  log_inflation       Year Month  \\\n",
       "Year                                                                         \n",
       "1980-01-31         11.3460    0          0       2.428865 1980-01-31   Jan   \n",
       "1980-02-29         11.4550    1          1       2.438426 1980-02-29   Feb   \n",
       "1980-03-31         11.5640    2          4       2.447897 1980-03-31   Mar   \n",
       "1980-04-30         11.6730    3          9       2.457278 1980-04-30   Apr   \n",
       "1980-05-31         11.7820    4         16       2.466573 1980-05-31   May   \n",
       "...                    ...  ...        ...            ...        ...   ...   \n",
       "2017-07-31          3.5150  450     202500       1.257040 2017-07-31   Jul   \n",
       "2017-08-31          3.5005  451     203401       1.252906 2017-08-31   Aug   \n",
       "2017-09-30          3.4860  452     204304       1.248755 2017-09-30   Sep   \n",
       "2017-10-31          3.4715  453     205209       1.244587 2017-10-31   Oct   \n",
       "2017-11-30          3.4570  454     206116       1.240401 2017-11-30   Nov   \n",
       "\n",
       "            year  Apr  Aug  Dec  Feb  Jan  Jul  Jun  Mar  May  Nov  Oct  Sep  \n",
       "Year                                                                          \n",
       "1980-01-31  1980    0    0    0    0    1    0    0    0    0    0    0    0  \n",
       "1980-02-29  1980    0    0    0    1    0    0    0    0    0    0    0    0  \n",
       "1980-03-31  1980    0    0    0    0    0    0    0    1    0    0    0    0  \n",
       "1980-04-30  1980    1    0    0    0    0    0    0    0    0    0    0    0  \n",
       "1980-05-31  1980    0    0    0    0    0    0    0    0    1    0    0    0  \n",
       "...          ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  \n",
       "2017-07-31  2017    0    0    0    0    0    1    0    0    0    0    0    0  \n",
       "2017-08-31  2017    0    1    0    0    0    0    0    0    0    0    0    0  \n",
       "2017-09-30  2017    0    0    0    0    0    0    0    0    0    0    0    1  \n",
       "2017-10-31  2017    0    0    0    0    0    0    0    0    0    0    1    0  \n",
       "2017-11-30  2017    0    0    0    0    0    0    0    0    0    1    0    0  \n",
       "\n",
       "[455 rows x 19 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data = india_month_interpolated.head(455)\n",
    "train_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "d4f1f31b",
   "metadata": {},
   "outputs": [
    {
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       "      <td>204304</td>\n",
       "      <td>1.248755</td>\n",
       "      <td>2017-09-30</td>\n",
       "      <td>Sep</td>\n",
       "      <td>2017</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>453</td>\n",
       "      <td>205209</td>\n",
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      "text/plain": [
       "            Inflation_rate    t  t_squared  log_inflation       Year Month  \\\n",
       "Year                                                                         \n",
       "2017-07-31          3.5150  450     202500       1.257040 2017-07-31   Jul   \n",
       "2017-08-31          3.5005  451     203401       1.252906 2017-08-31   Aug   \n",
       "2017-09-30          3.4860  452     204304       1.248755 2017-09-30   Sep   \n",
       "2017-10-31          3.4715  453     205209       1.244587 2017-10-31   Oct   \n",
       "2017-11-30          3.4570  454     206116       1.240401 2017-11-30   Nov   \n",
       "\n",
       "            year  Apr  Aug  Dec  Feb  Jan  Jul  Jun  Mar  May  Nov  Oct  Sep  \n",
       "Year                                                                          \n",
       "2017-07-31  2017    0    0    0    0    0    1    0    0    0    0    0    0  \n",
       "2017-08-31  2017    0    1    0    0    0    0    0    0    0    0    0    0  \n",
       "2017-09-30  2017    0    0    0    0    0    0    0    0    0    0    0    1  \n",
       "2017-10-31  2017    0    0    0    0    0    0    0    0    0    0    1    0  \n",
       "2017-11-30  2017    0    0    0    0    0    0    0    0    0    1    0    0  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "d557e138",
   "metadata": {},
   "outputs": [
    {
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       "      <th>2018-01-31</th>\n",
       "      <td>3.428000</td>\n",
       "      <td>456</td>\n",
       "      <td>207936</td>\n",
       "      <td>1.231977</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>2018</td>\n",
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       "      <th>2018-02-28</th>\n",
       "      <td>3.539167</td>\n",
       "      <td>457</td>\n",
       "      <td>208849</td>\n",
       "      <td>1.263891</td>\n",
       "      <td>2018-02-28</td>\n",
       "      <td>Feb</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2018-03-31</th>\n",
       "      <td>3.650333</td>\n",
       "      <td>458</td>\n",
       "      <td>209764</td>\n",
       "      <td>1.294818</td>\n",
       "      <td>2018-03-31</td>\n",
       "      <td>Mar</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2018-04-30</th>\n",
       "      <td>3.761500</td>\n",
       "      <td>459</td>\n",
       "      <td>210681</td>\n",
       "      <td>1.324818</td>\n",
       "      <td>2018-04-30</td>\n",
       "      <td>Apr</td>\n",
       "      <td>2018</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2018-05-31</th>\n",
       "      <td>3.872667</td>\n",
       "      <td>460</td>\n",
       "      <td>211600</td>\n",
       "      <td>1.353943</td>\n",
       "      <td>2018-05-31</td>\n",
       "      <td>May</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-30</th>\n",
       "      <td>3.983833</td>\n",
       "      <td>461</td>\n",
       "      <td>212521</td>\n",
       "      <td>1.382245</td>\n",
       "      <td>2018-06-30</td>\n",
       "      <td>Jun</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-31</th>\n",
       "      <td>4.095000</td>\n",
       "      <td>462</td>\n",
       "      <td>213444</td>\n",
       "      <td>1.409767</td>\n",
       "      <td>2018-07-31</td>\n",
       "      <td>Jul</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31</th>\n",
       "      <td>4.206167</td>\n",
       "      <td>463</td>\n",
       "      <td>214369</td>\n",
       "      <td>1.436552</td>\n",
       "      <td>2018-08-31</td>\n",
       "      <td>Aug</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-09-30</th>\n",
       "      <td>4.317333</td>\n",
       "      <td>464</td>\n",
       "      <td>215296</td>\n",
       "      <td>1.462638</td>\n",
       "      <td>2018-09-30</td>\n",
       "      <td>Sep</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-31</th>\n",
       "      <td>4.428500</td>\n",
       "      <td>465</td>\n",
       "      <td>216225</td>\n",
       "      <td>1.488061</td>\n",
       "      <td>2018-10-31</td>\n",
       "      <td>Oct</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-11-30</th>\n",
       "      <td>4.539667</td>\n",
       "      <td>466</td>\n",
       "      <td>217156</td>\n",
       "      <td>1.512854</td>\n",
       "      <td>2018-11-30</td>\n",
       "      <td>Nov</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>4.650833</td>\n",
       "      <td>467</td>\n",
       "      <td>218089</td>\n",
       "      <td>1.537046</td>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-31</th>\n",
       "      <td>4.762000</td>\n",
       "      <td>468</td>\n",
       "      <td>219024</td>\n",
       "      <td>1.560668</td>\n",
       "      <td>2019-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-28</th>\n",
       "      <td>4.879750</td>\n",
       "      <td>469</td>\n",
       "      <td>219961</td>\n",
       "      <td>1.585094</td>\n",
       "      <td>2019-02-28</td>\n",
       "      <td>Feb</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-31</th>\n",
       "      <td>4.997500</td>\n",
       "      <td>470</td>\n",
       "      <td>220900</td>\n",
       "      <td>1.608938</td>\n",
       "      <td>2019-03-31</td>\n",
       "      <td>Mar</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-30</th>\n",
       "      <td>5.115250</td>\n",
       "      <td>471</td>\n",
       "      <td>221841</td>\n",
       "      <td>1.632226</td>\n",
       "      <td>2019-04-30</td>\n",
       "      <td>Apr</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-31</th>\n",
       "      <td>5.233000</td>\n",
       "      <td>472</td>\n",
       "      <td>222784</td>\n",
       "      <td>1.654985</td>\n",
       "      <td>2019-05-31</td>\n",
       "      <td>May</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>5.350750</td>\n",
       "      <td>473</td>\n",
       "      <td>223729</td>\n",
       "      <td>1.677237</td>\n",
       "      <td>2019-06-30</td>\n",
       "      <td>Jun</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-31</th>\n",
       "      <td>5.468500</td>\n",
       "      <td>474</td>\n",
       "      <td>224676</td>\n",
       "      <td>1.699004</td>\n",
       "      <td>2019-07-31</td>\n",
       "      <td>Jul</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-31</th>\n",
       "      <td>5.586250</td>\n",
       "      <td>475</td>\n",
       "      <td>225625</td>\n",
       "      <td>1.720308</td>\n",
       "      <td>2019-08-31</td>\n",
       "      <td>Aug</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-30</th>\n",
       "      <td>5.704000</td>\n",
       "      <td>476</td>\n",
       "      <td>226576</td>\n",
       "      <td>1.741168</td>\n",
       "      <td>2019-09-30</td>\n",
       "      <td>Sep</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-31</th>\n",
       "      <td>5.821750</td>\n",
       "      <td>477</td>\n",
       "      <td>227529</td>\n",
       "      <td>1.761601</td>\n",
       "      <td>2019-10-31</td>\n",
       "      <td>Oct</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-30</th>\n",
       "      <td>5.939500</td>\n",
       "      <td>478</td>\n",
       "      <td>228484</td>\n",
       "      <td>1.781625</td>\n",
       "      <td>2019-11-30</td>\n",
       "      <td>Nov</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>6.057250</td>\n",
       "      <td>479</td>\n",
       "      <td>229441</td>\n",
       "      <td>1.801256</td>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-31</th>\n",
       "      <td>6.175000</td>\n",
       "      <td>480</td>\n",
       "      <td>230400</td>\n",
       "      <td>1.820509</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-29</th>\n",
       "      <td>6.123500</td>\n",
       "      <td>481</td>\n",
       "      <td>231361</td>\n",
       "      <td>1.812134</td>\n",
       "      <td>2020-02-29</td>\n",
       "      <td>Feb</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>6.072000</td>\n",
       "      <td>482</td>\n",
       "      <td>232324</td>\n",
       "      <td>1.803688</td>\n",
       "      <td>2020-03-31</td>\n",
       "      <td>Mar</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-30</th>\n",
       "      <td>6.020500</td>\n",
       "      <td>483</td>\n",
       "      <td>233289</td>\n",
       "      <td>1.795170</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>Apr</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-31</th>\n",
       "      <td>5.969000</td>\n",
       "      <td>484</td>\n",
       "      <td>234256</td>\n",
       "      <td>1.786579</td>\n",
       "      <td>2020-05-31</td>\n",
       "      <td>May</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>5.917500</td>\n",
       "      <td>485</td>\n",
       "      <td>235225</td>\n",
       "      <td>1.777914</td>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>Jun</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-31</th>\n",
       "      <td>5.866000</td>\n",
       "      <td>486</td>\n",
       "      <td>236196</td>\n",
       "      <td>1.769173</td>\n",
       "      <td>2020-07-31</td>\n",
       "      <td>Jul</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-31</th>\n",
       "      <td>5.814500</td>\n",
       "      <td>487</td>\n",
       "      <td>237169</td>\n",
       "      <td>1.760355</td>\n",
       "      <td>2020-08-31</td>\n",
       "      <td>Aug</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-30</th>\n",
       "      <td>5.763000</td>\n",
       "      <td>488</td>\n",
       "      <td>238144</td>\n",
       "      <td>1.751458</td>\n",
       "      <td>2020-09-30</td>\n",
       "      <td>Sep</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-31</th>\n",
       "      <td>5.711500</td>\n",
       "      <td>489</td>\n",
       "      <td>239121</td>\n",
       "      <td>1.742482</td>\n",
       "      <td>2020-10-31</td>\n",
       "      <td>Oct</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-30</th>\n",
       "      <td>5.660000</td>\n",
       "      <td>490</td>\n",
       "      <td>240100</td>\n",
       "      <td>1.733424</td>\n",
       "      <td>2020-11-30</td>\n",
       "      <td>Nov</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>5.608500</td>\n",
       "      <td>491</td>\n",
       "      <td>241081</td>\n",
       "      <td>1.724283</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-31</th>\n",
       "      <td>5.557000</td>\n",
       "      <td>492</td>\n",
       "      <td>242064</td>\n",
       "      <td>1.715058</td>\n",
       "      <td>2021-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-28</th>\n",
       "      <td>5.500250</td>\n",
       "      <td>493</td>\n",
       "      <td>243049</td>\n",
       "      <td>1.704794</td>\n",
       "      <td>2021-02-28</td>\n",
       "      <td>Feb</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-31</th>\n",
       "      <td>5.443500</td>\n",
       "      <td>494</td>\n",
       "      <td>244036</td>\n",
       "      <td>1.694422</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>Mar</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-30</th>\n",
       "      <td>5.386750</td>\n",
       "      <td>495</td>\n",
       "      <td>245025</td>\n",
       "      <td>1.683942</td>\n",
       "      <td>2021-04-30</td>\n",
       "      <td>Apr</td>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-31</th>\n",
       "      <td>5.330000</td>\n",
       "      <td>496</td>\n",
       "      <td>246016</td>\n",
       "      <td>1.673351</td>\n",
       "      <td>2021-05-31</td>\n",
       "      <td>May</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-30</th>\n",
       "      <td>5.273250</td>\n",
       "      <td>497</td>\n",
       "      <td>247009</td>\n",
       "      <td>1.662647</td>\n",
       "      <td>2021-06-30</td>\n",
       "      <td>Jun</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-31</th>\n",
       "      <td>5.216500</td>\n",
       "      <td>498</td>\n",
       "      <td>248004</td>\n",
       "      <td>1.651827</td>\n",
       "      <td>2021-07-31</td>\n",
       "      <td>Jul</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31</th>\n",
       "      <td>5.159750</td>\n",
       "      <td>499</td>\n",
       "      <td>249001</td>\n",
       "      <td>1.640888</td>\n",
       "      <td>2021-08-31</td>\n",
       "      <td>Aug</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-30</th>\n",
       "      <td>5.103000</td>\n",
       "      <td>500</td>\n",
       "      <td>250000</td>\n",
       "      <td>1.629829</td>\n",
       "      <td>2021-09-30</td>\n",
       "      <td>Sep</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-31</th>\n",
       "      <td>5.046250</td>\n",
       "      <td>501</td>\n",
       "      <td>251001</td>\n",
       "      <td>1.618645</td>\n",
       "      <td>2021-10-31</td>\n",
       "      <td>Oct</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-30</th>\n",
       "      <td>4.989500</td>\n",
       "      <td>502</td>\n",
       "      <td>252004</td>\n",
       "      <td>1.607336</td>\n",
       "      <td>2021-11-30</td>\n",
       "      <td>Nov</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>4.932750</td>\n",
       "      <td>503</td>\n",
       "      <td>253009</td>\n",
       "      <td>1.595897</td>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-31</th>\n",
       "      <td>4.876000</td>\n",
       "      <td>504</td>\n",
       "      <td>254016</td>\n",
       "      <td>1.584325</td>\n",
       "      <td>2022-01-31</td>\n",
       "      <td>Jan</td>\n",
       "      <td>2022</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation_rate    t  t_squared  log_inflation       Year Month  \\\n",
       "Year                                                                         \n",
       "2017-12-31        3.442500  455     207025       1.236198 2017-12-31   Dec   \n",
       "2018-01-31        3.428000  456     207936       1.231977 2018-01-31   Jan   \n",
       "2018-02-28        3.539167  457     208849       1.263891 2018-02-28   Feb   \n",
       "2018-03-31        3.650333  458     209764       1.294818 2018-03-31   Mar   \n",
       "2018-04-30        3.761500  459     210681       1.324818 2018-04-30   Apr   \n",
       "2018-05-31        3.872667  460     211600       1.353943 2018-05-31   May   \n",
       "2018-06-30        3.983833  461     212521       1.382245 2018-06-30   Jun   \n",
       "2018-07-31        4.095000  462     213444       1.409767 2018-07-31   Jul   \n",
       "2018-08-31        4.206167  463     214369       1.436552 2018-08-31   Aug   \n",
       "2018-09-30        4.317333  464     215296       1.462638 2018-09-30   Sep   \n",
       "2018-10-31        4.428500  465     216225       1.488061 2018-10-31   Oct   \n",
       "2018-11-30        4.539667  466     217156       1.512854 2018-11-30   Nov   \n",
       "2018-12-31        4.650833  467     218089       1.537046 2018-12-31   Dec   \n",
       "2019-01-31        4.762000  468     219024       1.560668 2019-01-31   Jan   \n",
       "2019-02-28        4.879750  469     219961       1.585094 2019-02-28   Feb   \n",
       "2019-03-31        4.997500  470     220900       1.608938 2019-03-31   Mar   \n",
       "2019-04-30        5.115250  471     221841       1.632226 2019-04-30   Apr   \n",
       "2019-05-31        5.233000  472     222784       1.654985 2019-05-31   May   \n",
       "2019-06-30        5.350750  473     223729       1.677237 2019-06-30   Jun   \n",
       "2019-07-31        5.468500  474     224676       1.699004 2019-07-31   Jul   \n",
       "2019-08-31        5.586250  475     225625       1.720308 2019-08-31   Aug   \n",
       "2019-09-30        5.704000  476     226576       1.741168 2019-09-30   Sep   \n",
       "2019-10-31        5.821750  477     227529       1.761601 2019-10-31   Oct   \n",
       "2019-11-30        5.939500  478     228484       1.781625 2019-11-30   Nov   \n",
       "2019-12-31        6.057250  479     229441       1.801256 2019-12-31   Dec   \n",
       "2020-01-31        6.175000  480     230400       1.820509 2020-01-31   Jan   \n",
       "2020-02-29        6.123500  481     231361       1.812134 2020-02-29   Feb   \n",
       "2020-03-31        6.072000  482     232324       1.803688 2020-03-31   Mar   \n",
       "2020-04-30        6.020500  483     233289       1.795170 2020-04-30   Apr   \n",
       "2020-05-31        5.969000  484     234256       1.786579 2020-05-31   May   \n",
       "2020-06-30        5.917500  485     235225       1.777914 2020-06-30   Jun   \n",
       "2020-07-31        5.866000  486     236196       1.769173 2020-07-31   Jul   \n",
       "2020-08-31        5.814500  487     237169       1.760355 2020-08-31   Aug   \n",
       "2020-09-30        5.763000  488     238144       1.751458 2020-09-30   Sep   \n",
       "2020-10-31        5.711500  489     239121       1.742482 2020-10-31   Oct   \n",
       "2020-11-30        5.660000  490     240100       1.733424 2020-11-30   Nov   \n",
       "2020-12-31        5.608500  491     241081       1.724283 2020-12-31   Dec   \n",
       "2021-01-31        5.557000  492     242064       1.715058 2021-01-31   Jan   \n",
       "2021-02-28        5.500250  493     243049       1.704794 2021-02-28   Feb   \n",
       "2021-03-31        5.443500  494     244036       1.694422 2021-03-31   Mar   \n",
       "2021-04-30        5.386750  495     245025       1.683942 2021-04-30   Apr   \n",
       "2021-05-31        5.330000  496     246016       1.673351 2021-05-31   May   \n",
       "2021-06-30        5.273250  497     247009       1.662647 2021-06-30   Jun   \n",
       "2021-07-31        5.216500  498     248004       1.651827 2021-07-31   Jul   \n",
       "2021-08-31        5.159750  499     249001       1.640888 2021-08-31   Aug   \n",
       "2021-09-30        5.103000  500     250000       1.629829 2021-09-30   Sep   \n",
       "2021-10-31        5.046250  501     251001       1.618645 2021-10-31   Oct   \n",
       "2021-11-30        4.989500  502     252004       1.607336 2021-11-30   Nov   \n",
       "2021-12-31        4.932750  503     253009       1.595897 2021-12-31   Dec   \n",
       "2022-01-31        4.876000  504     254016       1.584325 2022-01-31   Jan   \n",
       "\n",
       "            year  Apr  Aug  Dec  Feb  Jan  Jul  Jun  Mar  May  Nov  Oct  Sep  \n",
       "Year                                                                          \n",
       "2017-12-31  2017    0    0    1    0    0    0    0    0    0    0    0    0  \n",
       "2018-01-31  2018    0    0    0    0    1    0    0    0    0    0    0    0  \n",
       "2018-02-28  2018    0    0    0    1    0    0    0    0    0    0    0    0  \n",
       "2018-03-31  2018    0    0    0    0    0    0    0    1    0    0    0    0  \n",
       "2018-04-30  2018    1    0    0    0    0    0    0    0    0    0    0    0  \n",
       "2018-05-31  2018    0    0    0    0    0    0    0    0    1    0    0    0  \n",
       "2018-06-30  2018    0    0    0    0    0    0    1    0    0    0    0    0  \n",
       "2018-07-31  2018    0    0    0    0    0    1    0    0    0    0    0    0  \n",
       "2018-08-31  2018    0    1    0    0    0    0    0    0    0    0    0    0  \n",
       "2018-09-30  2018    0    0    0    0    0    0    0    0    0    0    0    1  \n",
       "2018-10-31  2018    0    0    0    0    0    0    0    0    0    0    1    0  \n",
       "2018-11-30  2018    0    0    0    0    0    0    0    0    0    1    0    0  \n",
       "2018-12-31  2018    0    0    1    0    0    0    0    0    0    0    0    0  \n",
       "2019-01-31  2019    0    0    0    0    1    0    0    0    0    0    0    0  \n",
       "2019-02-28  2019    0    0    0    1    0    0    0    0    0    0    0    0  \n",
       "2019-03-31  2019    0    0    0    0    0    0    0    1    0    0    0    0  \n",
       "2019-04-30  2019    1    0    0    0    0    0    0    0    0    0    0    0  \n",
       "2019-05-31  2019    0    0    0    0    0    0    0    0    1    0    0    0  \n",
       "2019-06-30  2019    0    0    0    0    0    0    1    0    0    0    0    0  \n",
       "2019-07-31  2019    0    0    0    0    0    1    0    0    0    0    0    0  \n",
       "2019-08-31  2019    0    1    0    0    0    0    0    0    0    0    0    0  \n",
       "2019-09-30  2019    0    0    0    0    0    0    0    0    0    0    0    1  \n",
       "2019-10-31  2019    0    0    0    0    0    0    0    0    0    0    1    0  \n",
       "2019-11-30  2019    0    0    0    0    0    0    0    0    0    1    0    0  \n",
       "2019-12-31  2019    0    0    1    0    0    0    0    0    0    0    0    0  \n",
       "2020-01-31  2020    0    0    0    0    1    0    0    0    0    0    0    0  \n",
       "2020-02-29  2020    0    0    0    1    0    0    0    0    0    0    0    0  \n",
       "2020-03-31  2020    0    0    0    0    0    0    0    1    0    0    0    0  \n",
       "2020-04-30  2020    1    0    0    0    0    0    0    0    0    0    0    0  \n",
       "2020-05-31  2020    0    0    0    0    0    0    0    0    1    0    0    0  \n",
       "2020-06-30  2020    0    0    0    0    0    0    1    0    0    0    0    0  \n",
       "2020-07-31  2020    0    0    0    0    0    1    0    0    0    0    0    0  \n",
       "2020-08-31  2020    0    1    0    0    0    0    0    0    0    0    0    0  \n",
       "2020-09-30  2020    0    0    0    0    0    0    0    0    0    0    0    1  \n",
       "2020-10-31  2020    0    0    0    0    0    0    0    0    0    0    1    0  \n",
       "2020-11-30  2020    0    0    0    0    0    0    0    0    0    1    0    0  \n",
       "2020-12-31  2020    0    0    1    0    0    0    0    0    0    0    0    0  \n",
       "2021-01-31  2021    0    0    0    0    1    0    0    0    0    0    0    0  \n",
       "2021-02-28  2021    0    0    0    1    0    0    0    0    0    0    0    0  \n",
       "2021-03-31  2021    0    0    0    0    0    0    0    1    0    0    0    0  \n",
       "2021-04-30  2021    1    0    0    0    0    0    0    0    0    0    0    0  \n",
       "2021-05-31  2021    0    0    0    0    0    0    0    0    1    0    0    0  \n",
       "2021-06-30  2021    0    0    0    0    0    0    1    0    0    0    0    0  \n",
       "2021-07-31  2021    0    0    0    0    0    1    0    0    0    0    0    0  \n",
       "2021-08-31  2021    0    1    0    0    0    0    0    0    0    0    0    0  \n",
       "2021-09-30  2021    0    0    0    0    0    0    0    0    0    0    0    1  \n",
       "2021-10-31  2021    0    0    0    0    0    0    0    0    0    0    1    0  \n",
       "2021-11-30  2021    0    0    0    0    0    0    0    0    0    1    0    0  \n",
       "2021-12-31  2021    0    0    1    0    0    0    0    0    0    0    0    0  \n",
       "2022-01-31  2022    0    0    0    0    1    0    0    0    0    0    0    0  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data =india_month_interpolated.tail(50)\n",
    "test_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7c19ed4",
   "metadata": {},
   "source": [
    "### Model Building"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b099e599",
   "metadata": {},
   "source": [
    "#### Linear Regression Method "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "63283e45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0793343945330967"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Linear Model\n",
    "\n",
    "import numpy as np\n",
    "import statsmodels.formula.api as smf\n",
    "\n",
    "# Training Data\n",
    "linear_model = smf.ols('Inflation_rate~t',data = train_data).fit()\n",
    "\n",
    "# Testing Data\n",
    "linear_pred = pd.Series(linear_model.predict(test_data['t']))\n",
    "\n",
    "# Evaluation\n",
    "rmse_linear = np.sqrt(np.mean((np.array(test_data['Inflation_rate'])-np.array(linear_pred))**2))\n",
    "rmse_linear"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2855b73",
   "metadata": {},
   "source": [
    "#### Exponential Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "6d3a2db8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8796098375669068"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exponential Model \n",
    "\n",
    "import numpy as np\n",
    "import statsmodels.formula.api as smf\n",
    "\n",
    "# Training Data\n",
    "exp_model = smf.ols('log_inflation~t',data = train_data).fit()\n",
    "\n",
    "# Testing Data\n",
    "exp_pred = pd.Series(exp_model.predict(test_data['t']))\n",
    "\n",
    "# Evaluation\n",
    "rmse_Exp = np.sqrt(np.mean((np.array(test_data['Inflation_rate'])-np.array(np.exp(exp_pred)))**2))\n",
    "rmse_Exp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e02392f",
   "metadata": {},
   "source": [
    "#### Quadratic Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "8b517a53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.4342920344745687"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Quadratic \n",
    "\n",
    "Quad = smf.ols('Inflation_rate~t+t_squared',data=train_data).fit()\n",
    "pred_Quad = pd.Series(Quad.predict(test_data[[\"t\",\"t_squared\"]]))\n",
    "rmse_Quad = np.sqrt(np.mean((np.array(test_data['Inflation_rate'])-np.array(pred_Quad))**2))\n",
    "rmse_Quad"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b8ca8f9",
   "metadata": {},
   "source": [
    "#### Additive Seasonality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "349e16e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.8320034105822045"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Additive seasonality \n",
    "\n",
    "add_sea = smf.ols('Inflation_rate~Jan+Feb+Mar+Apr+May+Jun+Jul+Aug+Sep+Oct+Nov+Dec',data=train_data).fit()\n",
    "pred_add_sea = pd.Series(add_sea.predict(test_data[['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']]))\n",
    "rmse_add_sea = np.sqrt(np.mean((np.array(test_data['Inflation_rate'])-np.array(pred_add_sea))**2))\n",
    "rmse_add_sea"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ea9d6b4",
   "metadata": {},
   "source": [
    "#### Additive Seasonality Quadratic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "5b92b69f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.4391294500960938"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Additive Seasonality Quadratic \n",
    "\n",
    "add_sea_Quad = smf.ols('Inflation_rate~t+t_squared+Jan+Feb+Mar+Apr+May+Jun+Jul+Aug+Sep+Oct+Nov+Dec',data=train_data).fit()\n",
    "pred_add_sea_quad = pd.Series(add_sea_Quad.predict(test_data[['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','t','t_squared']]))\n",
    "rmse_add_sea_quad = np.sqrt(np.mean((np.array(test_data['Inflation_rate'])-np.array(pred_add_sea_quad))**2))\n",
    "rmse_add_sea_quad"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed6e1f10",
   "metadata": {},
   "source": [
    "#### Multiplicative Seasonality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b418f1ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.3236474505825337"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Multiplicative Seasonality\n",
    "\n",
    "Mul_sea = smf.ols('log_inflation~Jan+Feb+Mar+Apr+May+Jun+Jul+Aug+Sep+Oct+Nov+Dec',data = train_data).fit()\n",
    "pred_Mult_sea = pd.Series(Mul_sea.predict(test_data))\n",
    "rmse_Mult_sea = np.sqrt(np.mean((np.array(test_data['Inflation_rate'])-np.array(np.exp(pred_Mult_sea)))**2))\n",
    "rmse_Mult_sea"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a074e13e",
   "metadata": {},
   "source": [
    "#### Multiplicative Additive Seasonality  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "7ae527c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8807784477987486"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Multiplicative Additive Seasonality \n",
    "\n",
    "Mul_Add_sea = smf.ols('log_inflation~t+Jan+Feb+Mar+Apr+May+Jun+Jul+Aug+Sep+Oct+Nov+Dec',data = train_data).fit()\n",
    "pred_Mult_add_sea = pd.Series(Mul_Add_sea.predict(test_data))\n",
    "rmse_Mult_add_sea = np.sqrt(np.mean((np.array(test_data['Inflation_rate'])-np.array(np.exp(pred_Mult_add_sea)))**2))\n",
    "rmse_Mult_add_sea "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe2420dd",
   "metadata": {},
   "source": [
    "#### Compare the results "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "23ede6e8",
   "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>MODEL</th>\n",
       "      <th>RMSE_Values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>rmse_Exp</td>\n",
       "      <td>0.879610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rmse_Mult_add_sea</td>\n",
       "      <td>0.880778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>rmse_linear</td>\n",
       "      <td>1.079334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rmse_Quad</td>\n",
       "      <td>1.434292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>rmse_add_sea_quad</td>\n",
       "      <td>1.439129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>rmse_Mult_sea</td>\n",
       "      <td>2.323647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>rmse_add_sea</td>\n",
       "      <td>2.832003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               MODEL  RMSE_Values\n",
       "1           rmse_Exp     0.879610\n",
       "6  rmse_Mult_add_sea     0.880778\n",
       "0        rmse_linear     1.079334\n",
       "2          rmse_Quad     1.434292\n",
       "4  rmse_add_sea_quad     1.439129\n",
       "5      rmse_Mult_sea     2.323647\n",
       "3       rmse_add_sea     2.832003"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = {\"MODEL\":pd.Series([\"rmse_linear\",\"rmse_Exp\",\"rmse_Quad\",\"rmse_add_sea\",\"rmse_add_sea_quad\",\"rmse_Mult_sea\",\"rmse_Mult_add_sea\"]),\n",
    "        \"RMSE_Values\":pd.Series([rmse_linear,rmse_Exp,rmse_Quad,rmse_add_sea,rmse_add_sea_quad,rmse_Mult_sea,rmse_Mult_add_sea])}\n",
    "table_rmse=pd.DataFrame(data)\n",
    "table_rmse.sort_values(['RMSE_Values'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e7b85b7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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