assignment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importing the relevant libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from pmdarima import auto_arima\n",
    "from statsmodels.tsa.stattools import adfuller\n",
    "from statsmodels.tsa.arima.model import ARIMA\n",
    "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n",
    "from statsmodels.tools.eval_measures import rmse\n",
    "from statsmodels.stats.diagnostic import acorr_ljungbox\n",
    "import statsmodels.api as sm\n",
    "from scipy.stats import shapiro"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_excel('WorldBank_India_GDP_1960-2022.xlsx')\n",
    "t=data['Year']\n",
    "Y=data['GDP_Ind_Dollars']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting GDP against Years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(t,Y,\"r-o\")\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"India GDP(in USD)\")\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=True)\n",
    "plt.show('GDP_vs_Year.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As it is a time series, ARIMA(p,d,q) would suit well. We need to determine the value of p,d and q. Starting with d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P-value at d= 0: 1.0\n",
      "P-value at d= 1: 1.0\n",
      "P-value at d= 2: 0.451213635397457\n"
     ]
    }
   ],
   "source": [
    "print(\"P-value at d= 0:\",adfuller(Y)[1]) \n",
    "print(\"P-value at d= 1:\",adfuller(Y.diff().dropna())[1])\n",
    "print(\"P-value at d= 2:\",adfuller(Y.diff().diff().dropna())[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From above P values, we determine d=2.\n",
    "Using ACF and PACF to determine p and q for d=2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d2Y=Y.diff().diff().dropna()\n",
    "plot_pacf(d2Y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_acf(d2Y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the graphs, it is clear that p=0 and q=1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Confirming our findings with the auto_arima method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                               SARIMAX Results                                \n",
      "==============================================================================\n",
      "Dep. Variable:                      y   No. Observations:                   58\n",
      "Model:               SARIMAX(0, 2, 1)   Log Likelihood               -1402.042\n",
      "Date:                Sat, 11 Nov 2023   AIC                           2808.084\n",
      "Time:                        14:46:16   BIC                           2812.135\n",
      "Sample:                             0   HQIC                          2809.655\n",
      "                                 - 58                                         \n",
      "Covariance Type:                  opg                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "ma.L1         -0.2969      0.083     -3.591      0.000      -0.459      -0.135\n",
      "sigma2      3.315e+20   3.18e-23   1.04e+43      0.000    3.31e+20    3.31e+20\n",
      "===================================================================================\n",
      "Ljung-Box (L1) (Q):                   0.62   Jarque-Bera (JB):                 1.57\n",
      "Prob(Q):                              0.43   Prob(JB):                         0.46\n",
      "Heteroskedasticity (H):               4.08   Skew:                            -0.21\n",
      "Prob(H) (two-sided):                  0.00   Kurtosis:                         3.71\n",
      "===================================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
      "[2] Covariance matrix is singular or near-singular, with condition number 3.71e+58. Standard errors may be unstable.\n"
     ]
    }
   ],
   "source": [
    "stepwise_fit=auto_arima(Y[0:58],start_p=0,start_q=0,\n",
    "                        max_p=2,max_q=1,\n",
    "                        error_action='ignore',\n",
    "                        suppress_warnings=True,\n",
    "                        stepwise=True)\n",
    "\n",
    "print(stepwise_fit.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ARIMA(0,2,1) is to be used. Training the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                               SARIMAX Results                                \n",
      "==============================================================================\n",
      "Dep. Variable:        GDP_Ind_Dollars   No. Observations:                   58\n",
      "Model:                 ARIMA(0, 2, 1)   Log Likelihood               -1402.042\n",
      "Date:                Fri, 10 Nov 2023   AIC                           2808.084\n",
      "Time:                        18:00:31   BIC                           2812.135\n",
      "Sample:                             0   HQIC                          2809.655\n",
      "                                 - 58                                         \n",
      "Covariance Type:                  opg                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "ma.L1         -0.2969      0.083     -3.591      0.000      -0.459      -0.135\n",
      "sigma2      3.315e+20   3.18e-23   1.04e+43      0.000    3.31e+20    3.31e+20\n",
      "===================================================================================\n",
      "Ljung-Box (L1) (Q):                   0.62   Jarque-Bera (JB):                 1.57\n",
      "Prob(Q):                              0.43   Prob(JB):                         0.46\n",
      "Heteroskedasticity (H):               4.08   Skew:                            -0.21\n",
      "Prob(H) (two-sided):                  0.00   Kurtosis:                         3.71\n",
      "===================================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
      "[2] Covariance matrix is singular or near-singular, with condition number 3.71e+58. Standard errors may be unstable.\n"
     ]
    }
   ],
   "source": [
    "train_data=data[0:58] #Training on 1960-2017\n",
    "test_data=data[58:]  #Testing on 2018-2022\n",
    "\n",
    "model=ARIMA(train_data['GDP_Ind_Dollars'],order=(0,2,1))\n",
    "arima_model=model.fit()\n",
    "print(arima_model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Diagnostic Checking"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_acf(arima_model.resid)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sm.qqplot(arima_model.resid)\n",
    "# sm.qqline(ax,arima_model.resid)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ShapiroResult(statistic=0.8213626146316528, pvalue=6.764381055290869e-07)"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shapiro(arima_model.resid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing the predictions on the entire dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions=arima_model.predict(0,62).rename('Predictions')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "58    2.590001e+12\n",
      "59    2.747986e+12\n",
      "60    2.905970e+12\n",
      "61    3.063955e+12\n",
      "62    3.221940e+12\n",
      "Name: Predictions, dtype: float64\n",
      "58    2.588975e+12\n",
      "59    2.689205e+12\n",
      "60    2.532396e+12\n",
      "61    2.761585e+12\n",
      "62    2.954978e+12\n",
      "Name: GDP_Ind_Dollars, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(predictions.tail())\n",
    "print(Y.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(t,Y,label='Observed GDP')\n",
    "plt.plot(t,predictions,label='Predicted GDP')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('India GDP in Dollars')\n",
    "plt.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Error Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE VALUES:::\n",
      "Training set(1960-2017): 2.81e+10\n",
      "Test set(2018-2022): 2.47e+11\n",
      "Entire set(1960-2022): 7.47e+10\n",
      "CORR. COEFF.S:::\n",
      "Training set(1960-2017): 0.9990\n",
      "Test set(2018-2022): 0.7698\n",
      "Entire set(1960-2022): 0.9970\n"
     ]
    }
   ],
   "source": [
    "rmse_train=rmse(Y[:58],predictions[:58])\n",
    "rmse_test=rmse(Y[58:],predictions[58:])\n",
    "rmse_entire=rmse(Y,predictions)\n",
    "print(\"RMSE VALUES:::\")\n",
    "print(\"Training set(1960-2017): %.2e\" %rmse_train)\n",
    "print(\"Test set(2018-2022): %.2e\" %rmse_test)\n",
    "print(\"Entire set(1960-2022): %.2e\" %rmse_entire)\n",
    "\n",
    "corr_train=np.corrcoef(Y[:58],predictions[:58])\n",
    "corr_test=np.corrcoef(Y[58:],predictions[58:])\n",
    "corr_entire=np.corrcoef(Y,predictions)\n",
    "print(\"CORR. COEFF.S:::\")\n",
    "print(\"Training set(1960-2017): %.4f\" %corr_train[0,1])\n",
    "print(\"Test set(2018-2022): %.4f\" %corr_test[0,1])\n",
    "print(\"Entire set(1960-2022): %.4f\" %corr_entire[0,1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Forecasting for the future(2023-2030)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "future=arima_model.predict(63,70).rename(\"Future\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Years   Predictions\n",
      "63   2023  3.379925e+12\n",
      "64   2024  3.537909e+12\n",
      "65   2025  3.695894e+12\n",
      "66   2026  3.853879e+12\n",
      "67   2027  4.011864e+12\n",
      "68   2028  4.169848e+12\n",
      "69   2029  4.327833e+12\n",
      "70   2030  4.485818e+12\n"
     ]
    }
   ],
   "source": [
    "df_curr=pd.DataFrame()\n",
    "df_curr[\"Years\"]=t\n",
    "df_curr[\"Predictions\"]=predictions\n",
    "df_fut=pd.DataFrame()\n",
    "df_fut[\"Years\"]=pd.Series([x for x in range(2023,2031)]).set_axis([x for x in range(63,71)])\n",
    "df_fut[\"Predictions\"]=future\n",
    "print(df_fut)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df=pd.concat([df_curr,df_fut])\n",
    "plt.plot(t,Y,label=\"Actual GDP(1960-2022)\")\n",
    "plt.plot(df.Years,df.Predictions,label=\"Predicted GDP(1960-2030)\")\n",
    "plt.xlabel(\"Years\")\n",
    "plt.ylabel(\"GDP in USD\")\n",
    "plt.tight_layout()\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extra: Using entire dataset for prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "model2=ARIMA(Y,order=(0,2,1))\n",
    "arima_model2=model2.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions2=arima_model2.predict(0,62).rename('Predictions')\n",
    "future2=arima_model2.predict(63,70).rename(\"Future\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_curr2=pd.DataFrame()\n",
    "df_curr2[\"Years\"]=t\n",
    "df_curr2[\"Predictions\"]=predictions2\n",
    "df_fut2=pd.DataFrame()\n",
    "df_fut2[\"Years\"]=pd.Series([x for x in range(2023,2031)]).set_axis([x for x in range(63,71)])\n",
    "df_fut2[\"Predictions\"]=future2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2=pd.concat([df_curr2,df_fut2])\n",
    "plt.plot(t,Y,label=\"Actual GDP(1960-2022)\")\n",
    "plt.plot(df2.Years,df2.Predictions,label=\"Predicted GDP(1960-2030)\")\n",
    "plt.xlabel(\"Years\")\n",
    "plt.ylabel(\"GDP in USD\")\n",
    "plt.tight_layout()\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 5.18e+10\n",
      "CORR: 0.9980\n"
     ]
    }
   ],
   "source": [
    "rmse_entire2=rmse(Y,predictions2)\n",
    "corr_entire2=np.corrcoef(Y,predictions2)\n",
    "print(\"RMSE: %.2e\" %rmse_entire2)\n",
    "print(\"CORR: %.4f\" %corr_entire2[0,1])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}