ttest_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cfbd\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from config import api_key\n",
    "import scipy.stats as st\n",
    "\n",
    "plt.rcParams.update({'font.size': 20})\n",
    "plt.rcParams['figure.figsize'] = [18, 10]\n",
    "\n",
    "configuration = cfbd.Configuration()\n",
    "configuration.api_key['Authorization'] = api_key\n",
    "configuration.api_key_prefix['Authorization'] = 'Bearer'\n",
    "\n",
    "api_instance = cfbd.GamesApi(cfbd.ApiClient(configuration))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_points_2004 = []\n",
    "total_points_2020 = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "games = api_instance.get_games(year=2004)\n",
    "for game in games:\n",
    "    total_points_2004.append(int(game.home_points)+int(game.away_points))\n",
    "\n",
    "games = api_instance.get_games(year=2020)\n",
    "for game in games:\n",
    "    total_points_2020.append(int(game.home_points)+int(game.away_points))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(2, 1, 2)\n",
    "plt.hist(total_points_2004, 10, density=True, alpha=0.7, label=\"2004\")\n",
    "plt.hist(total_points_2020, 10, density=True, alpha=0.7, label=\"2020\")\n",
    "plt.axvline(sum(total_points_2004)/len(total_points_2004), color='k', linestyle='dashed', linewidth=1)\n",
    "plt.axvline(sum(total_points_2020)/len(total_points_2020), color='k', linestyle='dashed', linewidth=1)\n",
    "plt.title(\"Histogram of Total Points Scored per Game\", color=\"purple\")\n",
    "plt.xlabel(\"Points Scored\", color=\"purple\")\n",
    "plt.ylabel(\"Proportion\", color=\"purple\")\n",
    "plt.xticks(color=\"purple\")\n",
    "plt.yticks(color=\"purple\")\n",
    "plt.legend()  \n",
    "plt.savefig(\"Output/Histogram.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_2004 = pd.DataFrame({\n",
    "    \"2004 Total Points\": total_points_2004\n",
    "})\n",
    "output_2020 = pd.DataFrame({\n",
    "    \"2020 Total Points\": total_points_2020\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_2004.to_csv(\"Output/2004_ttest_data.csv\", index=False, header=True)\n",
    "output_2020.to_csv(\"Output/2020_ttest_data.csv\", index=False, header=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=-5.014530349905278, pvalue=6.1526352641952e-07)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "st.ttest_ind(total_points_2004, total_points_2020, equal_var=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}