{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Week 7: Tennis Data Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using matplotlib backend: MacOSX\n",
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab\n",
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import seaborn as sn\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import stats\n",
    "\n",
    "data = pd.read_csv(\"tennis.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
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       "        <td id=\"T_75b4b348_4c3a_11e8_bc4a_32001d384000row5_col5\" class=\"data row5 col5\" >1</td> \n",
       "        <td id=\"T_75b4b348_4c3a_11e8_bc4a_32001d384000row5_col6\" class=\"data row5 col6\" >0.757689</td> \n",
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       "        <td id=\"T_75b4b348_4c3a_11e8_bc4a_32001d384000row6_col5\" class=\"data row6 col5\" >0.757689</td> \n",
       "        <td id=\"T_75b4b348_4c3a_11e8_bc4a_32001d384000row6_col6\" class=\"data row6 col6\" >1</td> \n",
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      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1127ee438>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.corr().style.background_gradient(cmap='Wistia')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1124a0400>,\n",
       " <matplotlib.lines.Line2D at 0x1124a0550>,\n",
       " <matplotlib.lines.Line2D at 0x1124a09b0>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = data[\"age\"]\n",
    "y = data[\"points\"]\n",
    "plt.scatter(x, y)\n",
    "plt.xlabel(\"age\")\n",
    "plt.ylabel(\"points\")\n",
    "p1 = poly1d(polyfit(x, y, 1))\n",
    "p2 = poly1d(polyfit(x, y, 2))\n",
    "p3 = poly1d(polyfit(x, y, 3))\n",
    "xu = x.unique()\n",
    "plot(xu, p1(xu), xu, p2(xu), xu, p3(xu))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-578.3045372326807"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poly1d(polyfit(data[\"age\"], data[\"points\"], 2))(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x11258da58>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(xu, p1(xu))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1125f28d0>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(xu, p2(xu))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PolyCollection at 0x11264d3c8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nbins = 15\n",
    "title('Hexbin')\n",
    "hexbin(x, y, gridsize=nbins, cmap=plt.cm.BuGn_r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'points')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(x, y, linestyle='', marker='o', markersize=0.7)\n",
    "xlabel(\"age\")\n",
    "ylabel(\"points\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Height is an advantage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average height of men: 185.64912280701753\n",
      "Average height of women: 180.37142857142857\n"
     ]
    }
   ],
   "source": [
    "male_mean = data.loc[data[\"gender\"] == \"M\"][\"height\"].mean()\n",
    "print(\"Average height of men:\", male_mean)\n",
    "female_mean = data.loc[data[\"gender\"] == \"F\"][\"height\"].mean()\n",
    "print(\"Average height of women:\", female_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T score: 1.711723, P score: 0.043815\n"
     ]
    }
   ],
   "source": [
    "scores_men_tall = data.loc[np.logical_and(data[\"gender\"] == \"M\", data[\"height\"] >= male_mean)][\"points\"]\n",
    "scores_men_short = data.loc[np.logical_and(data[\"gender\"] == \"M\", data[\"height\"] < male_mean)][\"points\"]\n",
    "t, p = stats.ttest_ind(scores_men_tall, scores_men_short)\n",
    "p = p/2 # Because 1 tailed T-Test\n",
    "print(\"T score: %f, P score: %f\" % (t, p))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T score: 1.860241, P score: 0.032030\n"
     ]
    }
   ],
   "source": [
    "scores_women_tall = data.loc[np.logical_and(data[\"gender\"] == \"F\", data[\"height\"] >= female_mean)][\"points\"]\n",
    "scores_women_short = data.loc[np.logical_and(data[\"gender\"] == \"F\", data[\"height\"] < female_mean)][\"points\"]\n",
    "t, p = stats.ttest_ind(scores_women_tall, scores_women_short)\n",
    "p = p/2 # Because 1 tailed T-Test\n",
    "print(\"T score: %f, P score: %f\" % (t, p))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Being left-handed is an advantage\n",
    "\n",
    "Initial investigation using simple data aggragation showed that left handed players hold higher ranks within the tennis board and on average they have more points than right handed players:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average rank of right-handed players: 215.72115384615384\n",
      "Average score of right-handed players: 608.775641025641\n",
      "\n",
      "Average rank of left-handed players: 186.56578947368422\n",
      "Average score of left-handed players: 662.0263157894736\n"
     ]
    }
   ],
   "source": [
    "print(\"Average rank of right-handed players:\", data.loc[data[\"hand\"] == \"R\"][\"ranking\"].mean())\n",
    "print(\"Average score of right-handed players:\", data.loc[data[\"hand\"] == \"R\"][\"points\"].mean())\n",
    "print(\"\\nAverage rank of left-handed players:\", data.loc[data[\"hand\"] == \"L\"][\"ranking\"].mean())\n",
    "print(\"Average score of left-handed players:\", data.loc[data[\"hand\"] == \"L\"][\"points\"].mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To investigate if left handed players have a significant advantage, we conduct a T-Test."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T score: 0.451694, P score: 0.325815\n"
     ]
    }
   ],
   "source": [
    "scoresL = data.loc[data[\"hand\"] == \"L\"][\"points\"]\n",
    "scoresR = data.loc[data[\"hand\"] == \"R\"][\"points\"]\n",
    "t, p = stats.ttest_ind(scoresL, scoresR)\n",
    "p = p/2 # Because 1 tailed T-Test\n",
    "print(\"T score: %f, P score: %f\" % (t, p))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our $t$-Test reveals a $p$-score of $0.325815$. Generally we reject our null-hypothesis when this score is less that $0.05$. From our data we can thus not conclude that left-handed players have a significant advantage over right-handed players."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Resources\n",
    "\n",
    "Links to the converters:\n",
    "- https://surfstat.anu.edu.au/surfstat-home/tables/t.php\n",
    "- http://www.socscistatistics.com/pvalues/tdistribution.aspx\n",
    "- https://goodcalculators.com/student-t-value-calculator/"
   ]
  }
 ],
 "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}