wOBAと打席数の長方形で選手の得点力を出すサンプル

rectangle_woba_pa.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pymysql\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "pd.options.display.max_columns = 30\n",
    "pd.options.display.max_rows = 60"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Connect Baseball Database\n",
    "connection = pymysql.connect(\n",
    "    host=os.environ.get('DB_HOST'),\n",
    "    user=os.environ.get('DB_USER'),\n",
    "    password=os.environ.get('DB_PASSWORD'),\n",
    "    db=os.environ.get('DB_DATABASE'),\n",
    "    charset='utf8',\n",
    "    cursorclass=pymysql.cursors.DictCursor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Batting Stats for Central League(over 200 pa)\n",
    "query_cl_batting = \"\"\"\n",
    "SELECT team AS `TEAM`,\n",
    "       number AS `NUMBER`,\n",
    "       name AS `NAME`,\n",
    "       ba AS `AVG`,\n",
    "       ba_risp AS `AVG_RISP`,\n",
    "       pa AS `PA`,\n",
    "       r AS `RUN`,\n",
    "       h AS `HIT`,\n",
    "       2b AS `2B`,\n",
    "        3b AS `3B`,\n",
    "         hr AS `HR`,\n",
    "         rbi AS `RBI`,\n",
    "         so AS `SO`,\n",
    "         bb AS `BB`,\n",
    "         sb AS `SB`,\n",
    "         cs AS `CS`,\n",
    "         dp AS `DP`,\n",
    "         obp AS `OBP`,\n",
    "         slg AS `SLG`,\n",
    "         ops AS `OPS`,\n",
    "         rc27 AS `RC27`,\n",
    "         woba AS `wOBA`,\n",
    "         wraa AS `wRAA`\n",
    "FROM player_batting\n",
    "WHERE YEAR = 2017\n",
    "  AND date =\n",
    "    (SELECT max(date)\n",
    "     FROM player_batting)\n",
    "  AND team IN ('g',\n",
    "               's',\n",
    "               'db',\n",
    "               'd',\n",
    "               't',\n",
    "               'c')\n",
    "  AND pa >= 200\n",
    "ORDER BY wRAA DESC\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_cl_batting = pd.read_sql(query_cl_batting, con=connection)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_example_area_maru = df_cl_batting.query('NAME==\"丸 佳浩\"')\n",
    "df_example_area_koba = df_cl_batting.query('NAME==\"小林 誠司\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pa_maru = df_example_area_maru['PA']\n",
    "woba_maru = df_example_area_maru['wOBA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pa_koba = df_example_area_koba['PA']\n",
    "woba_koba = df_example_area_koba['wOBA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d5733c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#  Red：丸(広島) Orange：小林(巨人)\n",
    "from matplotlib import pyplot as plt\n",
    "from matplotlib.patches import Rectangle\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "rect_maru = Rectangle((0.0, 0.0), pa_maru.values[0] / 1000, woba_maru.values[0], fc=\"red\")\n",
    "rect_koba = Rectangle((0.0, 0.0), pa_koba.values[0] / 1000, woba_koba.values[0], fc=\"orange\")\n",
    "ax.add_patch(rect_maru)\n",
    "ax.add_patch(rect_koba)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 続けてパ・リーグ\n",
    "# Batting Stats for Pacific League(over 200 pa)\n",
    "query_pl_batting = \"\"\"\n",
    "SELECT team AS `TEAM`,\n",
    "       number AS `NUMBER`,\n",
    "       name AS `NAME`,\n",
    "       ba AS `AVG`,\n",
    "       ba_risp AS `AVG_RISP`,\n",
    "       pa AS `PA`,\n",
    "       r AS `RUN`,\n",
    "       h AS `HIT`,\n",
    "       2b AS `2B`,\n",
    "        3b AS `3B`,\n",
    "         hr AS `HR`,\n",
    "         rbi AS `RBI`,\n",
    "         so AS `SO`,\n",
    "         bb AS `BB`,\n",
    "         sb AS `SB`,\n",
    "         cs AS `CS`,\n",
    "         dp AS `DP`,\n",
    "         obp AS `OBP`,\n",
    "         slg AS `SLG`,\n",
    "         ops AS `OPS`,\n",
    "         rc27 AS `RC27`,\n",
    "         woba AS `wOBA`,\n",
    "         wraa AS `wRAA`\n",
    "FROM player_batting\n",
    "WHERE YEAR = 2017\n",
    "  AND date =\n",
    "    (SELECT max(date)\n",
    "     FROM player_batting)\n",
    "  AND team IN ('l',\n",
    "               'f',\n",
    "               'm',\n",
    "               'bs',\n",
    "               'h',\n",
    "               'e')\n",
    "  AND pa >= 200\n",
    "ORDER BY wRAA DESC\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_pl_batting = pd.read_sql(query_pl_batting, con=connection)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_example_area_gi__ta = df_pl_batting.query('NAME==\"柳田 悠岐\"')\n",
    "df_example_area_takuya = df_pl_batting.query('NAME==\"中島 卓也\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pa_gi__ta = df_example_area_gi__ta['PA']\n",
    "woba_gi__ta = df_example_area_gi__ta['wOBA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pa_takuya = df_example_area_takuya['PA']\n",
    "woba_takuya = df_example_area_takuya['wOBA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d5730f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#  Yellow：ギータ(ソフトバンク) Blue：中島卓也(日ハム)\n",
    "from matplotlib import pyplot as plt\n",
    "from matplotlib.patches import Rectangle\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "rect_gi__ta = Rectangle((0.0, 0.0), pa_gi__ta.values[0] / 1000, woba_gi__ta.values[0], fc=\"yellow\")\n",
    "rect_takuya = Rectangle((0.0, 0.0), pa_takuya.values[0] / 1000, woba_takuya.values[0], fc=\"blue\")\n",
    "ax.add_patch(rect_gi__ta)\n",
    "ax.add_patch(rect_takuya)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "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": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}