{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第4章 Matplotlibでグラフを 描画しよう\n",
    "\n",
    "### 4-7: 箱ひげ図"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2078df01f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# リスト4.7.1：箱ひげ図の描画\n",
    "plt.style.use(\"ggplot\")\n",
    "x = [1, 2, 3, 3, 11, 20]\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.boxplot(x)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2078e064ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# リスト4.7.2：複数の箱ひげ図の描画\n",
    "# 複数のリストをリストにセット\n",
    "x = [[1, 2, 3, 3, 11, 20], [1, 2, 9, 10, 15, 16]]\n",
    "labels = [\"A\", \"B\"]\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "# データとラベルを指定\n",
    "ax.boxplot(x, labels=labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>genre</th>\n",
       "      <th>type</th>\n",
       "      <th>episodes</th>\n",
       "      <th>rating</th>\n",
       "      <th>members</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>anime_id</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>32281</th>\n",
       "      <td>Kimi no Na wa.</td>\n",
       "      <td>Drama, Romance, School, Supernatural</td>\n",
       "      <td>Movie</td>\n",
       "      <td>1</td>\n",
       "      <td>9.37</td>\n",
       "      <td>200630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5114</th>\n",
       "      <td>Fullmetal Alchemist: Brotherhood</td>\n",
       "      <td>Action, Adventure, Drama, Fantasy, Magic, Mili...</td>\n",
       "      <td>TV</td>\n",
       "      <td>64</td>\n",
       "      <td>9.26</td>\n",
       "      <td>793665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28977</th>\n",
       "      <td>Gintama°</td>\n",
       "      <td>Action, Comedy, Historical, Parody, Samurai, S...</td>\n",
       "      <td>TV</td>\n",
       "      <td>51</td>\n",
       "      <td>9.25</td>\n",
       "      <td>114262</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      name  \\\n",
       "anime_id                                     \n",
       "32281                       Kimi no Na wa.   \n",
       "5114      Fullmetal Alchemist: Brotherhood   \n",
       "28977                             Gintama°   \n",
       "\n",
       "                                                      genre   type  episodes  \\\n",
       "anime_id                                                                       \n",
       "32281                  Drama, Romance, School, Supernatural  Movie         1   \n",
       "5114      Action, Adventure, Drama, Fantasy, Magic, Mili...     TV        64   \n",
       "28977     Action, Comedy, Historical, Parody, Samurai, S...     TV        51   \n",
       "\n",
       "          rating  members  \n",
       "anime_id                   \n",
       "32281       9.37   200630  \n",
       "5114        9.26   793665  \n",
       "28977       9.25   114262  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# リスト4.7.3：anime_master.csvファイルの読み込み\n",
    "import os\n",
    "import pandas as pd\n",
    "\n",
    "base_url = \"https://raw.githubusercontent.com/practical-jupyter/sample-data/master/anime/\"\n",
    "anime_master_csv = os.path.join(base_url, \"anime_master.csv\")\n",
    "df = pd.read_csv(anime_master_csv, index_col=\"anime_id\")\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2078df01710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# リスト4.7.4：配給種別ごとのエピソード数を可視化\n",
    "labels = []\n",
    "types_list = []\n",
    "# 配給種別ごとのエピソード数の情報をリスト化\n",
    "for label, df_per_type in df.groupby(\"type\"):\n",
    "    labels.append(label)\n",
    "    types_list.append(df_per_type[\"episodes\"].tolist())\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.boxplot(types_list, labels=labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2078f001b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# リスト4.7.5：描画範囲を限定した箱ひげ図\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.boxplot(types_list, labels=labels)\n",
    "# Y軸の描画範囲を0から100までに限定\n",
    "ax.set_ylim(0, 100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3330.0\n",
       "mean       37.5\n",
       "std        83.3\n",
       "min         3.0\n",
       "25%        13.0\n",
       "50%        25.0\n",
       "75%        43.0\n",
       "max      1818.0\n",
       "Name: episodes, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# リスト4.7.6：四分位点の値をdescribe()で確認\n",
    "df[\"episodes\"][df[\"type\"] == \"TV\"].describe().round(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# リスト4.7.7：データセットの作成\n",
    "import numpy as np\n",
    "\n",
    "np.random.seed(3)\n",
    "dataset = [np.random.normal(20 + mu, 5, 1000) for mu in range(1, 5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# リスト4.7.8：書式辞書の作成\n",
    "# はずれ値の書式辞書\n",
    "flierprop = {\"color\": \"#EC407A\",\n",
    "             \"marker\": \"o\",\n",
    "             \"markerfacecolor\": \"#2196F3\",\n",
    "             \"markeredgecolor\": \"white\",\n",
    "             \"markersize\": 5,\n",
    "             \"linestyle\": \"None\",\n",
    "             \"linewidth\": 0.1}\n",
    "# 箱の書式辞書\n",
    "boxprop = {\"color\": \"#2196F3\", \n",
    "           \"facecolor\": \"#BBDEFB\", \n",
    "           \"linewidth\": 1, \n",
    "           \"linestyle\": \"-\"}\n",
    "# ヒゲの書式辞書\n",
    "whiskerprop = {\"color\": \"#2196F3\", \n",
    "               \"linewidth\": 1, \n",
    "               \"linestyle\": \"--\"}\n",
    "# ヒゲ末端キャップの書式辞書\n",
    "capprop = {\"color\": \"#2196F3\", \n",
    "           \"linewidth\": 1, \n",
    "           \"linestyle\": \":\"}\n",
    "# 中央値の書式辞書\n",
    "medianprop = {\"color\": \"#2196F3\", \n",
    "              \"linewidth\": 2, \n",
    "              \"linestyle\": \"-\"}\n",
    "# 平均値の書式辞書\n",
    "meanprop = {\"color\": \"#2196F3\",\n",
    "            \"marker\": \"^\",\n",
    "            \"markerfacecolor\": \"#2196F3\",\n",
    "            \"markeredgecolor\": \"white\",\n",
    "            \"markersize\": 10,\n",
    "            \"linewidth\": 1,\n",
    "            \"linestyle\": \"\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2078ee307b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# リスト4.7.9：箱ひげ図の書式一括設定\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.boxplot(\n",
    "    dataset,\n",
    "    patch_artist=\"Patch\",  # 書式を設定する場合は 「Patch」 を選択\n",
    "    labels=[\"A\", \"B\", \"C\", \"D\"],  # 項目ラベル\n",
    "    showmeans=True,  # 平均値の描画\n",
    "    flierprops=flierprop,  # はずれ値の書式設定\n",
    "    boxprops=boxprop,  # ボックスの書式設定\n",
    "    whiskerprops=whiskerprop,  # ヒゲの書式設定\n",
    "    capprops=capprop,  # ヒゲのキャップの書式設定\n",
    "    medianprops=medianprop,  # 中央値の書式設定\n",
    "    meanprops=meanprop,  # 平均値の書式設定\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2078e0a6978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# リスト4.7.10：ボックスごとに書式を設定する\n",
    "# 図の描画\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "bp = ax.boxplot(\n",
    "    dataset,\n",
    "    patch_artist=\"Patch\",\n",
    "    labels=[\"A\", \"B\", \"C\", \"D\"],\n",
    "    meanline=True,\n",
    "    showmeans=True,\n",
    ")\n",
    "# カラーセット\n",
    "colors1 = [\"#2196F3\", \"#43A047\", \"#FBC02D\", \"#FB8C00\"]\n",
    "colors2 = [\"#BBDEFB\", \"#C8E6C9\", \"#FFF9C4\", \"#FFE0B2\"]\n",
    "# 上下に分かれた要素に設定するための用の数列\n",
    "n = [0, 0, 1, 1, 2, 2, 3, 3]\n",
    "# 書式設定\n",
    "# ボックスとはずれ値、 中央値の書式設定\n",
    "for params in zip(bp[\"boxes\"], bp[\"fliers\"], bp[\"medians\"], colors1, colors2):\n",
    "    bpb, bpf, med, color1, color2 = params\n",
    "    # ボックスの書式設定\n",
    "    bpb.set_color(color1)\n",
    "    bpb.set_facecolor(color2)\n",
    "    bpb.set_linewidth(2)\n",
    "    # 外れ値の書式設定\n",
    "    bpf.set(marker=\"^\", color=color2)\n",
    "    bpf.set_markeredgecolor(\"white\")\n",
    "    bpf.set_markerfacecolor(color1)\n",
    "    # 中央値の書式設定\n",
    "    med.set_color(color1)\n",
    "    med.set_linewidth(2)\n",
    "# ヒゲとヒゲの末端キャップの書式設定\n",
    "for bpc, bpw, m in zip(bp[\"caps\"], bp[\"whiskers\"], n):\n",
    "    bpc.set_color(colors1[m])\n",
    "    bpc.set_linewidth(2)\n",
    "    bpw.set_color(colors1[m])\n",
    "    bpw.set_linewidth(2)\n",
    "# 平均値の書式設定\n",
    "for mean, color2 in zip(bp[\"means\"], colors2):\n",
    "    mean.set_color(\"grey\")\n",
    "    mean.set_linewidth(2)\n",
    "    mean.set_linestyle(\"--\")\n",
    "plt.show()"
   ]
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