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@kurozumi
Created July 18, 2016 02:27
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【Python】PandasとSeabornを使ってJリーグチームの入場者数の推移をグラフ化する方法
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#pip install pandas lxml html5lib BeautifulSoup4 matplotlib seaborn"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"\n",
"import pandas as pd\n",
"import seaborn as sns"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"year = 2016\n",
"url = \"http://data.jleague.jp/SFMS01/search?competition_years={year}&team_ids=42&home_away_select=0&section_months=1&section_months=2&section_months=3&section_months=4&section_months=5&section_months=6&section_months=7&section_months=8&section_months=9&section_months=10&section_months=11&section_months=12\".format(year=year)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"databases = pd.io.html.read_html(url)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"database = databases[0]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# シーズン途中なのでNanの入場者数行を削除\n",
"database = database.dropna()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# ホームの入場者数だけ取得\n",
"home = database[database[\"ホーム\"]==\"岡山\"]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1175bf8d0>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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50ICzZQ0yRkOu0GJux1tb85B/rlY6NmpoMFYsnOARdfzlICUBdgl0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\nzEmJ6jIJ9/uTVdKyXHcp1xvx6vs5qKz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"text/plain": [
"<matplotlib.figure.Figure at 0x1175c9b00>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# x軸を試合日、y軸を入場者数でグラフを表示\n",
"sns.pointplot(x=\"試合日\", y=\"入場者数\", data=home)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>年度</th>\n",
" <th>大会</th>\n",
" <th>節</th>\n",
" <th>試合日</th>\n",
" <th>K/O時刻</th>\n",
" <th>ホーム</th>\n",
" <th>スコア</th>\n",
" <th>アウェイ</th>\n",
" <th>スタジアム</th>\n",
" <th>入場者数</th>\n",
" <th>TV放送</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第2節第1日</td>\n",
" <td>03/06(日)</td>\n",
" <td>14:03</td>\n",
" <td>岡山</td>\n",
" <td>2-1</td>\n",
" <td>千葉</td>\n",
" <td>Cスタ</td>\n",
" <td>9288.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第3節第2日</td>\n",
" <td>03/13(日)</td>\n",
" <td>13:03</td>\n",
" <td>岡山</td>\n",
" <td>2-2</td>\n",
" <td>京都</td>\n",
" <td>Cスタ</td>\n",
" <td>9098.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス/テレビせとうち</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第5節第1日</td>\n",
" <td>03/26(土)</td>\n",
" <td>13:03</td>\n",
" <td>岡山</td>\n",
" <td>2-0</td>\n",
" <td>北九州</td>\n",
" <td>Cスタ</td>\n",
" <td>7050.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第6節第1日</td>\n",
" <td>04/03(日)</td>\n",
" <td>13:03</td>\n",
" <td>岡山</td>\n",
" <td>1-1</td>\n",
" <td>東京V</td>\n",
" <td>Cスタ</td>\n",
" <td>7184.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第9節第1日</td>\n",
" <td>04/23(土)</td>\n",
" <td>19:03</td>\n",
" <td>岡山</td>\n",
" <td>0-1</td>\n",
" <td>山形</td>\n",
" <td>Cスタ</td>\n",
" <td>8256.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第10節第1日</td>\n",
" <td>04/29(金・祝)</td>\n",
" <td>14:04</td>\n",
" <td>岡山</td>\n",
" <td>2-2</td>\n",
" <td>町田</td>\n",
" <td>Cスタ</td>\n",
" <td>9170.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス/山陽放送</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第13節第1日</td>\n",
" <td>05/15(日)</td>\n",
" <td>14:03</td>\n",
" <td>岡山</td>\n",
" <td>0-1</td>\n",
" <td>岐阜</td>\n",
" <td>Cスタ</td>\n",
" <td>9464.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第14節第1日</td>\n",
" <td>05/22(日)</td>\n",
" <td>14:03</td>\n",
" <td>岡山</td>\n",
" <td>2-1</td>\n",
" <td>愛媛</td>\n",
" <td>Cスタ</td>\n",
" <td>8486.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第16節第1日</td>\n",
" <td>06/04(土)</td>\n",
" <td>13:03</td>\n",
" <td>岡山</td>\n",
" <td>2-1</td>\n",
" <td>熊本</td>\n",
" <td>Cスタ</td>\n",
" <td>7308.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス/岡山放送</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第18節第1日</td>\n",
" <td>06/12(日)</td>\n",
" <td>19:03</td>\n",
" <td>岡山</td>\n",
" <td>2-1</td>\n",
" <td>松本</td>\n",
" <td>Cスタ</td>\n",
" <td>8193.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第21節第1日</td>\n",
" <td>07/03(日)</td>\n",
" <td>18:03</td>\n",
" <td>岡山</td>\n",
" <td>2-2</td>\n",
" <td>清水</td>\n",
" <td>Cスタ</td>\n",
" <td>11090.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>2016</td>\n",
" <td>J2</td>\n",
" <td>第23節第1日</td>\n",
" <td>07/16(土)</td>\n",
" <td>19:03</td>\n",
" <td>岡山</td>\n",
" <td>0-0</td>\n",
" <td>札幌</td>\n",
" <td>Cスタ</td>\n",
" <td>13304.0</td>\n",
" <td>スカパー!/スカパー!プレミアムサービス/テレビせとうち</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 年度 大会 節 試合日 K/O時刻 ホーム スコア アウェイ スタジアム 入場者数 \\\n",
"1 2016 J2 第2節第1日 03/06(日) 14:03 岡山 2-1 千葉 Cスタ 9288.0 \n",
"2 2016 J2 第3節第2日 03/13(日) 13:03 岡山 2-2 京都 Cスタ 9098.0 \n",
"4 2016 J2 第5節第1日 03/26(土) 13:03 岡山 2-0 北九州 Cスタ 7050.0 \n",
"5 2016 J2 第6節第1日 04/03(日) 13:03 岡山 1-1 東京V Cスタ 7184.0 \n",
"8 2016 J2 第9節第1日 04/23(土) 19:03 岡山 0-1 山形 Cスタ 8256.0 \n",
"9 2016 J2 第10節第1日 04/29(金・祝) 14:04 岡山 2-2 町田 Cスタ 9170.0 \n",
"12 2016 J2 第13節第1日 05/15(日) 14:03 岡山 0-1 岐阜 Cスタ 9464.0 \n",
"13 2016 J2 第14節第1日 05/22(日) 14:03 岡山 2-1 愛媛 Cスタ 8486.0 \n",
"15 2016 J2 第16節第1日 06/04(土) 13:03 岡山 2-1 熊本 Cスタ 7308.0 \n",
"17 2016 J2 第18節第1日 06/12(日) 19:03 岡山 2-1 松本 Cスタ 8193.0 \n",
"20 2016 J2 第21節第1日 07/03(日) 18:03 岡山 2-2 清水 Cスタ 11090.0 \n",
"22 2016 J2 第23節第1日 07/16(土) 19:03 岡山 0-0 札幌 Cスタ 13304.0 \n",
"\n",
" TV放送 \n",
"1 スカパー!/スカパー!プレミアムサービス \n",
"2 スカパー!/スカパー!プレミアムサービス/テレビせとうち \n",
"4 スカパー!/スカパー!プレミアムサービス \n",
"5 スカパー!/スカパー!プレミアムサービス \n",
"8 スカパー!/スカパー!プレミアムサービス \n",
"9 スカパー!/スカパー!プレミアムサービス/山陽放送 \n",
"12 スカパー!/スカパー!プレミアムサービス \n",
"13 スカパー!/スカパー!プレミアムサービス \n",
"15 スカパー!/スカパー!プレミアムサービス/岡山放送 \n",
"17 スカパー!/スカパー!プレミアムサービス \n",
"20 スカパー!/スカパー!プレミアムサービス \n",
"22 スカパー!/スカパー!プレミアムサービス/テレビせとうち "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#  グラフを作成したデータフレームの内容\n",
"home"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [py35]",
"language": "python",
"name": "Python [py35]"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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