【Python】Pandasを使ってJリーグチームの平均入場者数を計算する方法

average-number-of-visitors.ipynb

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   "source": [
    "#pip install pandas lxml html5lib BeautifulSoup4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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   "source": [
    "import pandas as pd"
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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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   "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
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   "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
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "8990.916666666666"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 平均入場者数\n",
    "home[\"入場者数\"].mean()"
   ]
  }
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