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hotchpotch/打率.ipynb Secret

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打率.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "打率.ipynb",
"provenance": [],
"collapsed_sections": [],
"authorship_tag": "ABX9TyMroyuj1nfw95z46kSwBSxt",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/hotchpotch/671e731670bd23a01db8f453c740507b/.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "js8PQLALJ7lX"
},
"source": [
"%load_ext google.colab.data_table\n"
],
"execution_count": 1,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "OSEoCONrKaZu",
"outputId": "09f673a1-2ae1-4284-d363-d831586b8452"
},
"source": [
"! pip install beautifulsoup4"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.7/dist-packages (4.6.3)\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "4KFUKUD-MRQW"
},
"source": [
"from bs4 import BeautifulSoup\n",
"\n",
"def parse_scores(body):\n",
" soup = BeautifulSoup(body, 'html.parser')\n",
" table = soup.select('table.sticky-left')[0]\n",
" names = [a.get_text().split(':')[1].replace('\\u3000', ' ') for a in table.select('th.pnm > a')]\n",
" scores = [float(hi.get_text().strip()) for hi in table.select('td.hi')]\n",
" return list(zip(names, scores))\n"
],
"execution_count": 3,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "Vl6j41FdOsvX"
},
"source": [
"import itertools\n",
"\n",
"def generate_url_infos():\n",
" leagues = {'ptop': 'パ・リーグ', 'ctop': 'セ・リーグ'}\n",
" years = range(2012, 2021)\n",
" for year, league in itertools.product(years, leagues.keys()):\n",
" url = f\"https://baseballdata.jp/{year}/{league}.html\"\n",
" yield (url, year, leagues[league])\n"
],
"execution_count": 4,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "YwHjSPS9QpAe"
},
"source": [
"import requests\n",
"import time\n",
"\n",
"def generate_scores(url_infos):\n",
" for (url, year, league) in url_infos:\n",
" res = requests.get(url)\n",
" res.encoding = res.apparent_encoding \n",
" body = res.text\n",
" for (rank, (name, score)) in enumerate(parse_scores(body), 1):\n",
" yield (name, score, rank, year, league)\n",
" time.sleep(1) # スクレイピングするので wait をいれる\n",
"\n"
],
"execution_count": 5,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "naQdKejlSb5p"
},
"source": [
"scores = generate_scores(generate_url_infos())\n",
"scores = list(scores)"
],
"execution_count": 6,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 623
},
"id": "ZtMSCNyJShg1",
"outputId": "2ac497bc-f1b5-4194-ec31-e710a356a55c"
},
"source": [
"import pandas as pd\n",
"\n",
"# 毎年の top-30 のスコア\n",
"score_df = pd.DataFrame(scores, columns=['player', 'score', 'rank', 'year', 'league'])\n",
"score_df"
],
"execution_count": 7,
"outputs": [
{
"output_type": "execute_result",
"data": {
"application/vnd.google.colaboratory.module+javascript": "\n import \"https://ssl.gstatic.com/colaboratory/data_table/a6224c040fa35dcf/data_table.js\";\n\n window.createDataTable({\n data: [[{\n 'v': 0,\n 'f': \"0\",\n },\n\"\\u89d2\\u4e2d \\u52dd\\u4e5f\",\n{\n 'v': 0.312,\n 'f': \"0.312\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 1,\n 'f': \"1\",\n },\n\"\\u4e2d\\u5cf6 \\u88d5\\u4e4b\",\n{\n 'v': 0.311,\n 'f': \"0.311\",\n },\n{\n 'v': 2,\n 'f': \"2\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 2,\n 'f': \"2\",\n },\n\"\\u7cf8\\u4e95 \\u5609\\u7537\",\n{\n 'v': 0.304,\n 'f': \"0.304\",\n },\n{\n 'v': 3,\n 'f': \"3\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 3,\n 'f': \"3\",\n },\n\"\\u5185\\u5ddd \\u8056\\u4e00\",\n{\n 'v': 0.3,\n 'f': \"0.3\",\n },\n{\n 'v': 4,\n 'f': \"4\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 4,\n 'f': \"4\",\n },\n\"\\u7530\\u4e2d \\u8ce2\\u4ecb\",\n{\n 'v': 0.3,\n 'f': \"0.3\",\n },\n{\n 'v': 5,\n 'f': \"5\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 5,\n 'f': \"5\",\n },\n\"\\u79cb\\u5c71 \\u7fd4\\u543e\",\n{\n 'v': 0.293,\n 'f': \"0.293\",\n },\n{\n 'v': 6,\n 'f': \"6\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 6,\n 'f': \"6\",\n },\n\"\\u7a32\\u8449 \\u7be4\\u7d00\",\n{\n 'v': 0.29,\n 'f': \"0.29\",\n },\n{\n 'v': 7,\n 'f': \"7\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 7,\n 'f': \"7\",\n },\n\"\\u6817\\u5c71 \\u5de7\",\n{\n 'v': 0.289,\n 'f': \"0.289\",\n },\n{\n 'v': 8,\n 'f': \"8\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 8,\n 'f': \"8\",\n },\n\"\\u967d 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\"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 13,\n 'f': \"13\",\n },\n\"\\u9577\\u8c37\\u5ddd \\u52c7\\u4e5f\",\n{\n 'v': 0.278,\n 'f': \"0.278\",\n },\n{\n 'v': 14,\n 'f': \"14\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 14,\n 'f': \"14\",\n },\n\"\\u30d8\\u30eb\\u30de\\u30f3\",\n{\n 'v': 0.27,\n 'f': \"0.27\",\n },\n{\n 'v': 15,\n 'f': \"15\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 15,\n 'f': \"15\",\n },\n\"\\u8056\\u6fa4 \\u8ad2\",\n{\n 'v': 0.27,\n 'f': \"0.27\",\n },\n{\n 'v': 16,\n 'f': \"16\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 16,\n 'f': \"16\",\n },\n\"\\u5ddd\\u7aef \\u5d07\\u7fa9\",\n{\n 'v': 0.266,\n 'f': \"0.266\",\n },\n{\n 'v': 17,\n 'f': \"17\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 17,\n 'f': \"17\",\n 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},\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 26,\n 'f': \"26\",\n },\n\"\\u30b5\\u30d6\\u30ed\\u30fc\",\n{\n 'v': 0.239,\n 'f': \"0.239\",\n },\n{\n 'v': 27,\n 'f': \"27\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 27,\n 'f': \"27\",\n },\n\"\\u4e2d\\u7530 \\u7fd4\",\n{\n 'v': 0.239,\n 'f': \"0.239\",\n },\n{\n 'v': 28,\n 'f': \"28\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 28,\n 'f': \"28\",\n },\n\"\\u4e2d\\u6751 \\u525b\\u4e5f\",\n{\n 'v': 0.231,\n 'f': \"0.231\",\n },\n{\n 'v': 29,\n 'f': \"29\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 29,\n 'f': \"29\",\n },\n\"\\u5c0f\\u8c37\\u91ce \\u6804\\u4e00\",\n{\n 'v': 0.228,\n 'f': \"0.228\",\n },\n{\n 'v': 30,\n 'f': \"30\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 30,\n 'f': \"30\",\n },\n\"\\u963f\\u90e8 \\u614e\\u4e4b\\u52a9\",\n{\n 'v': 0.34,\n 'f': \"0.34\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 31,\n 'f': \"31\",\n },\n\"\\u5742\\u672c \\u52c7\\u4eba\",\n{\n 'v': 0.311,\n 'f': \"0.311\",\n },\n{\n 'v': 2,\n 'f': \"2\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 32,\n 'f': \"32\",\n },\n\"\\u5927\\u5cf6 \\u6d0b\\u5e73\",\n{\n 'v': 0.31,\n 'f': \"0.31\",\n },\n{\n 'v': 3,\n 'f': \"3\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 33,\n 'f': \"33\",\n },\n\"\\u9577\\u91ce \\u4e45\\u7fa9\",\n{\n 'v': 0.301,\n 'f': \"0.301\",\n },\n{\n 'v': 4,\n 'f': \"4\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 34,\n 'f': \"34\",\n },\n\"\\u30df\\u30ec\\u30c3\\u30b8\",\n{\n 'v': 0.3,\n 'f': \"0.3\",\n },\n{\n 'v': 5,\n 'f': \"5\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 35,\n 'f': \"35\",\n },\n\"\\u30e9\\u30df\\u30ec\\u30b9\",\n{\n 'v': 0.3,\n 'f': \"0.3\",\n },\n{\n 'v': 6,\n 'f': \"6\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 36,\n 'f': \"36\",\n },\n\"\\u5ddd\\u7aef \\u614e\\u543e\",\n{\n 'v': 0.298,\n 'f': \"0.298\",\n },\n{\n 'v': 7,\n 'f': \"7\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 37,\n 'f': \"37\",\n },\n\"\\u548c\\u7530 \\u4e00\\u6d69\",\n{\n 'v': 0.285,\n 'f': \"0.285\",\n },\n{\n 'v': 8,\n 'f': \"8\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 38,\n 'f': \"38\",\n },\n\"\\u4e95\\u7aef \\u5f18\\u548c\",\n{\n 'v': 0.284,\n 'f': \"0.284\",\n },\n{\n 'v': 9,\n 'f': \"9\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 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},\n\"\\u5c71\\u7530 \\u54f2\\u4eba\",\n{\n 'v': 0.254,\n 'f': \"0.254\",\n },\n{\n 'v': 22,\n 'f': \"22\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 498,\n 'f': \"498\",\n },\n\"\\u30bd\\u30c8\",\n{\n 'v': 0.252,\n 'f': \"0.252\",\n },\n{\n 'v': 23,\n 'f': \"23\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 499,\n 'f': \"499\",\n },\n\"\\u7530\\u4e2d \\u5e83\\u8f14\",\n{\n 'v': 0.251,\n 'f': \"0.251\",\n },\n{\n 'v': 24,\n 'f': \"24\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 500,\n 'f': \"500\",\n },\n\"\\u5742\\u53e3 \\u667a\\u9686\",\n{\n 'v': 0.246,\n 'f': \"0.246\",\n },\n{\n 'v': 25,\n 'f': \"25\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 501,\n 'f': \"501\",\n },\n\"\\u4eac\\u7530 \\u967d\\u592a\",\n{\n 'v': 0.244,\n 'f': \"0.244\",\n },\n{\n 'v': 26,\n 'f': \"26\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 502,\n 'f': \"502\",\n },\n\"\\u30dc\\u30fc\\u30a2\",\n{\n 'v': 0.243,\n 'f': \"0.243\",\n },\n{\n 'v': 27,\n 'f': \"27\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"]],\n columns: [[\"number\", \"index\"], [\"string\", \"player\"], [\"number\", \"score\"], [\"number\", \"rank\"], [\"number\", \"year\"], [\"string\", \"league\"]],\n columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n rowsPerPage: 25,\n helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n suppressOutputScrolling: true,\n minimumWidth: undefined,\n });\n ",
"text/html": [
"<div>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>player</th>\n",
" <th>score</th>\n",
" <th>rank</th>\n",
" <th>year</th>\n",
" <th>league</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>角中 勝也</td>\n",
" <td>0.312</td>\n",
" <td>1</td>\n",
" <td>2012</td>\n",
" <td>パ・リーグ</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>中島 裕之</td>\n",
" <td>0.311</td>\n",
" <td>2</td>\n",
" <td>2012</td>\n",
" <td>パ・リーグ</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>糸井 嘉男</td>\n",
" <td>0.304</td>\n",
" <td>3</td>\n",
" <td>2012</td>\n",
" <td>パ・リーグ</td>\n",
" </tr>\n",
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" <th>3</th>\n",
" <td>内川 聖一</td>\n",
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" <td>パ・リーグ</td>\n",
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" <td>2012</td>\n",
" <td>パ・リーグ</td>\n",
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" <th>498</th>\n",
" <td>ソト</td>\n",
" <td>0.252</td>\n",
" <td>23</td>\n",
" <td>2020</td>\n",
" <td>セ・リーグ</td>\n",
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" <td>田中 広輔</td>\n",
" <td>0.251</td>\n",
" <td>24</td>\n",
" <td>2020</td>\n",
" <td>セ・リーグ</td>\n",
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" <td>25</td>\n",
" <td>2020</td>\n",
" <td>セ・リーグ</td>\n",
" </tr>\n",
" <tr>\n",
" <th>501</th>\n",
" <td>京田 陽太</td>\n",
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" <td>セ・リーグ</td>\n",
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],
"text/plain": [
" player score rank year league\n",
"0 角中 勝也 0.312 1 2012 パ・リーグ\n",
"1 中島 裕之 0.311 2 2012 パ・リーグ\n",
"2 糸井 嘉男 0.304 3 2012 パ・リーグ\n",
"3 内川 聖一 0.300 4 2012 パ・リーグ\n",
"4 田中 賢介 0.300 5 2012 パ・リーグ\n",
".. ... ... ... ... ...\n",
"498 ソト 0.252 23 2020 セ・リーグ\n",
"499 田中 広輔 0.251 24 2020 セ・リーグ\n",
"500 坂口 智隆 0.246 25 2020 セ・リーグ\n",
"501 京田 陽太 0.244 26 2020 セ・リーグ\n",
"502 ボーア 0.243 27 2020 セ・リーグ\n",
"\n",
"[503 rows x 5 columns]"
]
},
"metadata": {},
"execution_count": 7
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 265
},
"id": "4h5NL_y6UV4B",
"outputId": "f4ae6d56-e2a7-46da-a05f-d494282641de"
},
"source": [
"import matplotlib.pyplot as plt\n",
"score_df['score'].plot.hist(bins=30)\n",
"plt.show()"
],
"execution_count": 8,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 640
},
"id": "A4fY70YKVLYN",
"outputId": "4ce1080b-1e60-4567-9084-9aede8da6164"
},
"source": [
"top_10_df = score_df[score_df['rank'] <= 10]\n",
"print(len(top_10_df))\n",
"top_10_df.sort_values('score', ascending=False)"
],
"execution_count": 9,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"180\n"
]
},
{
"output_type": "execute_result",
"data": {
"application/vnd.google.colaboratory.module+javascript": "\n import \"https://ssl.gstatic.com/colaboratory/data_table/a6224c040fa35dcf/data_table.js\";\n\n window.createDataTable({\n data: [[{\n 'v': 166,\n 'f': \"166\",\n },\n\"\\u67f3\\u7530 \\u60a0\\u5c90\",\n{\n 'v': 0.363,\n 'f': \"0.363\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2015,\n 'f': \"2015\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 167,\n 'f': \"167\",\n },\n\"\\u79cb\\u5c71 \\u7fd4\\u543e\",\n{\n 'v': 0.359,\n 'f': \"0.359\",\n },\n{\n 'v': 2,\n 'f': \"2\",\n },\n{\n 'v': 2015,\n 'f': \"2015\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 330,\n 'f': \"330\",\n },\n\"\\u67f3\\u7530 \\u60a0\\u5c90\",\n{\n 'v': 0.352,\n 'f': \"0.352\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2018,\n 'f': \"2018\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 450,\n 'f': \"450\",\n },\n\"\\u5409\\u7530 \\u6b63\\u5c1a\",\n{\n 'v': 0.35,\n 'f': \"0.35\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 359,\n 'f': \"359\",\n },\n\"\\u30d3\\u30b7\\u30a8\\u30c9\",\n{\n 'v': 0.348,\n 'f': \"0.348\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2018,\n 'f': \"2018\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 360,\n 'f': \"360\",\n },\n\"\\u5742\\u672c \\u52c7\\u4eba\",\n{\n 'v': 0.345,\n 'f': \"0.345\",\n },\n{\n 'v': 2,\n 'f': \"2\",\n },\n{\n 'v': 2018,\n 'f': \"2018\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 248,\n 'f': \"248\",\n },\n\"\\u5742\\u672c \\u52c7\\u4eba\",\n{\n 'v': 0.344,\n 'f': \"0.344\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2016,\n 'f': \"2016\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 451,\n 'f': \"451\",\n },\n\"\\u67f3\\u7530 \\u60a0\\u5c90\",\n{\n 'v': 0.342,\n 'f': \"0.342\",\n },\n{\n 'v': 2,\n 'f': \"2\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 54,\n 'f': \"54\",\n },\n\"\\u9577\\u8c37\\u5ddd \\u52c7\\u4e5f\",\n{\n 'v': 0.341,\n 'f': \"0.341\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2013,\n 'f': \"2013\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 30,\n 'f': \"30\",\n },\n\"\\u963f\\u90e8 \\u614e\\u4e4b\\u52a9\",\n{\n 'v': 0.34,\n 'f': \"0.34\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 452,\n 'f': \"452\",\n },\n\"\\u8fd1\\u85e4 \\u5065\\u4ecb\",\n{\n 'v': 0.34,\n 'f': \"0.34\",\n },\n{\n 'v': 3,\n 'f': \"3\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 220,\n 'f': \"220\",\n },\n\"\\u89d2\\u4e2d \\u52dd\\u4e5f\",\n{\n 'v': 0.339,\n 'f': \"0.339\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2016,\n 'f': \"2016\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 139,\n 'f': \"139\",\n },\n\"\\u30de\\u30fc\\u30c8\\u30f3\",\n{\n 'v': 0.338,\n 'f': \"0.338\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2014,\n 'f': \"2014\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 196,\n 'f': \"196\",\n },\n\"\\u5ddd\\u7aef \\u614e\\u543e\",\n{\n 'v': 0.336,\n 'f': \"0.336\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2015,\n 'f': \"2015\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 249,\n 'f': \"249\",\n },\n\"\\u9234\\u6728 \\u8aa0\\u4e5f\",\n{\n 'v': 0.335,\n 'f': \"0.335\",\n },\n{\n 'v': 2,\n 'f': \"2\",\n },\n{\n 'v': 2016,\n 'f': \"2016\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 420,\n 'f': \"420\",\n },\n\"\\u9234\\u6728 \\u8aa0\\u4e5f\",\n{\n 'v': 0.335,\n 'f': \"0.335\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 2019,\n 'f': \"2019\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 87,\n 'f': \"87\",\n },\n\"\\u30d6\\u30e9\\u30f3\\u30b3\",\n{\n 'v': 0.333,\n 'f': \"0.333\",\n },\n{\n 'v': 1,\n 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},\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 205,\n 'f': \"205\",\n },\n\"\\u68b6\\u8c37 \\u9686\\u5e78\",\n{\n 'v': 0.275,\n 'f': \"0.275\",\n },\n{\n 'v': 10,\n 'f': \"10\",\n },\n{\n 'v': 2015,\n 'f': \"2015\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 459,\n 'f': \"459\",\n },\n\"\\u5927\\u7530 \\u6cf0\\u793a\",\n{\n 'v': 0.275,\n 'f': \"0.275\",\n },\n{\n 'v': 10,\n 'f': \"10\",\n },\n{\n 'v': 2020,\n 'f': \"2020\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 284,\n 'f': \"284\",\n },\n\"\\u677e\\u672c \\u525b\",\n{\n 'v': 0.274,\n 'f': \"0.274\",\n },\n{\n 'v': 10,\n 'f': \"10\",\n },\n{\n 'v': 2017,\n 'f': \"2017\",\n },\n\"\\u30d1\\u30fb\\u30ea\\u30fc\\u30b0\"],\n [{\n 'v': 39,\n 'f': \"39\",\n },\n\"\\u4e2d\\u6751 \\u7d00\\u6d0b\",\n{\n 'v': 0.274,\n 'f': \"0.274\",\n },\n{\n 'v': 10,\n 'f': \"10\",\n },\n{\n 'v': 2012,\n 'f': \"2012\",\n },\n\"\\u30bb\\u30fb\\u30ea\\u30fc\\u30b0\"]],\n columns: [[\"number\", \"index\"], [\"string\", \"player\"], [\"number\", \"score\"], [\"number\", \"rank\"], [\"number\", \"year\"], [\"string\", \"league\"]],\n columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n rowsPerPage: 25,\n helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n suppressOutputScrolling: true,\n minimumWidth: undefined,\n });\n ",
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" <td>秋山 翔吾</td>\n",
" <td>0.359</td>\n",
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" <tr>\n",
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" <td>10</td>\n",
" <td>2020</td>\n",
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" <td>松本 剛</td>\n",
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],
"text/plain": [
" player score rank year league\n",
"166 柳田 悠岐 0.363 1 2015 パ・リーグ\n",
"167 秋山 翔吾 0.359 2 2015 パ・リーグ\n",
"330 柳田 悠岐 0.352 1 2018 パ・リーグ\n",
"450 吉田 正尚 0.350 1 2020 パ・リーグ\n",
"359 ビシエド 0.348 1 2018 セ・リーグ\n",
".. ... ... ... ... ...\n",
"204 マートン 0.276 9 2015 セ・リーグ\n",
"205 梶谷 隆幸 0.275 10 2015 セ・リーグ\n",
"459 大田 泰示 0.275 10 2020 パ・リーグ\n",
"284 松本 剛 0.274 10 2017 パ・リーグ\n",
"39 中村 紀洋 0.274 10 2012 セ・リーグ\n",
"\n",
"[180 rows x 5 columns]"
]
},
"metadata": {},
"execution_count": 9
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 265
},
"id": "RJXxDJ_pVX4i",
"outputId": "ef0e16be-dd62-4ec1-89f1-9d8b42415a21"
},
"source": [
"top_10_df['score'].plot.hist(bins=30)\n",
"plt.show()"
],
"execution_count": 10,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "1EATqpttV4IH",
"outputId": "3cb3bdf2-f1eb-418b-94d5-8b6e6a3828d0"
},
"source": [
"from scipy.stats import norm\n",
"\n",
"mean = top_10_df['score'].mean()\n",
"std = top_10_df['score'].std()\n",
"print(mean, std)\n",
"z = (0.400 - mean) / std\n",
"print(z)\n",
"(1 - norm.cdf(z)) * 100\n"
],
"execution_count": 11,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"0.3062944444444442 0.01851126705737676\n",
"5.062082204589775\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"2.0735106509572887e-05"
]
},
"metadata": {},
"execution_count": 11
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "e90ssfuhgOz9",
"outputId": "695d293a-fdd0-485a-a042-add28620f4f6"
},
"source": [
"2.0735106509572887e-05 > 0.0000207\n"
],
"execution_count": 12,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"True"
]
},
"metadata": {},
"execution_count": 12
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "BiPiGvBHaxkI"
},
"source": [
"def get_top_1_score_from_wikipedia():\n",
" url = 'https://ja.wikipedia.org/wiki/%E9%A6%96%E4%BD%8D%E6%89%93%E8%80%85_(%E6%97%A5%E6%9C%AC%E3%83%97%E3%83%AD%E9%87%8E%E7%90%83)'\n",
" res = requests.get(url)\n",
" res.encoding = res.apparent_encoding \n",
" body = res.text\n",
" soup = BeautifulSoup(body)\n",
" table = soup.select('table.wikitable')[1]\n",
" return [float(td.get_text()) for td in table.select('td') if td.get_text().strip().startswith('.')]\n",
"\n"
],
"execution_count": 13,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 640
},
"id": "mS3WmE9_fSTS",
"outputId": "eec8b812-7edd-4730-8837-f47f882d7756"
},
"source": [
"top_1_scores = get_top_1_score_from_wikipedia()\n",
"print(len(top_1_scores))\n",
"pd.DataFrame(top_1_scores).sort_values(0, ascending=False)"
],
"execution_count": 14,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"142\n"
]
},
{
"output_type": "execute_result",
"data": {
"application/vnd.google.colaboratory.module+javascript": "\n import \"https://ssl.gstatic.com/colaboratory/data_table/a6224c040fa35dcf/data_table.js\";\n\n window.createDataTable({\n data: [[{\n 'v': 72,\n 'f': \"72\",\n },\n{\n 'v': 0.389,\n 'f': \"0.389\",\n }],\n [{\n 'v': 101,\n 'f': \"101\",\n },\n{\n 'v': 0.387,\n 'f': \"0.387\",\n }],\n [{\n 'v': 89,\n 'f': \"89\",\n },\n{\n 'v': 0.385,\n 'f': \"0.385\",\n }],\n [{\n 'v': 3,\n 'f': \"3\",\n },\n{\n 'v': 0.383,\n 'f': \"0.383\",\n }],\n [{\n 'v': 41,\n 'f': \"41\",\n },\n{\n 'v': 0.383,\n 'f': \"0.383\",\n }],\n [{\n 'v': 116,\n 'f': \"116\",\n },\n{\n 'v': 0.378,\n 'f': \"0.378\",\n }],\n [{\n 'v': 78,\n 'f': \"78\",\n },\n{\n 'v': 0.378,\n 'f': \"0.378\",\n }],\n [{\n 'v': 2,\n 'f': \"2\",\n },\n{\n 'v': 0.377,\n 'f': \"0.377\",\n }],\n [{\n 'v': 25,\n 'f': \"25\",\n },\n{\n 'v': 0.374,\n 'f': \"0.374\",\n }],\n [{\n 'v': 98,\n 'f': \"98\",\n },\n{\n 'v': 0.369,\n 'f': \"0.369\",\n }],\n [{\n 'v': 60,\n 'f': \"60\",\n },\n{\n 'v': 0.369,\n 'f': \"0.369\",\n }],\n [{\n 'v': 71,\n 'f': \"71\",\n },\n{\n 'v': 0.367,\n 'f': \"0.367\",\n }],\n [{\n 'v': 75,\n 'f': \"75\",\n },\n{\n 'v': 0.366,\n 'f': \"0.366\",\n }],\n [{\n 'v': 29,\n 'f': \"29\",\n },\n{\n 'v': 0.366,\n 'f': \"0.366\",\n }],\n [{\n 'v': 59,\n 'f': \"59\",\n },\n{\n 'v': 0.364,\n 'f': \"0.364\",\n }],\n [{\n 'v': 131,\n 'f': \"131\",\n },\n{\n 'v': 0.363,\n 'f': \"0.363\",\n }],\n [{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0.362,\n 'f': \"0.362\",\n }],\n [{\n 'v': 8,\n 'f': \"8\",\n },\n{\n 'v': 0.361,\n 'f': \"0.361\",\n }],\n [{\n 'v': 73,\n 'f': \"73\",\n },\n{\n 'v': 0.36,\n 'f': \"0.36\",\n }],\n [{\n 'v': 107,\n 'f': \"107\",\n },\n{\n 'v': 0.36,\n 'f': \"0.36\",\n }],\n [{\n 'v': 109,\n 'f': \"109\",\n },\n{\n 'v': 0.358,\n 'f': \"0.358\",\n }],\n [{\n 'v': 61,\n 'f': \"61\",\n },\n{\n 'v': 0.358,\n 'f': \"0.358\",\n }],\n [{\n 'v': 45,\n 'f': \"45\",\n },\n{\n 'v': 0.358,\n 'f': \"0.358\",\n }],\n [{\n 'v': 54,\n 'f': \"54\",\n },\n{\n 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},
"metadata": {},
"execution_count": 14
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 265
},
"id": "pVa-AxQoQr4m",
"outputId": "f985850c-ff9a-460b-b6d4-3642c09ffe3d"
},
"source": [
"pd.Series(top_1_scores).plot.hist(bins=30)\n",
"plt.show()"
],
"execution_count": 17,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "-7gK6WuzcAVE",
"outputId": "305296ad-bf73-4d68-b62d-aa3a33e60a40"
},
"source": [
"top_1_series = pd.Series(top_1_scores)\n",
"\n",
"mean = top_1_series.mean()\n",
"std = top_1_series.std()\n",
"print(mean, std)\n",
"\n",
"z = (0.400 - mean) / std\n",
"print(z)\n",
"round((1 - norm.cdf(z)) * 100, 4)\n"
],
"execution_count": 18,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"0.3415774647887325 0.01713663238252034\n",
"3.4092191456974645\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"0.0326"
]
},
"metadata": {},
"execution_count": 18
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "998fITf6jBqd",
"outputId": "da5bcf34-125b-4dd4-b2a0-e06051529c11"
},
"source": [
"z = (0.390 - mean) / std\n",
"print(z)\n",
"round((1 - norm.cdf(z)) * 100, 4)\n"
],
"execution_count": 19,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2.8256739206624584\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"0.2359"
]
},
"metadata": {},
"execution_count": 19
}
]
}
]
}
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