79 lines
2.2 KiB
Python
79 lines
2.2 KiB
Python
import requests
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from lxml import etree
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import pandas as pd
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import matplotlib.pyplot as plt
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url = f'https://www.transfermarkt.com/manchester-city/leistungsdaten/verein/281/plus/1?reldata=%262023'
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myheader = {'user-agent': 'Chrome'}
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response = requests.get(url, headers=myheader)
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# response.encoding = 'utf-8'
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html = response.content
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tree = etree.HTML(html)
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players = tree.xpath('//tbody/tr')
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# 提取数据
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player_data = []
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for player in players:
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# 提取球员名字
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name = player.xpath('.//img/@title')
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name = name[0] if name else None
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# 提取 PPG
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ppg = player.xpath('.//td[contains(@class, "cp")]/text()')
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ppg = ppg[0] if ppg else None
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ppg = eval(str(ppg))
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# 去掉未出场的球员
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if ppg == 0:
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continue
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# 提取出场时间
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playing_time = player.xpath('.//td[contains(@class, "rechts")]/text()')
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playing_time = playing_time[0].replace('.', '').strip("'") if playing_time else None
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playing_time = eval(str(playing_time))
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# 如果 PPG 或出场时间缺失，跳过该球员
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if name and ppg and playing_time:
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player_data.append({
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"name": name,
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"PPG": ppg,
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"playing_time": playing_time
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})
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# 将数据存储到 DataFrame
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df = pd.DataFrame(player_data)
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# 添加 "Matches" 列，出场时间除以 90，保留两位小数
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df['Matches'] = (df['playing_time'] / 90).round(2)
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# 输出结果
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print(df)
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# 绘制散点图
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plt.figure(figsize=(8, 6))
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plt.scatter(df['Matches'], df['PPG'], color='blue', label='Player Data')
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# 添加球员名字标注
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for i, row in df.iterrows():
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plt.text(row['Matches'], row['PPG'], row['name'], fontsize=9, ha='right', va='bottom')
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# 添加分割线
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split_x = 30
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split_y = 2.37
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plt.axhline(y=split_y, color='red', linestyle='--', linewidth=1.5, label='PPG Split (2.13)')
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plt.axvline(x=split_x, color='green', linestyle='--', linewidth=1.5, label='Matches Split (30)')
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# 设置标题和标签
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plt.title("Scatter Plot with Player Names and Splitting Lines", fontsize=14)
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plt.xlabel("Matches (Games Played)", fontsize=12)
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plt.ylabel("PPG (Points Per Game)", fontsize=12)
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# 添加网格
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plt.grid(alpha=0.3)
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# 添加图例
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plt.legend()
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# 显示图形
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plt.show()
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