我正在嘗試通過使用 Python 3 進行網絡抓取，將本網站的表格轉換為 .csv 文件： 2011-2012 NBA National Schedule該表的開頭如下： Revised Schedule Original ScheduleDate Time Game Net Time Game NetSun., 12/25/11 12 PM BOS (1) at NY (1) TNT 12 PM BOS (7) at NY (7) ESPNSun., 12/25/11 2:30 PM MIA (1) at DAL (1) ABC 2:30 PM MIA (8) at DAL (5) ABCSun., 12/25/11 5 PM CHI (1) at LAL (1) ABC 5 PM CHI (6) at LAL (9) ABCSun., 12/25/11 8 PM ORL (1) at OKC (1) ESPN no game no game no gameSun., 12/25/11 10:30 PM LAC (1) at GS (1) ESPN no game no game no gameTue., 12/27/11 8 PM BOS (2) at MIA (2) TNT no game no game no gameTue., 12/27/11 10:30 PM UTA (1) at LAL (2) TNT no game no game no game我只對修訂后的時間表感興趣，即前 4 列。我想要的 .csv 文件中的輸出如下所示：我正在使用這些包：import reimport requestsimport pandas as pdimport numpy as npfrom bs4 import BeautifulSoupfrom itertools import groupby這是我為匹配我想要的格式所做的代碼：df = pd.read_html("https://www.sportsmediawatch.com/2011/12/revised-2011-12-nba-national-tv-schedule/", header=0)[0]revisedCols = ['Date'] + [ col for col in df.columns if 'Revised' in col ]df = df[revisedCols]df.columns = df.iloc[0,:]df = df.iloc[1:,:].reset_index(drop=True)# Format Date to m/d/ydf['Date'] = np.where(df.Date.str.startswith(('10/', '11/', '12/')), df.Date + ' 11', df.Date + ' 12')df['Date']=pd.to_datetime(df['Date'])df['Date']=df['Date'].dt.strftime('%m/%d/%Y')# Split the Game columndf[['Away','Home']] = df.Game.str.split('at',expand=True) # Final dataframe with desired columnsdf = df[['Date','Time','Away','Home','Net']]df.columns = ['Date', 'Time', 'Away', 'Home', 'Network']print(df)我注意到在“客場”和“主場”列中每個團隊名稱旁邊都有 (1)、(2) 等。我如何實施抓取程序以刪除“客場”和“主場”列中每個團隊名稱旁邊的 (1)、(2) 等？
4 回答
慕標5832272
TA貢獻1966條經驗 獲得超4個贊
您可以在拆分游戲列后添加此代碼
df['Away']=df['Away'].astype(str).str[0:-4] df['Home']=df['Home'].astype(str).str[0:-4]
Cats萌萌
TA貢獻1805條經驗 獲得超9個贊
df['Away'] = df['Away'].str.replace('\(\d*\)', '').str.strip()
df['Home'] = df['Home'].str.replace('\(\d*\)', '').str.strip()
print (df.head())
Date Time Away Home Network
0 12/25/2011 12 PM BOS NY TNT
1 12/25/2011 2:30 PM MIA DAL ABC
2 12/25/2011 5 PM CHI LAL ABC
3 12/25/2011 8 PM ORL OKC ESPN
4 12/25/2011 10:30 PM LAC GS ESPN
牛魔王的故事
TA貢獻1830條經驗 獲得超3個贊
不要在 ' 處拆分 Game 列'at，不要特別聲明分隔符。.split()將在每個空白處拆分，然后您只需要 0 索引和 3rd 索引值。所以真的只需要更改 1 行代碼：
從df[['Away','Home']] = df.Game.str.split('at',expand=True) 到df[['Away','Home']] = df.Game.str.split(expand=True)[[0,3]]
import pandas as pd
import numpy as np
df = pd.read_html("https://www.sportsmediawatch.com/2011/12/revised-2011-12-nba-national-tv-schedule/", header=0)[0]
revisedCols = ['Date'] + [ col for col in df.columns if 'Revised' in col ]
df = df[revisedCols]
df.columns = df.iloc[0,:]
df = df.iloc[1:,:].reset_index(drop=True)
# Format Date to m/d/y
df['Date'] = np.where(df.Date.str.startswith(('10/', '11/', '12/')), df.Date + ' 11', df.Date + ' 12')
df['Date']=pd.to_datetime(df['Date'])
df['Date']=df['Date'].dt.strftime('%m/%d/%Y')
# Split the Game column
df[['Away','Home']] = df.Game.str.split(expand=True)[[0,3]]
# Final dataframe with desired columns
df = df[['Date','Time','Away','Home','Net']]
df.columns = ['Date', 'Time', 'Away', 'Home', 'Network']
print(df)
斯蒂芬大帝
TA貢獻1827條經驗 獲得超8個贊
您可以使用str.replace括號和數字str.strip，而且似乎在開頭或結尾有一些空格：
df['Away'] = df['Away'].str.replace('\(\d*\)', '').str.strip()
df['Home'] = df['Home'].str.replace('\(\d*\)', '').str.strip()
print (df.head())
Date Time Away Home Network
0 12/25/2011 12 PM BOS NY TNT
1 12/25/2011 2:30 PM MIA DAL ABC
2 12/25/2011 5 PM CHI LAL ABC
3 12/25/2011 8 PM ORL OKC ESPN
4 12/25/2011 10:30 PM LAC GS ESPN
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