在使用Python进行web抓取时，如何删除pandas数据框中的字符？

Question

我正在尝试使用Python 3将此网站的一个表从web上刮取到一个.csv文件中： 2011-2012 NBA National Schedule

表格开始时如下所示：

                Revised Schedule                    Original Schedule

Date            Time      Game                Net   Time      Game                  Net
Sun., 12/25/11  12 PM     BOS (1) at NY (1)   TNT   12 PM     BOS (7) at NY (7)     ESPN
Sun., 12/25/11  2:30 PM   MIA (1) at DAL (1)  ABC   2:30 PM   MIA (8) at DAL (5)    ABC
Sun., 12/25/11  5 PM      CHI (1) at LAL (1)  ABC   5 PM      CHI (6) at LAL (9)    ABC
Sun., 12/25/11  8 PM      ORL (1) at OKC (1)  ESPN  no game   no game               no game
Sun., 12/25/11  10:30 PM  LAC (1) at GS (1)   ESPN  no game   no game               no game
Tue., 12/27/11  8 PM      BOS (2) at MIA (2)  TNT   no game   no game               no game
Tue., 12/27/11  10:30 PM  UTA (1) at LAL (2)  TNT   no game   no game               no game

我只对修订后的附表感兴趣，它是前4栏。我希望.csv文件中的输出如下所示：

我正在使用这些软件包：

import re
import requests
import pandas as pd
import numpy as np
from bs4 import BeautifulSoup
from itertools import groupby

这是我为匹配所需格式而编写的代码：

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('at',expand=True)   


# Final dataframe with desired columns
df = df[['Date','Time','Away','Home','Net']]

df.columns = ['Date', 'Time', 'Away', 'Home', 'Network']

print(df)

输出：

           Date      Time      Away        Home Network
0    12/25/2011     12 PM   BOS (1)      NY (1)     TNT
1    12/25/2011   2:30 PM   MIA (1)     DAL (1)     ABC
2    12/25/2011      5 PM   CHI (1)     LAL (1)     ABC
3    12/25/2011      8 PM   ORL (1)     OKC (1)    ESPN
4    12/25/2011  10:30 PM   LAC (1)      GS (1)    ESPN
5    12/27/2011      8 PM   BOS (2)     MIA (2)     TNT
6    12/27/2011  10:30 PM   UTA (1)     LAL (2)     TNT

我注意到在客场和主场栏中，每个队名旁边都有（1）、（2）等如何使用刮刀删除客场和主场列中每个球队名称旁边的（1）、（2）等？

Answer 1

可以将^{}与括号和数字一起使用，也可以使用^{}因为开头或结尾似乎有一些空格：

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

Answer 2

您可以在拆分游戏列后添加此代码

df['Away']=df['Away'].astype(str).str[0:-4]
df['Home']=df['Home'].astype(str).str[0:-4]

Answer 3

import re
import numpy as np
import pandas as pd

dataset = pd.read_csv("Dataset.csv")
dataset.rename(columns={'Country(or dependent territory)': 'Country'}, inplace = True)
dataset.rename(columns={'% of worldpopulation': 'Percentage of World Population'}, inplace = True)
dataset.rename(columns={'Total Area': 'Total Area (km2)'}, inplace = True)