Python 在dataframe中查找模式并进行替换

我试图在数据帧中查找模式并进行替换

我正在寻找的一个模式示例：

[不是]+[任何东西]+[更多]

不再（不再=>模式）=>不再

数据：

0    can seem form something like coherent...
1    not any more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

df['Data'] = df['Data'].str.replace(r'(not|no)(\s)(\w)(\s)(more)', '\1_\3_\5')

0    can seem form something like coherent...
1    not any more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

0    can seem form something like coherent...
1    not_any_more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

我试过：

0    can seem form something like coherent...
1    not any more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

df['Data'] = df['Data'].str.replace(r'(not|no)(\s)(\w)(\s)(more)', '\1_\3_\5')

0    can seem form something like coherent...
1    not any more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

0    can seem form something like coherent...
1    not_any_more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

我的输出：

0    can seem form something like coherent...
1    not any more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

df['Data'] = df['Data'].str.replace(r'(not|no)(\s)(\w)(\s)(more)', '\1_\3_\5')

0    can seem form something like coherent...
1    not any more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

0    can seem form something like coherent...
1    not_any_more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

输出良好：

0    can seem form something like coherent...
1    not any more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

df['Data'] = df['Data'].str.replace(r'(not|no)(\s)(\w)(\s)(more)', '\1_\3_\5')

0    can seem form something like coherent...
1    not any more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

0    can seem form something like coherent...
1    not_any_more...
2    is unclear any better deal...
3    Peter won’t start if you don’t sit...
4    is unclear basic conditions any...
Name: Data, dtype: object

---

您的代码中有两个小错误。您需要将

\w

更改为

\w+

，并将替换模式设置为原始字符串

如果没有加号，

\w

将只匹配一个字符

print(df['Data'].str.replace(r'(not|no)(\s)(\w+)(\s)(more)', r'\1_\3_\5'))
#0    can seem form something like coherent...
#1                             not_any_more...
#2               is unclear any better deal...
#3       Peter won’t start if you don’t sit...
#4          is unclear basic conditions any...
#Name: Data, dtype: object

---

您的代码中有两个小错误。您需要将

\w

更改为

\w+

，并将替换模式设置为原始字符串

如果没有加号，

\w

将只匹配一个字符

print(df['Data'].str.replace(r'(not|no)(\s)(\w+)(\s)(more)', r'\1_\3_\5'))
#0    can seem form something like coherent...
#1                             not_any_more...
#2               is unclear any better deal...
#3       Peter won’t start if you don’t sit...
#4          is unclear basic conditions any...
#Name: Data, dtype: object