[英]Extract words after a symbol in python
I have the following data where i would like to extract out source= from the values.我有以下数据,我想从这些数据中提取 source= 。 Is there a way to create a general regex function so that i can apply on other columns as well to extract words after equal sign?
有没有办法创建一个通用的正则表达式 function 以便我可以应用于其他列以及提取等号后的单词?
Data Data2
source=book social-media=facebook
source=book social-media=instagram
source=journal social-media=facebook
Im using python and i have tried the following:我正在使用 python 并且我尝试了以下操作:
df['Data'].astype(str).str.replace(r'[a-zA-Z]\=', '', regex=True)
but it didnt work但它没有用
you can try this:你可以试试这个:
df.replace(r'[a-zA-Z]+-?[a-zA-Z]+=', '', regex=True)
It gives you the following result:它给你以下结果:
Data Data2
0 book facebook
1 book instagram
2 journal facebook
Regex is not required in this situation:在这种情况下不需要正则表达式:
print(df['Data'].apply(lambda x : x.split('=')[-1]))
print(df['Data2'].apply(lambda x : x.split('=')[-1]))
You have to repeat the character class 1 or more times and you don't have to escape the equals sign.您必须重复字符 class 1 次或多次,并且不必转义等号。
What you can do is make the match a bit broader matching all characters except a whitespace char or an equals sign.您可以做的是使匹配更广泛一些,以匹配除空白字符或等号之外的所有字符。
Then set the result to the new value.然后将结果设置为新值。
import pandas as pd
data = [
"source=book",
"source=journal",
"social-media=facebook",
"social-media=instagram"
]
df = pd.DataFrame(data, columns=["Data"])
df['Data'] = df['Data'].astype(str).str.replace(r'[^\s=]+=', '', regex=True)
print(df)
Output Output
Data
0 book
1 journal
2 facebook
3 instagram
If there has to be a value after the equals sign, you can also use str.extract如果等号后面必须有一个值,你也可以使用 str.extract
df['Data'] = df['Data'].astype(str).str.extract(r'[^\s=]+=([^\s=]+)')
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