I have the following data where i would like to extract out source= from the values. 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?
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:
df['Data'].astype(str).str.replace(r'[a-zA-Z]\=', '', regex=True)
but it didnt work
you can try this:
df.replace(r'[a-zA-Z]+-?[a-zA-Z]+=', '', regex=True)
It gives you the following result:
Data Data2
0 book facebook
1 book instagram
2 journal facebook
Regex is not required in this situation:
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.
What you can do is make the match a bit broader matching all characters except a whitespace char or an equals sign.
Then set the result to the new value.
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
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
df['Data'] = df['Data'].astype(str).str.extract(r'[^\s=]+=([^\s=]+)')
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