How to parse from one column to create another with Pandas and Regex?

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I have a pd dataframe with one column user_id and each row ends with "/tgroup..."

I want to create a new column group_id where each row will have the corresponding "tgroup..." matching user_id.

This is my implementation so far:

                                         user_id
0  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-0
1  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-1
2  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-2
3  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-3
4  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-4


df['group_id'] = df['user_id'].apply(lambda x: re.findall('(^\t)',x))

print(df.head())

                                         user_id group_id
0  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-0       []
1  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-1       []
2  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-2       []
3  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-3       []
4  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-4       []

Clearly lambda/regex method is not grabbing the string selection that I want.

Any ideas?

pandas python
1 Answers

is \t the tab character or backslash and t? If the latter you can try:

df['group_id'] = df.user_id.str.extract(r'\\t(.*)')

Output:

                                         user_id group_id
0  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-0  group-0
1  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-1  group-1
2  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-2  group-2
3  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-3  group-3
4  87dce49a-f752-47f8-9bc4-b97a446a85f5\tgroup-4  group-4
user_42384080
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