Add group indexers to pandas dataframe

Question

I have some data that looks something like this:

date_time, user, page
12345, A, index
13456, A, index
14566, B, home
...

I’d like to store the index of each row (i.e., its order when sorted by date_time), both overall, and per page.

Overall is simple. Just something like:

df['overall_count'] = range(len(df))

But I can’t figure out how to do it for the pages. The following code gets me what I want, but it’s connected to the groupby object, and I can’t figure out how to move it to the main dataframe.

grouped = df.groupby('page')
for name, group in grouped:
    group = group.sort_values('date_time')
    group['page_count'] = range(len(group))

Asked By: Jeremy

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Source

Answer 1

If you want to assign group-wise indices, you can use cumcount:

df.groupby('page').cumcount()

Answered By: ayhan

Add group indexers to pandas dataframe

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