Pandas add grouping to each column

Question

I have a dataset that has one line per user per week that records whether or not the user has registered along with values of certain metrics:

cols = ["Worker ID", "Registered", "Week Ending", "Metric Value"]
rows = [
    ['A', True, '2022-08-06', 2],
    ['B', False, '2022-08-06', 3],
    ['C', False, '2022-08-06', 4],
    ['A', True, '2022-08-13', 3],
    ['B', False, '2022-08-13', 2],
    ['C', True, '2022-08-13', 5]
]

df = pd.DataFrame(columns=cols, data = rows)

I need to group by Week Ending and Registered and aggregate by number of unique worker ids and sum of the metrics. Normally this would be like this:

df.groupby(["Week Ending", "Registered"]).agg({'Worker ID': pd.Series.nunique, "Metric Value": sum})

This provides groupings as rows. I would like to have the registration group be along columns, something like:

Week Ending Date	Worker ID Reg True	Worker ID Reg False	Metric Value Reg True	Metric Value Reg False
2022-08-06	1	2	2	7
2022-08-13	2	1	8	2

Any ideas on how to do this?

Asked By: Raj

||

Source

Answer 1

Use unstack so:

df.groupby(["Week Ending", "Registered"]).agg({'Worker ID': pd.Series.nunique, "Metric Value": sum}).unstack()

Answered By: Panda Kim

Pandas add grouping to each column

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