Pandas DataFrame aggregate function using multiple columns

by

Yes; use the .apply(...) function, which will be called on each sub-DataFrame. For example:

grouped = df.groupby(keys)

def wavg(group):
    d = group['data']
    w = group['weights']
    return (d * w).sum() / w.sum()

grouped.apply(wavg)

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