Converting a named aggregate prior to pandas/python3

Tags: ,

For the below:

summary_df = (df
    .groupby(['provider', 'master_id'])
        content_type_id             =('content_type_id', 'first'),
        title                       =('title', 'first'),
        release_year                =('release_year', 'first'), ...
        subs                        =('burned_in_sub_language', lambda x: str(sorted(i.lower() for i in x.dropna().unique())))

What would be the proper way to do this before named aggregates were introduced, including the aliasing of columns?


As mentioned by Henry Yik, use .agg() followed by .rename().
For example:

summary_df = (df
    .groupby(['provider', 'master_id'])
    .agg({'content_type_id':'first', 'title': 'first',})
        'content_type_id': 'something else', 
        'title': 'changed_name',})

Source: stackoverflow