Getting lists of indices from pandas dataframe

You want to get the index out for each group.

this is stored in the 'groups' attribute of a groupbydataframe.

#filter for coverage==True
#group by 'name'
#access the 'groups' attribute
by_person = df[df.coverage].groupby('name').groups

will return:

{'Jason': Int64Index([0, 5], dtype='int64'),
 'Tina': Int64Index([4], dtype='int64')}

From which you can access the individuals as you would a regular dictionary:

by_person['Jason']

returns:

Int64Index([0, 5], dtype='int64')

Which you can treat like a regular list.

This is doable, using boolean indexing first followed by the groupby:

In [942]: df[df.coverage].groupby('name').agg({'reports' : lambda x: list(x.index)})
Out[942]: 
      reports
name         
Jason  [0, 5]
Tina      [4]

You may use dfGroupBy.agg to get your output as a column of lists.

This should work:

  grouped=df.groupby('name').apply(lambda x: x.index[x.coverage].values)

output:

name
Jason    [0, 5]
Tina        [4]