从不同的GroupBy组中选择不同的行

Question

As opposed to GroupBy.nth , which selects the same index for each group, I would like to take specific indices from each group. For example, if my GroupBy object consisted of four groups and I would like the 1st, 5th, 10th, and 15th from each respectively, then I would like to be able to pass x = [0, 4, 9, 14] and get those rows.

Answer 1

This is kind of a strange thing to want; is there a reason?

In any case, to do what you want, try this:

df = pd.DataFrame([['a', 1], ['a', 2], 
                   ['b', 3], ['b', 4], ['b', 5], 
                   ['c', 6], ['c', 7]], 
                  columns=['group', 'value'])

def index_getter(which):
    def get(series):
        return series.iloc[which[series.name]]
    return get

which = {'a': 0, 'b': 2, 'c': 1}

df.groupby('group')['value'].apply(index_getter(which))

Which results in:

group
a    1
b    5
c    7