[FIXED] Random sampling of groups after pandas groupby

Issue

I have a large dataframe that looks like this:

Nationality	Sex	Response
American	Female	I have no need for this product.
German	Male	It looks great.
Finnish	Female	I would definitely buy one.

etc.

What I want to do is to randomly select a number of responses from each group so that I can analyse them further.

My groupby function has returned something like this:

Nationality Sex
American    Male    567
American    Female  342
German      Male    421
German      Female  234
Finnish     Male    149
Finnish     Female  67

etc.

I want to have a new dataframe with 20 random responses of each group. Is that possible using lambda? Because new_df = df.groupby('Nationality')['Sex'].apply(lambda x: x.sample(20)) doesn't return what I am looking for. Is there a way to do this?

Solution

Using iterrows from Pandas you can iterate over DataFrame rows as (index, Series) pairs, and get what you want:

new_df = df.groupby(['Nationality', 'Sex'], as_index=False).size()

for _, row in new_df.iterrows():
    print(df[(df.Nationality==row.Nationality)&(df.Sex==row.Sex)].sample(20))

Answered By - Renato Aranha