Groupby one column and count another column with a condition?

Question

I was wondering if it is possible to groupby one column while counting the values of another column that fulfill a condition. Because my dataset is a bit weird, I created a similar one:

import pandas as pd

raw_data = {'name': ['John', 'Paul', 'George', 'Emily', 'Jamie'], 
            'nationality': ['USA', 'USA', 'France', 'France', 'UK'],     
            'books': [0, 15, 0, 14, 40]}  
df = pd.DataFrame(raw_data, columns = ['name', 'nationality', 'books'])

Say, I want to groupby the nationality and count the number of people that don't have any books (books == 0) from that country.

I would therefore expect something like the following as output:

nationality
USA      1
France   1
UK       0

I tried most variations of groupby, using filter, agg but don't seem to get anything that works.

Thanks in advance, BBQuercus :)

Answer 1

IIUC:

df.books.eq(0).astype(int).groupby(df.nationality).sum()

nationality
France    1
UK        0
USA       1
Name: books, dtype: int64