Count unique values using pandas groupby

Question

I have data of the following form:

df = pd.DataFrame({
    \'group\': [1, 1, 2, 3, 3, 3, 4],
    \'param\': [\'a\', \'a\', \'b\', np.nan, \'a\', \'a\', np.na         


        

Answer 1

I think you can use SeriesGroupBy.nunique:

print (df.groupby('param')['group'].nunique())
param
a    2
b    1
Name: group, dtype: int64

Another solution with unique, then create new df by DataFrame.from_records, reshape to Series by stack and last value_counts:

a = df[df.param.notnull()].groupby('group')['param'].unique()
print (pd.DataFrame.from_records(a.values.tolist()).stack().value_counts())
a    2
b    1
dtype: int64