Count unique values using pandas groupby
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
This is just an add-on to the solution in case you want to compute not only unique values but other aggregate functions:
df.groupby(['group']).agg(['min', 'max', 'count', 'nunique'])