pyspark.pandas.groupby.GroupBy.nunique#

GroupBy.nunique(dropna=True)[source]#

Return DataFrame with number of distinct observations per group for each column.

Parameters

dropnaboolean, default True: Don’t include NaN in the counts.

Returns

nuniqueDataFrame or Series

Examples

>>> df = ps.DataFrame({'id': ['spam', 'egg', 'egg', 'spam',
...                           'ham', 'ham'],
...                    'value1': [1, 5, 5, 2, 5, 5],
...                    'value2': list('abbaxy')}, columns=['id', 'value1', 'value2'])
>>> df
     id  value1 value2
0  spam       1      a
1   egg       5      b
2   egg       5      b
3  spam       2      a
4   ham       5      x
5   ham       5      y

>>> df.groupby('id').nunique().sort_index() 
      value1  value2
id
egg        1       1
ham        1       2
spam       2       1

>>> df.groupby('id')['value1'].nunique().sort_index() 
id
egg     1
ham     1
spam    2
Name: value1, dtype: int64