pandas.core.groupby.SeriesGroupBy.nunique#

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

Return number of unique elements in the group.

Returns:

Series: Number of unique values within each group.

Examples

For SeriesGroupby:

>>> lst = ['a', 'a', 'b', 'b']
>>> ser = pd.Series([1, 2, 3, 3], index=lst)
>>> ser
a    1
a    2
b    3
b    3
dtype: int64
>>> ser.groupby(level=0).nunique()
a    2
b    1
dtype: int64

For Resampler:

>>> ser = pd.Series([1, 2, 3, 3], index=pd.DatetimeIndex(
...                 ['2023-01-01', '2023-01-15', '2023-02-01', '2023-02-15']))
>>> ser
2023-01-01    1
2023-01-15    2
2023-02-01    3
2023-02-15    3
dtype: int64
>>> ser.resample('MS').nunique()
2023-01-01    2
2023-02-01    1
Freq: MS, dtype: int64