BPt.Dataset.nunique#

Dataset.nunique(axis=0, dropna=True)[source]#

Count number of distinct elements in specified axis.

Return Series with number of distinct elements. Can ignore NaN values.

Parameters
axis{0 or ‘index’, 1 or ‘columns’}, default 0

The axis to use. 0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise.

dropnabool, default True

Don’t include NaN in the counts.

Returns
Series

See also

Series.nunique

Method nunique for Series.

DataFrame.count

Count non-NA cells for each column or row.

Examples

>>> df = pd.DataFrame({'A': [4, 5, 6], 'B': [4, 1, 1]})
>>> df.nunique()
A    3
B    2
dtype: int64

>>> df.nunique(axis=1)
0    1
1    2
2    2
dtype: int64