def nunique(self, axis=<NUM_LIT:0>, dropna=True):
return self.apply(Series.nunique, axis=axis, dropna=dropna)<EOL>
Count distinct observations over requested axis.

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

.. versionadded:: 0.20.0

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.
dropna : bool, 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': [1, 2, 3], 'B': [1, 1, 1]})
>>> df.nunique()
A    3
B    1
dtype: int64

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