DataFrameGroupBy.nunique(self, dropna=True) [source]
Return DataFrame with number of distinct observations per group for each column.
New in version 0.20.0.
| Parameters: |
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| Returns: |
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>>> df = pd.DataFrame({'id': ['spam', 'egg', 'egg', 'spam',
... 'ham', 'ham'],
... 'value1': [1, 5, 5, 2, 5, 5],
... 'value2': list('abbaxy')})
>>> 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()
id value1 value2
id
egg 1 1 1
ham 1 1 2
spam 1 2 1
Check for rows with the same id but conflicting values:
>>> df.groupby('id').filter(lambda g: (g.nunique() > 1).any())
id value1 value2
0 spam 1 a
3 spam 2 a
4 ham 5 x
5 ham 5 y
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.core.groupby.DataFrameGroupBy.nunique.html