pyspark.pandas.Index.dropna#

Index.dropna(how='any')[source]#

Return Index or MultiIndex without NA/NaN values

Parameters

how{‘any’, ‘all’}, default ‘any’: If the Index is a MultiIndex, drop the value when any or all levels are NaN.

Returns

Index or MultiIndex

Examples

>>> df = ps.DataFrame([[1, 2], [4, 5], [7, 8]],
...                   index=['cobra', 'viper', None],
...                   columns=['max_speed', 'shield'])
>>> df  
       max_speed  shield
cobra          1       2
viper          4       5
None           7       8

>>> df.index.dropna()
Index(['cobra', 'viper'], dtype='object')

Also support for MultiIndex

>>> tuples = [(np.nan, 1.0), (2.0, 2.0), (np.nan, np.nan), (3.0, np.nan)]
>>> midx = ps.MultiIndex.from_tuples(tuples)
>>> midx  
MultiIndex([(nan, 1.0),
            (2.0, 2.0),
            (nan, nan),
            (3.0, nan)],
           )

>>> midx.dropna()  
MultiIndex([(2.0, 2.0)],
           )

>>> midx.dropna(how="all")  
MultiIndex([(nan, 1.0),
            (2.0, 2.0),
            (3.0, nan)],
           )