pyspark.pandas.Index.set_names¶

Index.set_names(names: Union[Any, Tuple[Any, …], List[Union[Any, Tuple[Any, …]]]], level: Union[int, Any, Tuple[Any, …], List[Union[int, Any, Tuple[Any, …]]], None] = None, inplace: bool = False) → Optional[pyspark.pandas.indexes.base.Index]¶

Set Index or MultiIndex name. Able to set new names partially and by level.

Parameters

nameslabel or list of label: Name(s) to set.
levelint, label or list of int or label, optional: If the index is a MultiIndex, level(s) to set (None for all levels). Otherwise level must be None.
inplacebool, default False: Modifies the object directly, instead of creating a new Index or MultiIndex.

Returns

Index: The same type as the caller or None if inplace is True.

See also

Index.rename: Able to set new names without level.

Examples

>>> idx = ps.Index([1, 2, 3, 4])
>>> idx
Int64Index([1, 2, 3, 4], dtype='int64')

>>> idx.set_names('quarter')
Int64Index([1, 2, 3, 4], dtype='int64', name='quarter')

For MultiIndex

>>> idx = ps.MultiIndex.from_tuples([('a', 'x'), ('b', 'y')])
>>> idx  
MultiIndex([('a', 'x'),
            ('b', 'y')],
           )

>>> idx.set_names(['kind', 'year'], inplace=True)
>>> idx  
MultiIndex([('a', 'x'),
            ('b', 'y')],
           names=['kind', 'year'])

>>> idx.set_names('species', level=0)  
MultiIndex([('a', 'x'),
            ('b', 'y')],
           names=['species', 'year'])

pyspark.pandas.Index.value_counts

pyspark.pandas.Index.droplevel