pyspark.pandas.Index.map

Index.map(mapper: Union[dict, Callable[[Any], Any], pandas.core.series.Series], na_action: Optional[str] = None) → pyspark.pandas.indexes.base.Index

Map values using input correspondence (a dict, Series, or function).

Parameters

mapperfunction, dict, or pd.Series

Mapping correspondence.

na_action{None, ‘ignore’}

If ‘ignore’, propagate NA values, without passing them to the mapping correspondence.

Returns

appliedIndex, inferred

The output of the mapping function applied to the index.

Examples

>>> psidx = ps.Index([1, 2, 3])

>>> psidx.map({1: "one", 2: "two", 3: "three"})
Index(['one', 'two', 'three'], dtype='object')

>>> psidx.map(lambda id: "{id} + 1".format(id=id))
Index(['1 + 1', '2 + 1', '3 + 1'], dtype='object')

>>> pser = pd.Series(["one", "two", "three"], index=[1, 2, 3])
>>> psidx.map(pser)
Index(['one', 'two', 'three'], dtype='object')

pyspark.pandas.Index.max pyspark.pandas.Index.rename