pyspark.pandas.Index.symmetric_difference¶
-
Index.symmetric_difference(other: pyspark.pandas.indexes.base.Index, result_name: Union[Any, Tuple[Any, …], None] = None, sort: Optional[bool] = None) → pyspark.pandas.indexes.base.Index[source]¶ Compute the symmetric difference of two Index objects.
- Parameters
- otherIndex or array-like
- result_namestr
- sortTrue or None, default None
Whether to sort the resulting index. * True : Attempt to sort the result. * None : Do not sort the result.
- Returns
- symmetric_differenceIndex
Notes
symmetric_differencecontains elements that appear in eitheridx1oridx2but not both. Equivalent to the Index created byidx1.difference(idx2) | idx2.difference(idx1)with duplicates dropped.Examples
>>> s1 = ps.Series([1, 2, 3, 4], index=[1, 2, 3, 4]) >>> s2 = ps.Series([1, 2, 3, 4], index=[2, 3, 4, 5])
>>> s1.index.symmetric_difference(s2.index) Int64Index([5, 1], dtype='int64')
You can set name of result Index.
>>> s1.index.symmetric_difference(s2.index, result_name='pandas-on-Spark') Int64Index([5, 1], dtype='int64', name='pandas-on-Spark')
You can set sort to True, if you want to sort the resulting index.
>>> s1.index.symmetric_difference(s2.index, sort=True) Int64Index([1, 5], dtype='int64')
You can also use the
^operator:>>> s1.index ^ s2.index Int64Index([5, 1], dtype='int64')