xorbits.pandas.Index.join#

final Index.join(other: Index, *, how: JoinHow = 'left', level: Level = None, return_indexers: Literal[True], sort: bool = False) → tuple[Index, npt.NDArray[np.intp] | None, npt.NDArray[np.intp] | None][source]#
final Index.join(other: Index, *, how: JoinHow = 'left', level: Level = None, return_indexers: Literal[False] = False, sort: bool = False) → Index
final Index.join(other: Index, *, how: JoinHow = 'left', level: Level = None, return_indexers: bool = False, sort: bool = False) → Index | tuple[Index, npt.NDArray[np.intp] | None, npt.NDArray[np.intp] | None]

Compute join_index and indexers to conform data structures to the new index.

Parameters

  • other (Index) –

  • how ({'left', 'right', 'inner', 'outer'}) –

  • level (int or level name, default None) –

  • return_indexers (bool, default False) –

  • sort (bool, default False) – Sort the join keys lexicographically in the result Index. If False, the order of the join keys depends on the join type (how keyword).

Return type

join_index, (left_indexer, right_indexer)

Examples

>>> idx1 = pd.Index([1, 2, 3])  
>>> idx2 = pd.Index([4, 5, 6])  
>>> idx1.join(idx2, how='outer')  
Index([1, 2, 3, 4, 5, 6], dtype='int64')

Warning

This method has not been implemented yet. Xorbits will try to execute it with pandas.

This docstring was copied from pandas.core.indexes.base.Index.