pyspark.pandas.Index.take#
- Index.take(indices)#
Return the elements in the given positional indices along an axis.
This means that we are not indexing according to actual values in the index attribute of the object. We are indexing according to the actual position of the element in the object.
- Parameters
- indicesarray-like
An array of ints indicating which positions to take.
- Returns
- takensame type as caller
An array-like containing the elements taken from the object.
See also
DataFrame.locSelect a subset of a DataFrame by labels.
DataFrame.ilocSelect a subset of a DataFrame by positions.
numpy.takeTake elements from an array along an axis.
Examples
Series
>>> psser = ps.Series([100, 200, 300, 400, 500]) >>> psser 0 100 1 200 2 300 3 400 4 500 dtype: int64
>>> psser.take([0, 2, 4]).sort_index() 0 100 2 300 4 500 dtype: int64
Index
>>> psidx = ps.Index([100, 200, 300, 400, 500]) >>> psidx Index([100, 200, 300, 400, 500], dtype='int64')
>>> psidx.take([0, 2, 4]).sort_values() Index([100, 300, 500], dtype='int64')
MultiIndex
>>> psmidx = ps.MultiIndex.from_tuples([("x", "a"), ("x", "b"), ("x", "c")]) >>> psmidx MultiIndex([('x', 'a'), ('x', 'b'), ('x', 'c')], )
>>> psmidx.take([0, 2]) MultiIndex([('x', 'a'), ('x', 'c')], )