Series.
take
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.
An array of ints indicating which positions to take.
An array-like containing the elements taken from the object.
See also
DataFrame.loc
Select a subset of a DataFrame by labels.
DataFrame.iloc
Select a subset of a DataFrame by positions.
numpy.take
Take 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 Int64Index([100, 200, 300, 400, 500], dtype='int64')
>>> psidx.take([0, 2, 4]).sort_values() Int64Index([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')], )