ak.argsort#

Defined in awkward.operations.ak_argsort on line 22.

ak.argsort(array, axis=-1, *, ascending=True, stable=True, highlevel=True, behavior=None, attrs=None)#

Parameters:

array – Array-like data (anything ak.to_layout recognizes).
axis (int) – The dimension at which this operation is applied. The outermost dimension is 0, followed by 1, etc., and negative values count backward from the innermost: -1 is the innermost dimension, -2 is the next level up, etc.
ascending (bool) – If True, the first value in each sorted group will be smallest, the last value largest; if False, the order is from largest to smallest.
stable (bool) – If True, use a stable sorting algorithm; if False, use a sorting algorithm that is not guaranteed to be stable.
highlevel (bool) – If True, return an ak.Array; otherwise, return a low-level ak.contents.Content subclass.
behavior (None or dict) – Custom ak.behavior for the output array, if high-level.
attrs (None or dict) – Custom attributes for the output array, if high-level.

Returns an array of integer indexes that would sort the array if applied as an integer-array slice.

For example,

>>> ak.argsort(ak.Array([[7.7, 5.5, 7.7], [], [2.2], [8.8, 2.2]]))
<Array [[1, 0, 2], [], [0], [1, 0]] type='4 * var * int64'>

The result of this function can be used to index other arrays with the same shape:

>>> data = ak.Array([[7, 5, 7], [], [2], [8, 2]])
>>> index = ak.argsort(data)
>>> index
<Array [[1, 0, 2], [], [0], [1, 0]] type='4 * var * int64'>
>>> data[index]
<Array [[5, 7, 7], [], [2], [2, 8]] type='4 * var * int64'>