ak.unzip#

Defined in awkward.operations.ak_unzip on line 16.

ak.unzip(array, *, how=tuple, highlevel=True, behavior=None, attrs=None)#

Parameters:

array – Array-like data (anything ak.to_layout recognizes).
how (type) – The type of the returned output. This can be tuple or dict.
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.

If the array contains tuples or records, this operation splits them into a Python tuple (or dict) of arrays, one for each field.

If the array does not contain tuples or records, the single array is placed in a length 1 Python tuple (or dict).

For example,

>>> array = ak.Array([{"x": 1.1, "y": [1]},
...                   {"x": 2.2, "y": [2, 2]},
...                   {"x": 3.3, "y": [3, 3, 3]}])
>>> x, y = ak.unzip(array)
>>> x
<Array [1.1, 2.2, 3.3] type='3 * float64'>
>>> y
<Array [[1], [2, 2], [3, 3, 3]] type='3 * var * int64'>

The how argument determines the structure of the output. Using how=dict returns a dictionary of arrays instead of a tuple, and let’s you round-trip through ak.zip:

>>> array = ak.Array([{"x": 1.1, "y": [1]},
...                   {"x": 2.2, "y": [2, 2]},
...                   {"x": 3.3, "y": [3, 3, 3]}])
>>> x = ak.unzip(array, how=dict)
>>> x
{'x': <Array [1.1, 2.2, 3.3] type='3 * float64'>,
 'y': <Array [[1], [2, 2], [3, 3, 3]] type='3 * var * int64'>}
>>> assert ak.zip(ak.unzip(array, how=dict), depth_limit=1).to_list() == array.to_list()  # True

ak.unzip#

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