- ak.any(array, axis=None, *, keepdims=False, mask_identity=False, flatten_records=unset, highlevel=True, behavior=None)#
array – Array-like data (anything
axis (None or int) – If None, combine all values from the array into a single scalar result; if an int, group by that axis:
0is the outermost,
1is the first level of nested lists, etc., and negative
axiscounts from the innermost:
-1is the innermost,
-2is the next level up, etc.
keepdims (bool) – If False, this reducer decreases the number of dimensions by 1; if True, the reduced values are wrapped in a new length-1 dimension so that the result of this operation may be broadcasted with the original array.
mask_identity (bool) – If True, reducing over empty lists results in None (an option type); otherwise, reducing over empty lists results in the operation’s identity.
Returns True in each group of elements from
array (many types supported,
including all Awkward Arrays and Records) if any values are True; False
otherwise. Thus, it represents reduction over the “logical or” operation,
whose identity is False (i.e. asking if there are any True values in an
empty list results in False). This operation is the same as NumPy’s
if all lists at a given dimension have the same length and no None values,
but it generalizes to cases where they do not.
ak.sum for a more complete description of nested list and missing
value (None) handling in reducers.