ak.count_nonzero¶
Defined in awkward.operations.reducers on line 100.
- ak.count_nonzero(array, axis=None, keepdims=False, mask_identity=False)¶
- Parameters
array – Data in which to count nonzero elements.
axis (None or int) – If None, combine all values from the array into a single scalar result; if an int, group by that axis:
0
is the outermost,1
is the first level of nested lists, etc., and negativeaxis
counts from the innermost:-1
is the innermost,-2
is 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.
Counts nonzero elements of array
(many types supported, including all
Awkward Arrays and Records). The identity of counting is 0
and it is
usually not masked. This operation is the same as NumPy’s
count_nonzero
if all lists at a given dimension have the same length and no None values,
but it generalizes to cases where they do not.
See ak.sum
for a more complete description of nested list and missing
value (None) handling in reducers.
Following the same rules as other reducers, ak.count_nonzero
does not
count None values. If it is desirable to count them, use ak.fill_none
to turn them into something that would be counted.