ak.count_nonzero — Awkward Array documentation

# ak.count_nonzero

Defined in awkward.operations.reducers on line 101.

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 negative `axis` 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.