ak.num — Awkward Array documentation

# ak.num

Defined in awkward.operations.structure on line 187.

ak.num(array, axis=1, highlevel=True, behavior=None)
  Parameters:

    - array – Data containing nested lists to count.

    - 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.

    - highlevel (bool) – If True, return an `ak.Array`; otherwise, return a low-level `ak.layout.Content` subclass.

    - behavior (None or dict) – Custom `ak.behavior` for the output array, if high-level.

Returns an array of integers specifying the number of elements at a particular level.

For instance, given the following doubly nested `array`,

    ak.Array([[
               [1.1, 2.2, 3.3],
               [],
               [4.4, 5.5],
               [6.6]
              ],
              [],
              [
               [7.7],
               [8.8, 9.9]]
              ])

The number of elements in `axis=1` is

    >>> ak.num(array, axis=1)
    <Array [4, 0, 2] type='3 * int64'>

and the number of elements at the next level down, `axis=2`, is

    >>> ak.num(array, axis=2)
    <Array [[3, 0, 2, 1], [], [1, 2]] type='3 * var * int64'>

The `axis=0` case is special: it returns a scalar, the length of the array.

    >>> ak.num(array, axis=0)
    3

This function is useful for ensuring that slices do not raise errors. For instance, suppose that we want to select the first element from each of the outermost nested lists of `array`. One of these lists is empty, so selecting the first element (`0`) would raise an error. However, if our first selection is `ak.num(array) > 0`, we are left with only those lists that do have a first element:

    >>> array[ak.num(array) > 0, 0]
    <Array [[1.1, 2.2, 3.3], [7.7]] type='2 * var * float64'>

To keep a placeholder (None) in each place we do not want to select, consider using `ak.mask` instead of a `ak.Array.__getitem__`.

    >>> ak.mask(array, ak.num(array) > 0)[:, 0]
    <Array [[1.1, 2.2, 3.3], None, [7.7]] type='3 * option[var * float64]'>