ak.moment
---------

.. py:module: ak.moment

Defined in `awkward.operations.ak_moment <https://github.com/scikit-hep/awkward/blob/36da52cfa8846355c390beb6555eac1d31c27c26/src/awkward/operations/ak_moment.py>`__ on `line 26 <https://github.com/scikit-hep/awkward/blob/36da52cfa8846355c390beb6555eac1d31c27c26/src/awkward/operations/ak_moment.py#L26>`__.

.. py:function:: ak.moment(x, n, weight=None, axis=None, *, keepdims=False, mask_identity=False, highlevel=True, behavior=None, attrs=None)


    :param x: The data on which to compute the moment (anything :py:obj:`ak.to_layout` recognizes).
    :param n: The choice of moment: ``0`` is a sum of weights, ``1`` is
          :py:obj:`ak.mean`, ``2`` is :py:obj:`ak.var` without subtracting the mean, etc.
    :type n: int
    :param weight: Data that can be broadcasted to ``x`` to give each value a
               weight. Weighting values equally is the same as no weights;
               weighting some values higher increases the significance of those
               values. Weights can be zero or negative.
    :param axis: 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.
    :type axis: None or int
    :param keepdims: If False, this function decreases the number of
                 dimensions by 1; if True, the output values are wrapped in a new
                 length-1 dimension so that the result of this operation may be
                 broadcasted with the original array.
    :type keepdims: bool
    :param mask_identity: If True, the application of this function on
                      empty lists results in None (an option type); otherwise, the
                      calculation is followed through with the reducers' identities,
                      usually resulting in floating-point ``nan``.
    :type mask_identity: bool
    :param highlevel: If True, return an :py:obj:`ak.Array`; otherwise, return
                  a low-level :py:obj:`ak.contents.Content` subclass.
    :type highlevel: bool
    :param behavior: Custom :py:obj:`ak.behavior` for the output array, if
                 high-level.
    :type behavior: None or dict
    :param attrs: Custom attributes for the output array, if
              high-level.
    :type attrs: None or dict

Computes the ``n``th moment in each group of elements from ``x`` (many
types supported, including all Awkward Arrays and Records). The grouping
is performed the same way as for reducers, though this operation is not a
reducer and has no identity.

This function has no NumPy equivalent.

Passing all arguments to the reducers, the moment is calculated as

.. code-block:: python


    ak.sum((x*weight)**n) / ak.sum(weight)

The ``n=2`` moment differs from :py:obj:`ak.var` in that :py:obj:`ak.var` also subtracts the
mean (the ``n=1`` moment).

See :py:obj:`ak.sum` for a complete description of handling nested lists and
missing values (None) in reducers, and :py:obj:`ak.mean` for an example with another
non-reducer.