ak.moment
=========

Defined in `awkward.operations.ak_moment <https://github.com/scikit-hep/awkward/blob/6549acea0193f5a82f58eedb62b9776ef3ec944b/src/awkward/operations/ak_moment.py>`__ on `line 26 <https://github.com/scikit-hep/awkward/blob/6549acea0193f5a82f58eedb62b9776ef3ec944b/src/awkward/operations/ak_moment.py#L26>`__.

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

   Computes the ``n``th moment over one or all levels of nesting.

   Many types are 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::

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

   :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; if a str, it is interpreted as the
                name of the axis which maps to an int if named axes are present.
                Named axes are attached to an array using :py:obj:`ak.with_named_axis` and
                removed with :py:obj:`ak.without_named_axis`; also see the
                `Named axes user guide <../../user-guide/how-to-array-properties-named-axis.html>`__.
   :type axis: None or int or str
   :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

   :returns: The ``n``th moment in each group of elements from ``x``.