ak.nanstd
---------

.. py:module: ak.nanstd

Defined in `awkward.operations.ak_std <https://github.com/scikit-hep/awkward/blob/36da52cfa8846355c390beb6555eac1d31c27c26/src/awkward/operations/ak_std.py>`__ on `line 100 <https://github.com/scikit-hep/awkward/blob/36da52cfa8846355c390beb6555eac1d31c27c26/src/awkward/operations/ak_std.py#L100>`__.

.. py:function:: ak.nanstd(x, weight=None, ddof=0, axis=None, *, keepdims=False, mask_identity=True, highlevel=True, behavior=None, attrs=None)


    :param x: The data on which to compute the standard deviation (anything :py:obj:`ak.to_layout` recognizes).
    :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 ddof: "delta degrees of freedom": the divisor used in the
             calculation is ``sum(weights) - ddof``. Use this for "reduced
             standard deviation."
    :type ddof: int
    :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

Like :py:obj:`ak.std`, but treating NaN ("not a number") values as missing.

Equivalent to

.. code-block:: python


    ak.std(ak.nan_to_none(array))

with all other arguments unchanged.

See also :py:obj:`ak.std`.