Function nanvar

numpy/lib/_nanfunctions_impl.py:1694–1874

Compute the variance along the specified axis, while ignoring NaNs. Returns the variance of the array elements, a measure of the spread of a distribution. The variance is computed for the flattened array by default, otherwise over the specified axis. For all-NaN slices or sli

(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue,
           *, where=np._NoValue, mean=np._NoValue, correction=np._NoValue)

@array_function_dispatch(_nanvar_dispatcher)
def nanvar(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue,
           *, where=np._NoValue, mean=np._NoValue, correction=np._NoValue):
    """
    Compute the variance along the specified axis, while ignoring NaNs.

    Returns the variance of the array elements, a measure of the spread of
    a distribution.  The variance is computed for the flattened array by
    default, otherwise over the specified axis.

    For all-NaN slices or slices with zero degrees of freedom, NaN is
    returned and a `RuntimeWarning` is raised.

    Parameters
    ----------
    a : array_like
        Array containing numbers whose variance is desired.  If `a` is not an
        array, a conversion is attempted.
    axis : {int, tuple of int, None}, optional
        Axis or axes along which the variance is computed.  The default is to compute
        the variance of the flattened array.
    dtype : data-type, optional
        Type to use in computing the variance.  For arrays of integer type
        the default is `float64`; for arrays of float types it is the same as
        the array type.
    out : ndarray, optional
        Alternate output array in which to place the result.  It must have
        the same shape as the expected output, but the type is cast if
        necessary.
    ddof : {int, float}, optional
        "Delta Degrees of Freedom": the divisor used in the calculation is
        ``N - ddof``, where ``N`` represents the number of non-NaN
        elements. By default `ddof` is zero.
    keepdims : bool, optional
        If this is set to True, the axes which are reduced are left
        in the result as dimensions with size one. With this option,
        the result will broadcast correctly against the original `a`.
    where : array_like of bool, optional
        Elements to include in the variance. See `~numpy.ufunc.reduce` for
        details.

        .. versionadded:: 1.22.0

    mean : array_like, optional
        Provide the mean to prevent its recalculation. The mean should have
        a shape as if it was calculated with ``keepdims=True``.
        The axis for the calculation of the mean should be the same as used in
        the call to this var function.

        .. versionadded:: 2.0.0

    correction : {int, float}, optional
        Array API compatible name for the ``ddof`` parameter. Only one of them
        can be provided at the same time.

        .. versionadded:: 2.0.0

    Returns
    -------