numpy.nansum(a, axis=None, dtype=None, out=None, keepdims=<class numpy._globals._NoValue>)
[source]
Return the sum of array elements over a given axis treating Not a Numbers (NaNs) as zero.
In NumPy versions <= 1.8.0 Nan is returned for slices that are all-NaN or empty. In later versions zero is returned.
Parameters: |
a : array_like Array containing numbers whose sum is desired. If axis : int, optional Axis along which the sum is computed. The default is to compute the sum of the flattened array. dtype : data-type, optional The type of the returned array and of the accumulator in which the elements are summed. By default, the dtype of New in version 1.8.0. out : ndarray, optional Alternate output array in which to place the result. The default is New in version 1.8.0. 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 If the value is anything but the default, then New in version 1.8.0. |
---|---|
Returns: |
nansum : ndarray. A new array holding the result is returned unless |
See also
If both positive and negative infinity are present, the sum will be Not A Number (NaN).
>>> np.nansum(1) 1 >>> np.nansum([1]) 1 >>> np.nansum([1, np.nan]) 1.0 >>> a = np.array([[1, 1], [1, np.nan]]) >>> np.nansum(a) 3.0 >>> np.nansum(a, axis=0) array([ 2., 1.]) >>> np.nansum([1, np.nan, np.inf]) inf >>> np.nansum([1, np.nan, np.NINF]) -inf >>> np.nansum([1, np.nan, np.inf, -np.inf]) # both +/- infinity present nan
© 2008–2017 NumPy Developers
Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.nansum.html