nancumsum(a, axis=None, dtype=None)¶
- Return the cumulative sum of array elements over a given axis treating Not a
Numbers (NaNs) as zero. The cumulative sum does not change when NaNs are encountered and leading NaNs are replaced by zeros.
LAX-backend implementation of
nancumsum(). Original docstring below.
Zeros are returned for slices that are all-NaN or empty.
New in version 1.12.0.
a (array_like) – Input array.
axis (int, optional) – Axis along which the cumulative sum is computed. The default (None) is to compute the cumsum over the flattened array.
dtype (dtype, optional) – Type of the returned array and of the accumulator in which the elements are summed. If dtype is not specified, it defaults to the dtype of a, unless a has an integer dtype with a precision less than that of the default platform integer. In that case, the default platform integer is used.
nancumsum – A new array holding the result is returned unless out is specified, in which it is returned. The result has the same size as a, and the same shape as a if axis is not None or a is a 1-d array.
- Return type
>>> np.nancumsum(1) array() >>> np.nancumsum() array() >>> np.nancumsum([1, np.nan]) array([1., 1.]) >>> a = np.array([[1, 2], [3, np.nan]]) >>> np.nancumsum(a) array([1., 3., 6., 6.]) >>> np.nancumsum(a, axis=0) array([[1., 2.], [4., 2.]]) >>> np.nancumsum(a, axis=1) array([[1., 3.], [3., 3.]])