numpy.nancumsum#
- numpy.nancumsum(a,axis=None,dtype=None,out=None)[source]#
Return the cumulative sum of array elements over a given axis treating Not aNumbers (NaNs) as zero. The cumulative sum does not change when NaNs areencountered and leading NaNs are replaced by zeros.
Zeros are returned for slices that are all-NaN or empty.
- Parameters:
- aarray_like
Input array.
- axisint, optional
Axis along which the cumulative sum is computed. The default(None) is to compute the cumsum over the flattened array.
- dtypedtype, optional
Type of the returned array and of the accumulator in which theelements are summed. If
dtypeis not specified, it defaultsto the dtype ofa, unlessa has an integer dtype with aprecision less than that of the default platform integer. Inthat case, the default platform integer is used.- outndarray, optional
Alternative output array in which to place the result. It musthave the same shape and buffer length as the expected outputbut the type will be cast if necessary. SeeOutput type determination formore details.
- Returns:
- nancumsumndarray.
A new array holding the result is returned unlessout isspecified, in which it is returned. The result has the samesize asa, and the same shape asa ifaxis is not Noneora is a 1-d array.
See also
numpy.cumsumCumulative sum across array propagating NaNs.
isnanShow which elements are NaN.
Examples
>>>importnumpyasnp>>>np.nancumsum(1)array([1])>>>np.nancumsum([1])array([1])>>>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.]])