nansum

nansum is a numerical function in the NumPy library used to compute the sum of array elements while treating NaN values as zero. It is part of NumPy’s set of NaN-aware reduction operations.

nansum expects an array-like input and can reduce along a specified axis. When axis is None, it returns a single scalar; when an axis is provided, it returns an array with that axis reduced. The function ignores NaN values during the summation, effectively replacing NaNs with zero for the purpose of the calculation. For example, summing [1, NaN, 3] yields 4.

The function also supports optional parameters to control the result type and output location. A dtype argument can be supplied to specify the accumulator’s precision, which is useful for controlling overflow or choosing a different numeric type. An out parameter allows the result to be written into an existing array.

Implementation notes emphasize that NaN values do not propagate into the result; they are treated as missing data that do not contribute to the sum. If all elements along a reduction axis are NaN, the result is zero (or zero of the chosen dtype). This behavior makes nansum particularly suitable for datasets with missing values where total quantities are still of interest.

nansum is commonly used in scientific computing with NumPy, especially when data may be incomplete. It complements functions like numpy.sum, which propagate NaNs, and other nan-aware reductions such as nanmean, nanmin, and nanmax.