Sum of NaNs to equal NaN (not zero)

Question

I can add a TOTAL column to this DF using df['TOTAL'] = df.sum(axis=1), and it adds the row elements like this:

   col1  col2  TOTAL
0   1.0   5.0    6.0
1   2.0   6.0    8.0
2   0.0   NaN    0.0
3   NaN   NaN    0.0

However, I would like the total of the bottom row to be NaN, not zero, like this:

   col1  col2  TOTAL
0   1.0   5.0    6.0
1   2.0   6.0    8.0
2   0.0   NaN    0.0
3   NaN   NaN    Nan

Is there a way I can achieve this in a performant way?

Answer 1

Add parameter min_count=1 to DataFrame.sum:

min_count : int, default 0
The required number of valid values to perform the operation. If fewer than min_count non-NA values are present the result will be NA.

New in version 0.22.0: Added with the default being 0. This means the sum of an all-NA or empty Series is 0, and the product of an all-NA or empty Series is 1.

df['TOTAL'] = df.sum(axis=1, min_count=1)
print (df)
   col1  col2  TOTAL
0   1.0   5.0    6.0
1   2.0   6.0    8.0
2   0.0   NaN    0.0
3   NaN   NaN    NaN