How does df.combine() works?
From example in docs
take_smaller = lambda s1, s2: s1 if s1.sum() < s2.sum() else s2This says if sum of a series in df1 is less than sum of the series in df2 , return series from df1 else from df2.
So when you do:
df1.combine(df2, take_smaller) A B0 0 3.01 0 0.0This works fine.
However when you do a fill_value=-5 , then the sum of second series in the first dataframe becomes smaller since fill_value first fills NaN and then compares. (-5+4) < (3+0) , hence -5 and 4 is returned.
fill_value scalar value, default NoneThe value to fill NaNs with prior to passing any column to the merge func.
I guess you are refering to doc example
take_smaller = lambda s1, s2: s1 if s1.sum() < s2.sum() else s2if so
Here you are using fill_value=-5 so column B passed in function would be[-5,4] and [3,0]
so -5 + 4 = -1 is less than 3 + 0 = 3 hence [-5, 4] returned.