Adding pandas Series with different indices without getting NaNs

Question

I'm trying to do what I think is a straight froward operation in pandas but I can't seem to make it work.

I have two pandas Series with different numbers of indices, I would like to add values together if they share an index, otherwise I would just like to pass the values that don't have corresponding indices along.

For example

Sr1 = pd.Series([1,2,3,4], index = ['A', 'B', 'C', 'D']) Sr2 = pd.Series([5,6], index = ['A', 'C']) Sr1        Sr2 A     1    A     5 B     2    C     6 C     3 D     4 

Sr1 + Sr2 or Sr1.add(Sr2) give

A     6 B   NaN C     9 D   NaN 

But what I want is

A     6 B     2 C     9 D     4 

where the B and D values for Sr1 are just passed along.

Any suggestions?

Answer 1

You could use fill_value:

>>> import pandas as pd >>> Sr1 = pd.Series([1,2,3,4], index = ['A', 'B', 'C', 'D']) >>> Sr2 = pd.Series([5,6], index = ['A', 'C']) >>> Sr1+Sr2 A     6 B   NaN C     9 D   NaN >>> Sr1.add(Sr2, fill_value=0) A    6 B    2 C    9 D    4 

Answer 2

Sr1 = pd.Series([1,2,3,4], index = ['A', 'B', 'C', 'D'])  Sr2 = pd.Series([5,6,7], index = ['A', 'C','E']) (Sr1+Sr2).fillna(Sr2).fillna(Sr1) 

An alternative approach using fillna. It will work on all cases when indeces do not match too