Pandas Groupby and Sum Only One Column

Question

So I have a dataframe, df1, that looks like the following:

       A      B      C 1     foo    12    California 2     foo    22    California 3     bar    8     Rhode Island 4     bar    32    Rhode Island 5     baz    15    Ohio 6     baz    26    Ohio 

I want to group by column A and then sum column B while keeping the value in column C. Something like this:

      A       B      C 1    foo     34    California 2    bar     40    Rhode Island 3    baz     41    Ohio 

The issue is, when I say df.groupby('A').sum() column C gets removed returning

      B A bar  40 baz  41 foo  34 

How can I get around this and keep column C when I group and sum?

Answer 1

The only way to do this would be to include C in your groupby (the groupby function can accept a list).

Give this a try:

df.groupby(['A','C'])['B'].sum() 

One other thing to note, if you need to work with df after the aggregation you can also use the as_index=False option to return a dataframe object. This one gave me problems when I was first working with Pandas. Example:

df.groupby(['A','C'], as_index=False)['B'].sum()