python - 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?

Can you just groupby A and C? If every value of A doesn't map 1 to 1 to a value of C, then what you're asking isn't possible. If they do map 1 to 1, it should be no trouble to groupby both — Kyle Heuton
Yea got it, I had been trying to do multiple values but hadn't been using the proper format which caused me to think I couldn't use multiple values. Thanks! — JSolomonCulp

Sevyns Sevyns · Accepted Answer · 2016-08-16T21:58:06

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()

python - Pandas Groupby and Sum Only One Column

2 Answers