Can you perform multiple operations in a groupby?

Suppose I have the following DataFrame:

df = pd.DataFrame({
    'year': [2015, 2015, 2018, 2018, 2020],
    'total': [100, 200, 50, 150, 400],
    'tax': [10, 20, 5, 15, 40]})

   year  total  tax
0  2015    100   10
1  2015    200   20
2  2018     50    5
3  2018    150   15
4  2020    400   40

I want to sum up the total and tax columns by year and obtain the size at the same time.

The following code gives me the sum of the two columns:

df_total_tax = df.groupby('year', as_index=False)[['total', 'tax']].apply(np.sum)

However, I can't figure out how to also include a column for size at the same time. Must I perform a different groupby, then use .size() and then append that column to df_total_tax? Or is there an easier way?

The end result would look like this:

   year  total  tax  size
0  2015    300   30     2
1  2018    200   20     2
2  2020    400   40     1

Solution

You can specify for each column separately aggregate function in named aggregation:

df.groupby('year', as_index=False).agg(total=('total', 'sum'),
                                       tax=('tax', 'sum'),
                                       size=('tax', 'size'))

   year  total  tax  size
0  2015    300   30     2
1  2018    200   20     2
2  2020    400   40     1