df = pd.DataFrame({'a':[1,1,1,2,2,2,3,3,3,3],'b':np.random.randn(10)})
df
a b
0 1 1.048099
1 1 -0.830804
2 1 1.007282
3 2 -0.470914
4 2 1.948448
5 2 -0.144317
6 3 -0.645503
7 3 -1.694219
8 3 0.375280
9 3 -0.065624
groups = df.groupby('a')
groups # Tells you what "df.groupby('a')" is, not an error
<pandas.core.groupby.DataFrameGroupBy object at 0x00000000097EEB38>
groups.count() # count the number of 1 present in the 'a' column
b
a
1 3
2 3
3 4
groups.sum() # sums the 'b' column values based on 'a' grouping
b
a
1 1.224577
2 1.333217
3 -2.030066