Answers for "group by pandas multiple columns"

dataframe groupby multiple columns

grouped_multiple = df.groupby(['Team', 'Pos']).agg({'Age': ['mean', 'min', 'max']})
grouped_multiple.columns = ['age_mean', 'age_min', 'age_max']
grouped_multiple = grouped_multiple.reset_index()
print(grouped_multiple)

two groupby pandas

In [8]: grouped = df.groupby('A')

In [9]: grouped = df.groupby(['A', 'B'])

group by, aggregate multiple column -pandas

df[['col1', 'col2', 'col3', 'col4']].groupby(['col1', 'col2']).agg(['mean', 'count'])

group by 2 columns pandas

In [11]: df.groupby(['col5', 'col2']).size()
Out[11]:
col5  col2
1     A       1
      D       3
2     B       2
3     A       3
      C       1
4     B       1
5     B       2
6     B       1
dtype: int64