Answers for "groupby aggregate on multiple columns"

12

Pandas groupby aggregate 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)
Posted by: Guest on October-15-2020
0

group by, aggregate multiple column -pandas

df[['col1', 'col2', 'col3', 'col4']].groupby(['col1', 'col2']).agg(['mean', 'count'])
Posted by: Guest on November-20-2020

Code answers related to "groupby aggregate on multiple columns"

Python Answers by Framework

Browse Popular Code Answers by Language