Answers for "pandas aggregate multiple columns"

12

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)
Posted by: Guest on October-15-2020
0

assign multiple columns pandas

import pandas as pd

df = {'col_1': [0, 1, 2, 3],
        'col_2': [4, 5, 6, 7]}
df = pd.DataFrame(df)

df[[ 'column_new_1', 'column_new_2','column_new_3']] = [np.nan, 'dogs',3]  #thought this wo
Posted by: Guest on September-22-2020

Code answers related to "pandas aggregate multiple columns"

Python Answers by Framework

Browse Popular Code Answers by Language