pandas apply function on multiple columns code example

Example 1: 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)

Example 2: set dtype for multiple columns pandas

import pandas as pd

df = pd.DataFrame({'id':['a1', 'a2', 'a3', 'a4'],
  				   'A':['0', '1', '2', '3'],
                   'B':['1', '1', '1', '1'],
                   'C':['0', '1', '1', '0']})

df[['A', 'B', 'C']] = df[['A', 'B', 'C']].apply(pd.to_numeric, axis = 1)