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)