Pandas: Assigning multiple *new* columns simultaneously

Just use result_type="expand" in pandas apply

df
Out[78]: 
   a  b
0  0  1
1  2  3
2  4  5
3  6  7
4  8  9

df[['mean', 'std', 'max']]=df[['a','b']].apply(mathOperationsTuple, axis=1, result_type="expand")

df
Out[80]: 
   a  b  mean  std  max
0  0  1   0.5  0.5  1.0
1  2  3   2.5  0.5  3.0
2  4  5   4.5  0.5  5.0
3  6  7   6.5  0.5  7.0
4  8  9   8.5  0.5  9.0

and here some copy paste code

import pandas as pd
import numpy as np

df = pd.DataFrame(np.arange(10).reshape(5,2), columns=['a','b'])
print('df',df, sep='\n')
print()
def mathOperationsTuple(arr):
    return np.mean(arr), np.std(arr), np.amax(arr)

df[['mean', 'std', 'max']]=df[['a','b']].apply(mathOperationsTuple, axis=1, result_type="expand")
print('df',df, sep='\n')