Python Pandas add column for row-wise max value of selected columns

data = {'name' : ['bill', 'joe', 'steve'],
    'test1' : [85, 75, 85],
    'test2' : [35, 45, 83],
     'test3' : [51, 61, 45]}
frame = pd.DataFrame(data)

I would like to add a new column that shows the max value for each row.

desired output:

 name test1 test2 test3 HighScore
 bill  75    75    85    85
 joe   35    45    83    83 
 steve  51   61    45    61 

Sometimes

frame['HighScore'] = max(data['test1'], data['test2'], data['test3'])

works but most of the time gives this error:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Why does it only work sometimes? Is there another way of doing it?

>>> frame['HighScore'] = frame[['test1','test2','test3']].max(axis=1)
>>> frame
    name  test1  test2  test3  HighScore
0   bill     85     35     51         85
1    joe     75     45     61         75
2  steve     85     83     45         85

>>> frame['HighScore'] = frame[['test1','test2','test3']].apply(max, axis=1)
>>> frame
    name  test1  test2  test3  HighScore
0   bill     85     35     51        85
1    joe     75     45     61        75
2  steve     85     83     45        85

if a max or min value between multiple columns in a df is to be determined then use:

df['Z']=df[['A','B','C']].apply(np.max,axis=1)