grades_df = pd.DataFrame(
    data={'exam1': [43, 81, 78, 75, 89, 70, 91, 65, 98, 87],
          'exam2': [24, 63, 56, 56, 67, 51, 79, 46, 72, 60]},
    index=['Andre', 'Barry', 'Chris', 'Dan', 'Emilio', 
           'Fred', 'Greta', 'Humbert', 'Ivan', 'James']
)
    
def convert_grades(grades):
    '''
    Fill in this function to convert the given DataFrame of numerical
    grades to letter grades. Return a new DataFrame with the converted
    grade.
    
    The conversion rule is:
        90-100 -> A
        80-89  -> B
        70-79  -> C
        60-69  -> D
        0-59   -> F
    '''
    if grades >= 90:
        grades == 'A'
    elif grades >= 80:
        grades == 'B'
    elif grades >= 70:
        grades == 'C'
    elif grades >= 60:
        grades == 'D'
    else:
        grades == 'F'
    return grades
print grades_df.applymap(convert_grades)

運(yùn)行結(jié)果如下（分?jǐn)?shù)并沒有轉(zhuǎn)化為等級）：

    exam1  exam2

Andre 43 24
Barry 81 63
Chris 78 56
Dan 75 56
Emilio 89 67
Fred 70 51
Greta 91 79
Humbert 65 46
Ivan 98 72
James 87 60