DataFrame apply()

import pandas as pd

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']
)

if False:
	def convert_grades_curve(exam_grades):
		return pd.qcut(exam_grades,
			[0, 0.1, 0.2, 0.5, 0.8, 1],
			labels=['F','D','C','B','A'])

	print convert_grades_curve(grades_df['exam1'])

	print grades_df.apply(convert_grades_curve)

def standardize(df):

	return None

import numpy as np
import pandas as pd

df = pd.DataFrame({
	'a': [4,5,3,1,2],
	'b': [20,10,40,50,30],
	'c': [25,20, 5, 15, 10]
	})

if False:
	print df.apply(np.mean)
	print df.apply(np.max)

def second_largest(df):
	return None