Data frame vectorized

import pandas as pd

if False:
	df1 = pd.DataFrame({'a':[1,2,3],'b':[4,5,6],'c':[7,8,9]})
	df2 = pd.DataFrame({'a':[10,20,30],'b':[40,50,60],'c':[70,80,90]})
	print df1 + df2

if False:
	df1 = pd.DataFrame({'a':[1,2,3], 'b':[4,5,6], 'c':['7','8','9']})
	df2 = pd.DataFrame({'d':[10,20,30], 'c':[40,50,60], 'b':[70,80,90]})
	df1 + df2

if False:
	df1 = pd.DataFrame({'a':[1,2,3], 'b':[4,5,6], 'c':[7,8,9]},
			index=['row1','row2','row3'])
	df2 = pd.DataFrame({'a':[10,20,30],'b':[40,50,60],'c':[70,80,90]},
			index=['row4','row3','row2'])
	print df1 + df2

entries_and_exits = pd.DataFrame({
    'ENTRIESn': [3144312, 3144335, 3144353, 3144424, 3144594,
                 3144808, 3144895, 3144905, 3144941, 3145094],
    'EXITSn': [1088151, 1088159, 1088177, 1088231, 1088275,
               1088317, 1088328, 1088331, 1088420, 1088753]
	})

def get_hourly_entries_and_exits(entries_and_exits):

	return None

import pandas as pd

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

	def add_one(x):
		return x + 1

	print df.applymap(add_one)

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):

	return None