In [1]:

    

import numpy as np
import pandas as pd


    

In [3]:

    

hair_eye_color = pd.read_csv("In-ClassFirst/HairEyeColor.csv", index_col=0)


    

In [4]:

    

pivoted = pd.pivot_table(hair_eye_color, values='Freq', rows=['Eye', 'Sex'], cols=['Hair'])


    

In [5]:

    

hairSexSum = 1.0*pivoted.sum(axis=1)


    

In [6]:

    

normalized_pivoted = 100.0*pivoted.div(1.0*hairSexSum, axis='index')


    

In [7]:

    

normalized_pivoted


    

    
Out[7]:






  

    

      

      
Hair
      
Black
      
Blond
      
Brown
      
Red
    
    

      
Eye
      
Sex
      

      

      

      

    
  
  

    

      
Blue
      
Female
      
  7.894737
      
 56.140351
      
 29.824561
      
  6.140351
    
    

      
Male
      
 10.891089
      
 29.702970
      
 49.504950
      
  9.900990
    
    

      
Brown
      
Female
      
 29.508197
      
  3.278689
      
 54.098361
      
 13.114754
    
    

      
Male
      
 32.653061
      
  3.061224
      
 54.081633
      
 10.204082
    
    

      
Green
      
Female
      
  6.451613
      
 25.806452
      
 45.161290
      
 22.580645
    
    

      
Male
      
  9.090909
      
 24.242424
      
 45.454545
      
 21.212121
    
    

      
Hazel
      
Female
      
 10.869565
      
 10.869565
      
 63.043478
      
 15.217391
    
    

      
Male
      
 21.276596
      
 10.638298
      
 53.191489
      
 14.893617
    
  

In [8]:

    

axes = normalized_pivoted.plot(kind='bar', stacked=True)