In [1]:

    

%matplotlib inline
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt


    

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# Load dataset
import zipfile
with zipfile.ZipFile('../datasets/baby-names2.csv.zip', 'r') as z:
    f = z.open('baby-names2.csv')
    names = pd.io.parsers.read_table(f, sep=',')


    

In [3]:

    

names.head()


    

    
Out[3]:






  

    

      

      
year
      
name
      
prop
      
sex
      
soundex
    
  
  

    

      
0
      
1880
      
John
      
0.081541
      
boy
      
J500
    
    

      
1
      
1880
      
William
      
0.080511
      
boy
      
W450
    
    

      
2
      
1880
      
James
      
0.050057
      
boy
      
J520
    
    

      
3
      
1880
      
Charles
      
0.045167
      
boy
      
C642
    
    

      
4
      
1880
      
George
      
0.043292
      
boy
      
G620
    
  

In [4]:

    

names[names.year == 1993].head()


    

    
Out[4]:






  

    

      

      
year
      
name
      
prop
      
sex
      
soundex
    
  
  

    

      
113000
      
1993
      
Michael
      
0.024010
      
boy
      
M240
    
    

      
113001
      
1993
      
Christopher
      
0.018572
      
boy
      
C623
    
    

      
113002
      
1993
      
Matthew
      
0.017332
      
boy
      
M300
    
    

      
113003
      
1993
      
Joshua
      
0.016268
      
boy
      
J200
    
    

      
113004
      
1993
      
Tyler
      
0.014439
      
boy
      
T460
    
  

In [5]:

    

boys = names[names.sex == 'boy'].copy()    
girls = names[names.sex == 'girl'].copy()


    

In [6]:

    

william = boys[boys['name']=='William']

plt.plot(range(william.shape[0]), william['prop'])
plt.xticks(range(william.shape[0])[::5], william['year'].values[::5], rotation='vertical')
plt.ylim([0, 0.1])
plt.show()


    

In [7]:

    

Daniel = boys[boys['name']=='Daniel']

plt.plot(range(Daniel.shape[0]), Daniel['prop'])
plt.xticks(range(Daniel.shape[0])[::5], Daniel['year'].values[::5], rotation='vertical')
plt.ylim([0, 0.1])
plt.show()


    

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