In [31]:

    

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
names = pd.read_csv("names_prop_by_year.csv")
boy_names = names[names["Sex"]=='M']
girl_names = names[names["Sex"]=='F']
girl_names.head()
boy_names.columns
john_occurnace = boy_names[boy_names["Name"]=="John"]
mary_occurnace = girl_names[girl_names["Name"]=="Mary"]


    

In [52]:

    

chloe_occurnace = girl_names[girl_names["Name"]=="Chloe"]
# john_occurnace = john_occurnace.sort(["Year"])
john_occurnace.head()
mary_occurnace.head()
# mary_occurnace[['Prop']] = mary_occurnace[['Prop']].astype(float)
# mary = mary_occurnace.ix[0:,['Year','Prop']]
# john = john_occurnace.ix[0:,['Year','Prop']]


    

    
Out[52]:






  

    

      

      
Name
      
Sex
      
Count
      
Prop
      
Year
    
  
  

    

      
0
      
Mary
      
F
      
7065
      
0.035065
      
1880
    
    

      
2000
      
Mary
      
F
      
6919
      
0.035906
      
1881
    
    

      
3935
      
Mary
      
F
      
8148
      
0.036779
      
1882
    
    

      
6062
      
Mary
      
F
      
8012
      
0.036930
      
1883
    
    

      
8146
      
Mary
      
F
      
9217
      
0.037857
      
1884
    
  

In [58]:

    

# mary.head()
# mary.to_csv('file.csv', index=False)
# john = john_occurnace.ix[0:,['Year','Prop']]
# mary.plot()
# john.plot(color='Blue')
# plt.show()
plt.figure();
john_occurnace.plot(x="Year",y="Prop",color="Red",title='John')
plt.legend( ('John',), loc=0 )
mary_occurnace.plot(x="Year",y="Prop",color="Blue",title='Mary')
plt.legend( ('Mary',), loc=0 )
chloe_occurnace.plot(x="Year",y="Prop",color="Green",title='Chloe')
plt.legend( ('Chloe',), loc=0 )
plt.show()


    

In [102]:

    

mix = pd.merge(john_occurnace.loc[:,['Year','Prop']], mary_occurnace.loc[:,['Year','Prop']], on='Year')
mix = pd.merge(mix, chloe_occurnace.loc[:,['Year','Prop']], on='Year')
mix.columns = ['Year', 'john', 'mary','chloe']


    

In [108]:

    

mix.plot(x="Year")
plt.show()


    

In [105]:

    

mix.tail()


    

    
Out[105]:






  

    

      

      
Year
      
john
      
mary
      
chloe
    
  
  

    

      
129
      
2009
      
0.003175
      
0.000827
      
0.003120
    
    

      
130
      
2010
      
0.003130
      
0.000776
      
0.003185
    
    

      
131
      
2011
      
0.003023
      
0.000741
      
0.003009
    
    

      
132
      
2012
      
0.002906
      
0.000703
      
0.002646
    
    

      
133
      
2013
      
0.002935
      
0.000721
      
0.002415
    
  

In [ ]: