In [1]:

    

from ast import literal_eval
from pandas import DataFrame  # http://github.com/pydata/pandas
import re
import requests               # http://github.com/kennethreitz/requests
import subprocess
import sys


    

In [2]:

    

import matplotlib as plt
%matplotlib inline


    

In [3]:

    

from tools import word_freq


    

In [4]:

    

df1 = word_freq(['monocultural', 'monoracial']) 
df1.plot()


    

    
Out[4]:





<matplotlib.axes._subplots.AxesSubplot at 0x1088c2c18>






    

In [6]:

    

df2 = word_freq(['bicultural', 'biracial', 'biethnic', 'interracial'])
df2.plot()


    

    
Out[6]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f08085b6588>






    

In [7]:

    

df3 = word_freq(['mixed race', 'mixed ethnicity', 'other race', 'other ethnicity'])
df3.plot()


    

    
Out[7]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f080852f748>






    

In [8]:

    

df4 = word_freq(['multicultural', 'multiracial', 'multiethnic', 'polyracial', 'polyethnic', 'polycultural'])
df4.plot()


    

    
Out[8]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f0808501a58>






    

In [9]:

    

df5 = word_freq(['multiculturalism', 'polyculturalism', 'cultural pluralism'])
df5.plot()


    

    
Out[9]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f08085869e8>






    

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