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In [1]:

    
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import glob
from os import path
import itertools
import requests
from io import StringIO
from pandas import DataFrame



In [3]:

    
%matplotlib inline



In [4]:

    
from tools import word_freq



In [5]:

    
data = word_freq(["African American", 'bicultural', 'biracial', 'biethnic', 'interracial'])



In [6]:

    
data.head()









    Out[6]:






  
    
      
      African_American
      bicultural
      biracial
      biethnic
      interracial
    
    
      year
      
      
      
      
      
    
  
  
    
      1800
      0
      2.330130e-09
      0
      0
      0
    
    
      1801
      0
      1.864104e-09
      0
      0
      0
    
    
      1802
      0
      1.553420e-09
      0
      0
      0
    
    
      1803
      0
      1.331503e-09
      0
      0
      0
    
    
      1804
      0
      1.331503e-09
      0
      0
      0



In [7]:

    
data["combined"] = data["interracial"] + data["biethnic"]



In [10]:

    
data[["African_American", "bicultural", "combined"]].plot()









    Out[10]:





<matplotlib.axes._subplots.AxesSubplot at 0x10aaa2940>

	African_American	bicultural	biracial	biethnic	interracial
year
1800	0	2.330130e-09	0	0	0
1801	0	1.864104e-09	0	0	0
1802	0	1.553420e-09	0	0	0
1803	0	1.331503e-09	0	0	0
1804	0	1.331503e-09	0	0	0