from google_ngram import *
# this is safe because there's just the one class, named Gngram
import matplotlib.pyplot as plt
%matplotlib inline

g = Gngram(['google', 'ngram'], years=[1940, 2000], case_insensitive=True)

print g.df_parents.head()

plt.plot(g.df_parents.index, g.df_parents)

      google (All)  ngram (All)
1940  0.033068      0.000000
1941  0.040585      0.000000
1942  0.037307      0.000000
1943  0.015727      0.001123
1944  0.049249      0.000000

Searches Google Ngram Viewer for search terms and creates pandas dataframes of results
    
    Arguments: ngrams must be list
               years is list of length 2, endpoints (inclusive)\
               corpus: 15 is English
               If case_insensitive = True, will return df_parents and df_expansion;
                   otherwise just df_parents
    
    Dataframe objects:
             df_parents: a dataframe with years as Index and search terms as columns and
                         words per million words as value
             df_expansion: similar, but with df_parent columns expanded in different cases
                           where applicable (e.g. the, The, THE)
                           
    Dict objects (not necessarily useful, but included for the sake of thoroughness):
             ngram_type: dict of column name : Goolge ngram defined type, 
                         e.g. {"the (All): NGRAM", "the": "expansion" ... }
             parent_expansion: dict of parent column name : list of expansion column names
                               e.g. {"the (All)": ["The", "the", "THE"]}
             expansion_parent: dict of expansion column name: parent column name
                               e.g. {'the': 'the (All)', 'The', 'the (All)', ...}
                               
    Other:
             html: the raw html returned from Google Ngrams Viewer
             json: the json object of results extracted from the raw html (it's inline in the html)
             url: the Google Ngrams Viewer url that returned the results.