text: import pandas as pd
  from nltk.corpus import wordnet as wn
  import nltk
  from rpy2 import robjects
  
  def R_network_plot(data, map_name):
      r = robjects.r
      MisLinks, MisNodes = data
  
      str = """
      library(networkD3)
      data({})
      data({})
      a=forceNetwork(Links = MisLinks, Nodes = MisNodes,
                  Source = "source", Target = "target",
                  Value = "value", NodeID = "name",
                  Group = "group", opacity = 0.8)
      saveNetwork(a, 'D:/Github/Vocabulary_Analysis/Map/{}.html')
      """.format(MisLinks, MisNodes, map_name)
      r(str)
  
  # corpus = pd.read_csv('./ECDICT/ecdict.csv', sep=',', error_bad_lines=False, index_col=False, dtype='unicode')
  
  
  def print_all_lemma(word):
      for i in wn.synsets(word):
          w = i
          print('{}'.format(w), w.lemma_names())
  
  if __name__=='__main__':
      print_all_lemma('emphasize')
  
  
  
  