new_contents: """Plot fasttext embedding."""
  
  from matplotlib.pyplot import show, title
  
  import seaborn as sns
  
  from pandas import DataFrame
  
  from six import u
  
  from dasem.dannet import FastText
  
  
  fast_text = FastText()
  
  words = ['virksomhed', 'virxsomhed', 'forretning', 'kapital', 'finans',
           'grus', 'grusgrav', 'transportvirksomhed', u('hyrek\xf8rsel')]
  vector = fast_text.word_vector(words[0])
  
  df = DataFrame([], index=range(len(vector)), columns=words)
  
  for word in words:
      df.ix[:, word] = fast_text.word_vector(word)
  
  corr = df.corr()
  sns.heatmap(corr, 
              xticklabels=corr.columns.values,
              yticklabels=corr.columns.values)
  title('Correlation in word embedding')
  show()
  
subject: Create plot_fasttext_embedding.py