title: train Word2vec model using Gensim
body: <p>this is my code.it reads reviews from an excel file (rev column) and make a list of list.</p>
  
  <p>xp is like this</p>
  
  <pre><code>["['intrepid', 'bumbling', 'duo', 'deliver', 'good', 'one'],['better', 'offering', 'considerable', 'cv', 'freshly', 'qualified', 'private', 'investigator', 'thrust', 'murder', 'investigation', 'invisible'],[ 'man', 'alone', 'tell', 'fun', 'flow', 'decent', 'clip', 'need', 'say', 'sequence', 'comedy', 'gold', 'like', 'scene', 'restaurant', 'excellent', 'costello', 'pretending', 'work', 'ball', 'gym', 'final', 'reel']"]
  </code></pre>
  
  <p>but when use list for model, it gives me error"TypeError: 'float' object is not iterable".i don't know where is my problem.
  Thanks.</p>
  
  <pre><code>xp=[]
  import gensim 
  import logging
  import pandas as pd 
  file = r'FileNamelast.xlsx'
  df = pd.read_excel(file,sheet_name='FileNamex')
  pages = [i for i in range(0,1000)]
  
  
  for page in  pages:
  
   text =df.loc[page,["rev"]]
   xp.append(text[0])
  
  
  model = gensim.models.Word2Vec (xp, size=150, window=10, min_count=2, 
  workers=10)
  model.train(xp,total_examples=len(xp),epochs=10)
  </code></pre>
  
  <p>this is what i got.TypeError: 'float' object is not iterable</p>
  
  <pre><code>---------------------------------------------------------------------------
  TypeError                                 Traceback (most recent call last)
  &lt;ipython-input-32-aa34c0e432bf&gt; in &lt;module&gt;()
       14 
       15 
  ---&gt; 16 model = gensim.models.Word2Vec (xp, size=150, window=10, min_count=2, workers=10)
       17 model.train(xp,total_examples=len(xp),epochs=10)
  
  C:\ProgramData\Anaconda3\lib\site-packages\gensim\models\word2vec.py in __init__(self, sentences, corpus_file, size, alpha, window, min_count, max_vocab_size, sample, seed, workers, min_alpha, sg, hs, negative, ns_exponent, cbow_mean, hashfxn, iter, null_word, trim_rule, sorted_vocab, batch_words, compute_loss, callbacks, max_final_vocab)
      765             callbacks=callbacks, batch_words=batch_words, trim_rule=trim_rule, sg=sg, alpha=alpha, window=window,
      766             seed=seed, hs=hs, negative=negative, cbow_mean=cbow_mean, min_alpha=min_alpha, compute_loss=compute_loss,
  --&gt; 767             fast_version=FAST_VERSION)
      768 
      769     def _do_train_epoch(self, corpus_file, thread_id, offset, cython_vocab, thread_private_mem, cur_epoch,
  
  C:\ProgramData\Anaconda3\lib\site-packages\gensim\models\base_any2vec.py in __init__(self, sentences, corpus_file, workers, vector_size, epochs, callbacks, batch_words, trim_rule, sg, alpha, window, seed, hs, negative, ns_exponent, cbow_mean, min_alpha, compute_loss, fast_version, **kwargs)
      757                 raise TypeError("You can't pass a generator as the sentences argument. Try an iterator.")
      758 
  --&gt; 759             self.build_vocab(sentences=sentences, corpus_file=corpus_file, trim_rule=trim_rule)
      760             self.train(
      761                 sentences=sentences, corpus_file=corpus_file, total_examples=self.corpus_count,
  
  C:\ProgramData\Anaconda3\lib\site-packages\gensim\models\base_any2vec.py in build_vocab(self, sentences, corpus_file, update, progress_per, keep_raw_vocab, trim_rule, **kwargs)
      934         """
      935         total_words, corpus_count = self.vocabulary.scan_vocab(
  --&gt; 936             sentences=sentences, corpus_file=corpus_file, progress_per=progress_per, trim_rule=trim_rule)
      937         self.corpus_count = corpus_count
      938         self.corpus_total_words = total_words
  
  C:\ProgramData\Anaconda3\lib\site-packages\gensim\models\word2vec.py in scan_vocab(self, sentences, corpus_file, progress_per, workers, trim_rule)
     1569             sentences = LineSentence(corpus_file)
     1570 
  -&gt; 1571         total_words, corpus_count = self._scan_vocab(sentences, progress_per, trim_rule)
     1572 
     1573         logger.info(
  
  C:\ProgramData\Anaconda3\lib\site-packages\gensim\models\word2vec.py in _scan_vocab(self, sentences, progress_per, trim_rule)
     1552                     sentence_no, total_words, len(vocab)
     1553                 )
  -&gt; 1554             for word in sentence:
     1555                 vocab[word] += 1
     1556             total_words += len(sentence)
  
  TypeError: 'float' object is not iterable
  </code></pre>