title: Use RegexpTokenizer in a pandas dataframe
body: <p>I'm trying to apply the RegexpTokenizer in a column of the dataframe.</p>
  
  <p>dataframe:</p>
  
  <pre><code>    all_cols
  0   who is your hero and why
  1   what do you do to relax
  2   can't stop to eat
  4   how many hours of sleep do you get a night
  5   describe the last time you were relax
  </code></pre>
  
  <p>Script:</p>
  
  <pre><code>import re
  import nltk
  import pandas as pd
  from nltk import RegexpTokenizer
  
  #tokenization of data and suppression of None (NA)
  df['all_cols'].dropna(inplace=True)
  
  tokenizer = RegexpTokenizer("[\w']+")
  df['all_cols'] = df['all_cols'].apply(tokenizer)
  </code></pre>
  
  <p>Error:</p>
  
  <blockquote>
    <p>TypeError: 'RegexpTokenizer' object is not callable</p>
  </blockquote>
  
  <p>But I don't understand. When I use the other nltk tokenization mode, word_tokenize, works perfectly ...</p>