title: Lemmatization Pandas (Python)
body: <p>I am a beginner at Pandas and I am trying to figure out how to lemmatize a single column of my dataframe. Take the following example (this is some text after (un)common word removal which I'd like to lemmatize):</p>
  
  <blockquote>
    <p>0    good needs changes virgils natural micro brewe...</p>
    
    <p>1    new favorite given delightful surprise find fl...</p>
    
    <p>2    red sauce favorite enjoy strong tannin ok pull...</p>
    
    <p>3    quality fantastic 1800s 21st century try drink...</p>
    
    <p>4    red first time trying love 100excellent blend ...</p>
  </blockquote>
  
  <p>This is the code I use to do lemmatization (taken from <a href="https://www.analyticsvidhya.com/blog/2018/02/the-different-methods-deal-text-data-predictive-python/" rel="nofollow noreferrer">here</a>):</p>
  
  <pre><code>df['words'] = df['words'].apply(lambda x: "".join([Word(word).lemmatize() for word in x]))
  df['words'].head()
  </code></pre>
  
  <p>But once this code is run the output doesn't change:</p>
  
  <blockquote>
    <p>0    good need change virgil natural micro brewed r...</p>
    
    <p>1    new favorite given delightful surprise find fl...</p>
    
    <p>2    red sauce favorite enjoy strong tannin ok pull...</p>
    
    <p>3    quality fantastic 1800s 21st century try drink...</p>
    
    <p>4    red first time trying love 100excellent blend ...</p>
  </blockquote>
  
  <p>Any help would be greatly appreciated :)</p>
  
  <p>P.S: <code>words</code> is a list of tokenized words</p>