title: Regular Expressions not working with Pandas Dataframe
body: <p>I've got a Pandas Dataframe that's made up of emails that I'm needing to clean using regex. However, my attempts to clean the column, aren't actually being applied to the text.</p>
  
  <p>Example data is below:</p>
  
  <pre><code>|subeject         | description       |
  ---------------------------------------
  |change email     | 'Hi, I'm trying...|
  |how are you?     | 'Hi, how are...   |
  </code></pre>
  
  <p>The actual dataset has about 2500 rows.</p>
  
  <p>The example code that I'm using is:</p>
  
  <pre><code>data = pd.read_csv('file.csv', names=['subject', 'description'])
  data['description'] = data['description'].str.lower().str.split()
  
  # Text cleaning below:
  data['description'] = data['description'].replace(r'&lt;(.*?)\&gt;', '')
  data['description'] = data['description'].replace(r'www[a-z]+', '')
  ... # more regex
  </code></pre>
  
  <p>Running this code in an iPython notebook using Python 2.7 I would expect the regex to identify statements and replace it with a space.</p>
  
  <p>However, when running it, the text of the description does not change.</p>
  
  <p>An alternative method I've tried with the same result is as follows:</p>
  
  <pre><code>for i in data['description']:
      re.sub(r'&lt;(.*?)\&gt;', '', i)
      re.sub(r'www[a-z]+', '', i)
  </code></pre>
  
  <p>However, I got the same result with none of the text being removed.</p>
  
  <p>Could you please advise or point me in the right direction?</p>