title: Creating a pandas column conditional to another columns values based on a dictionary
body: <p>Goodday,</p>
  
  <p>I'm currently trying to tag a lot of job-ads based on the job-title using python 3.x and pandas. As every company uses different terminology for their jobs I want to cluster them in a sensible way.</p>
  
  <p>Currently I have a dataframe containing 40.000+ job-ads and use following code to tag the jobs in a new pandas column:</p>
  
  <pre><code>dictionary = {
      'c.*dev': 'c developer',
      'web.*des': 'web designer',
      'onl.*mark': 'online marketer',
  ...
  }
  for key in dictionary:
      df.loc[(df['Job'].str.contains(key) == True), ['Clustered Jobs']] = dictionary[key]
  </code></pre>
  
  <p>As the dictionary and the database is growing constantly. I wanted to ask whether there is a more elegant and efficient way to do this.</p>
  
  <p>Thanks for your help in advance.</p>