title: Removing rows with a duplicate column pandas dataframe (Python)
body: <p>I have a csv, which I read using pandas and created a dataframe.
  The dataframe looks like this:</p>
  
  <pre><code>description     title
  lorem ipsum       A
  ipsum lorem       A
  dolor sit amet    C
  amet sit dolor    B
  </code></pre>
  
  <p>It has 1034 rows and 2 columns</p>
  
  <p>Now I want to remove all the rows with duplicate titles from the dataframe and have the dataframe like this:</p>
  
  <pre><code>description     title
  lorem ipsum       A
  dolor sit amet    C
  amet sit dolor    B
  </code></pre>
  
  <p>I found a solution which says to remove duplicates using <code>drop_duplicates()</code>. In my scenerio I did: </p>
  
  <pre><code>df.drop_duplicates('title', inplace = True)
  </code></pre>
  
  <p>When I <code>print df</code> it still shows 1034 rows, but at the end it displays [967 x 2], which means it has 967 rows and it did remove duplicates. Even doing df.shape tells me the same thing. But when I print or iterate over it seems to not work. In-fact even print length of particular column gives me 967. Example: <code>print len(df['title'])</code> gives me <code>967</code>. Is it just that the dataframe indices are numbered the same? Or it really still has 1034 rows?
  What could be the issue? </p>
  
  <p>I am attaching my code: </p>
  
  <pre><code>df = pd.read_csv('latestdata.csv', sep='\t')
  df.drop_duplicates('title', inplace=True)
  print df
  </code></pre>