title: How can I extrace and replace a column dictionary into a single column in Pandas
body: <p>I have a dataframe where every entry in the column <code>info</code> is a dictionary of the form <code>{'name':name, 'year':year}</code>. I want to be able to unpack this dictionary and just replace that column such that every cell will just be <code>name</code>.</p>
  <p>I've tried using <code>json_normalize</code> as follows</p>
  <pre><code>df = df.read_csv('file.csv')
  df.dropna(subset=['info'], inplace=True)
  names = pd.json_normalize(df['name'])
  df['info'] = names['name']
  </code></pre>
  <p>This is close but I find that it introduces weird NaN values into my final df (I think it's related to losing the row indexes from dropping).</p>
  <p>If there's an efficient way to do this without creating extra columns and deleting them, that would be appreciated.</p>