title: How to normalize a complex json format in a pandas data frame that is a list of dictionaries
body: <p>I have a pandas data frame that has one column like this in json format. I am not able to understand how to extract this.</p>
  <pre><code>df['completionDetails'][0] gives:
  
  [{'name': 'start', 'time': 1654098788177},
   {'name': 'arrival',
    'time': 1654099038368,
    'location': [-74.2713929, 40.5017297]},
   {'name': 'departure',
    'time': 1654098843357,
    'location': [-74.2802414, 40.5095964]}]
  </code></pre>
  <p>I have tried:</p>
  <pre><code>dict_df = pd.DataFrame([ast.literal_eval(i) for i in df['completionDetails'].values])
  </code></pre>
  <p>But it is giving me error. What method can I use for this?</p>
  <p>Expected Output:</p>
  <p><div class="snippet" data-lang="js" data-hide="false" data-console="true" data-babel="false">
  <div class="snippet-code">
  <pre class="snippet-code-html lang-html prettyprint-override"><code>start_time  arrival_time    arrival_location    departure_time  departure_location
  1654098788177   1654099038368   [-74.2713929, 40.5017297]   1654098843357    [-74.2802414, 40.5095964]</code></pre>
  </div>
  </div>
  </p>