title: DataFrame from list of multiple dictionaries where keys are index and values is column data
body: <p>I am trying to create a DataFrame with pandas from a list of dictionaries which looks like this:</p>
  <pre><code>
  [{'3600': '12', '7600': '1212343'}, {'0': 0.0, '3600': 0.0, '7200': 0.0, '10800': 0.0, '14400': 0.0, '18000': 0.0, '21600': 0.0, '25200': 116.93828280645994} .... ]
  
  </code></pre>
  <p>My columns is a list of items: <code>[&quot;col1&quot;, &quot;col2&quot; ...]</code></p>
  <p>What I want is the keys of the dicts to be the index, the values of the dicts should fill the columns. In this example:</p>
  <pre><code>                       col1                  col2
  0                       0/NaN                0.0
  3600                    12                   0.0
  7600                    1212343              NaN
  7200                    NaN                  0.0
  10800                   NaN                  0.0
  18000                   NaN                  0.0
  21600                   NaN                  0.0
  25200                   NaN                  116.93828280645994
  </code></pre>
  <p>So the values of each dictionary basically represent column values. Since the dicts can be of different sizes I need to add NaN.</p>
  <p>I thought I had this already figured out with the help here(<a href="https://stackoverflow.com/questions/62508852/">Create a Dataframe from list of Dictionaries</a>) like this:</p>
  <pre><code>
      columns = [&quot;col&quot;, &quot;col2&quot; ...]
      df_data = mydataasabove
  
      final_dict = defaultdict(list)
  
      for data in df_data:
          for key, value in data.items():
              final_dict[key].append(value)
  
      final_dict = dict(final_dict)
  
      df = pd.DataFrame.from_dict(final_dict, orient='index', columns=columns)
  
  </code></pre>
  <p>But this gives me a df like this:</p>
  <pre><code>                     col1                     col2
  3600                   12                    0.0
  7600              1212343                    NaN
  0                       0                    NaN
  7200                    0                    NaN
  10800                   0                    NaN
  14400                   0                    NaN
  18000                   0                    NaN
  21600                   0                    NaN
  25200             116.938                    NaN
  
  </code></pre>
  <p>As you can see the values do not correspond correctly to my columns. The output of printing <code>final_dict</code> is:</p>
  <p><code>{'3600': ['12', 0.0], '7600': ['1212343'], '0': [0.0], '7200': [0.0], '10800': [0.0], '14400': [0.0], '18000': [0.0], '21600': [0.0], '25200': [116.93828280645994]}</code></p>
  <p>I also tried something along the lines with Chainmap:</p>
  <p><code>df = pd.DataFrame.from_dict(ChainMap(*nec_data), orient='index', columns=['col1'])</code>
  but I couldn't add multiple columns.</p>
  <p>Maybe someone can lend me a ? It would be very much appreciated! Thanks in advance</p>