title: How to work with HDF file (fixed format, multiple keys) as a pandas dataframe?
body: <p>I was given a 20GB HDF5 file created using pandas, but unfortunately written in the fixed format (rather than table) with each column written as a separate key. This works nicely for quickly loading one feature, but it doesn't allow handy table-oriented procedures (e.g., statistical analysis or plotting).</p>
  
  <p>Trying to load the file as a whole gives the following error:</p>
  
  <p><code>ValueError: key must be provided when HDF5 file contains multiple datasets</code>.</p>
  
  <pre><code>f=pd.read_hdf('file_path')
  
  ValueError                             Traceback (most recent call last)
  
  384             for group_to_check in groups[1:]:
  385                 if not _is_metadata_of(group_to_check, candidate_only_group):
  
  --&gt; 386                     raise ValueError('key must be provided when HDF5 file '
      387                                      'contains multiple datasets.')
      388             key = candidate_only_group._v_pathname
  
  ValueError: key must be provided when HDF5 file contains multiple datasets.
  </code></pre>
  
  <p>Unfortunately 'key' doesn't accept a python list, so I can't simply load all at once. Is there a way to convert the h5 file from 'fixed' to 'table'? Or to load the file to a dataframe in one go? At the moment my solution is to load each column separately and append to an empty dataframe.</p>