title: Append to a pd.DataFrame, dynamically allocating any new columns
body: <p>I'm wanting to aggregate some API responses into a DataFrame.</p>
  
  <p>The request consistently returns a number of json key value pairs, lets say A,B,C. occasionally however it will return A,B,C,D.</p>
  
  <p>I would like something comparible to SQL's OUTER JOIN, that will simply add the new row, whilst filling the corresponding previous columns as NULL or some other placeholder.</p>
  
  <p>The pandas join options insist upon imposing a unique suffix for the side, I really don't want this.</p>
  
  <p>Am I looking at this the wrong way?</p>
  
  <p>If there is no easy solution, I could just select a subset of the consistently available columns but I really wanted to download the lot and do the processing as a separate stage.</p>