title: Saving dataframes after cleaning in Python
body: <p>I have a collection of JSONs, all of the same format and with the same data irregularities, that I'd like to clean and ultimately convert to dataframes for use within Python.  </p>
  
  <p>As I'm doing the same process repeatedly over each JSON, a loop seemed like the most natural solution. </p>
  
  <p>I'm running into an issue in reassigning the dataframes to variables post-cleaning, as there doesn't appear to be a natural way to store them.  </p>
  
  <p>I know Python frowns on dynamically creating variable names.  I'd like to avoid using a dictionary or otherwise creating a holder variable to achieve this.  Being that I have a list of variables and a placeholder df, it's not otherwise obvious to me how to assign/name the variables post-cleaning.  </p>
  
  <p>Code below.  Any suggestions on how to save the cleaned dataframes at the end of the loop?</p>
  
  <pre><code>vars = [a, b, c]
  
  # clean data iteratively
  for i in vars:
      df = pd.DataFrame(i)
      df['value'] = df['value'].replace('.', np.nan).fillna(method='bfill')
      df['value'] = pd.to_numeric(df['value'])
      [???] = df
  </code></pre>