title: Is there a cleaner way to read in mulipt *.csv files and add a column then a for loop?
body: <p>I would like to read in several *.csv files from disk into one big dataframe including a new column of paths as a string in an efficient and clean way.
  Is there a way other then a for-loop?</p>
  
  <p>Data are stored in the same form for different realizations. The setup is the same except the realizations have varying parameter values (and thus results) but are always store via <code>pd.to_csv()</code> with the same columns.</p>
  
  <p>Current solution via for loop:</p>
  
  <pre><code>dfs = []
  
  for path in paths:
      df = pd.read_csv(path)
      df['PATH'] = path
      dfs.append(df)
  
  concated_dfs = pd.concat(dfs)
  </code></pre>
  
  <p>List comprehension but missing column of file paths</p>
  
  <pre><code>concated_dfs = pd.concat([pd.read_csv(path) for path in paths])
  </code></pre>
  
  <p>Desired result: A concated dataframe including a columns describing the path or realization.</p>