title: Loop through multiple panda dataframes to get multiple dataframe output in Python
body: <p>I have 1000 dataframes that were read by looping 1000 csv files in a directory and my codes are as follows:</p>
  <pre><code>
  for csv in csvs:
          df = pd.read_csv(csvs)
          dfs.append(df)
  </code></pre>
  <p>So basically I have <code>dfs[0]</code> to <code>dfs[999]</code>. Then I made a function called <code>fun</code> to apply to all of these dataframes. If it were only a few dataframes to go through, I would just do <code>output = fun(dfs[0])</code> , <code>output2 = fun(dfs[1])</code>, and so on, but since I have so many dataframes, I want to somehow loop them so I can get 1000 separate output for 1000 separate dataframes. Is this feasible? Also, is there a way to export all these output dataframes into csv files at once? I have never dealt with so many dataframes at once before and would really appreciate if someone could help me out. Thank you in advance!</p>