title: How to resample a dataframe with different functions applied to each column if we have more than 20 columns?
body: <p>I know this question has been asked before. The answer is as follows:</p>
  
  <pre><code>df.resample('M').agg({'col1': np.sum, 'col2': np.mean})
  </code></pre>
  
  <p>But I have 27 columns and I want to sum the first 25, and average the remaining two. Should I write this('col1' - 'col25': np.sum) for 25 columns and this('col26': np.mean, 'col27': np.mean) for two columns? </p>
  
  <p>Mt dataframe contains hourly data and I want to convert it to monthly data. I want to try something like that but it is nonsense:</p>
  
  <pre><code>for i in col_list:
      df = df.resample('M').agg({i-2: np.sum, 'col26': np.mean, 'col27': np.mean})
  
  </code></pre>
  
  <p>Is there any shortcut for this situation?</p>