title: Express pandas operations as pipeline
body: <pre><code>df = df.loc[:, dict_lup.values()].rename(columns={v: k for k, v in dict_lup.items()})
  
  df['cover'] = df.loc[:, 'cover'] * 100.
  df['id'] = df['condition'].map(constants.dict_c) 
  df['temperature'] = (df['min_t'] + df['max_t])/2.
  </code></pre>
  
  <p>Is there a way to express the code above as a pandas pipeline? I am stuck at the first step where I rename some columns in the dataframe and select a subset of the columns.</p>
  
  <p>-- EDIT:
  Data is here:</p>
  
  <pre><code>    max_t   col_a   min_t   cover   condition   pressure
  0   38.02   1523106000  19.62   0.48    269.76  1006.64
  1   39.02   1523196000  20.07   0.29    266.77  1008.03
  2   39  1523282400  19.48   0.78    264.29  1008.29
  3   39.11   1523368800  20.01   0.7 263.68  1008.29
  4   38.59   1523455200  20.88   0.83    262.35  1007.36
  5   39.33   1523541600  22  0.65    261.87  1006.82
  6   38.96   1523628000  24.05   0.57    259.27  1006.96
  7   39.09   1523714400  22.53   0.88    256.49  1007.94
  </code></pre>