title: Take multiple columns of one dataframe to create another dataframe of two columns
body: <p>I have a dataframe of 145 columns, one column is variable A and the rest are subsets of variable B. What I want is a new dataframe of two columns, A and B. I want to make sure all the B values in the new dataframe have the corresponding A values.</p>
  
  <p>A simplified example of 'original' dataframe:</p>
  
  <pre><code>   A  B1  B2
  0  1   6  11
  1  2   7  12
  2  3   8  13
  3  4   9  14
  4  5  10  15
  </code></pre>
  
  <p>And what I would like to achieve:</p>
  
  <pre><code>   A   B
  0  1   6
  1  2   7
  2  3   8
  3  4   9
  4  5  10
  5  1  11
  6  2  12
  7  3  13
  8  4  14
  9  5  15
  </code></pre>
  
  <p>I have tried to do it like this but have manage to only get the equivalent of B1 and A, the rest vanishes. </p>
  
  <pre><code>original_data = data[1:145]
  
  filtered_data = pd.DataFrame(columns = ['A', 'B'])
  
  columns = list(original_data)
  
  for values in columns:
      for row in pressure_data:
          filtered_data["B"] = original_data[values]
          filtered_data["A"] = data['A']
  </code></pre>
  
  <p>I'd appreciate any tips/advice! Many thanks.</p>