title: how to scale columns in a DataFrame by factors from another DataFrame using Numpy
body: <p>To Scale each columns (A, B, C) in a DataFrame df:</p>
  <pre><code>l1 = [1,2,3]
  l2 = [4,5,6]
  l3 = [7,8,9]
  
  df = pd.DataFrame([z for z in zip(l1,l2,l3)], columns= ['A', 'B', 'C'])
  </code></pre>
  <p>with scaling factors in a DataFrame scaling:</p>
  <pre><code>scaling = pd.DataFrame(dict(id=['B', 'A','C'], scaling = [0.2, 0.3, 0.4]))
  </code></pre>
  <p>using Numpy:</p>
  <pre><code>df = pd.DataFrame(np.array(df)*np.array(scaling['scaling']), columns=df.columns)
  </code></pre>
  <p>How to obtain right factors from scaling with the corresponding id ['B', 'A','C'] using Numpy?</p>
  <p>I expected to have the following result with print(df)</p>
  <pre><code>   A    B    C
  0  0.3  0.8  2.8
  1  0.6  1.0  3.2
  2  0.9  1.2  3.6
  </code></pre>