title: Descending sorting in numpy by several columns
body: <p>I have NumPy array and need to sort it by two columns (first by column 0 and then sort equal values by column 1), both in descending order. When I try to sort sequentially by column 1 and column 0, the rows equal in the second sorting turn to be sorted in ascending order in the first sorting.</p>
  <p>My array:</p>
  <pre><code>arr = np.array([
      [150, 8],
      [105, 20],
      [90, 100],
      [101, 12],
      [110, 80],
      [105, 100],
  ])
  </code></pre>
  <p>When I sort twice (by column 1 and column 0):</p>
  <pre><code>arr = arr[arr[:,1].argsort(kind='stable')[::-1]]
  arr = arr[arr[:,0].argsort(kind='stable')[::-1]]
  </code></pre>
  <p>I have this result (where rows 2 and 3 are swapped):</p>
  <pre><code>array([[150,   8],
         [110,  80],
         [105,  20],
         [105, 100],
         [101,  12],
         [ 90, 100]])
  </code></pre>
  <p>As far as I understand, it happens because stable mode preserves the original order for equal values, but when we flip the indices to make the order descend, the original order changes too.</p>
  <p>The results I'd like to have:</p>
  <pre><code>array([[150,   8],
         [110,  80],
         [105, 100],
         [105,  20],
         [101,  12],
         [ 90, 100]])
  </code></pre>