title: Multidimensional array for random.choice in NumPy
body: <p>I have a table and I need to use random.choice for probability calculation, 
  for example (taken from docs):</p>
  
  <pre><code>&gt;&gt;&gt; aa_milne_arr = ['pooh', 'rabbit', 'piglet', 'Christopher']
  &gt;&gt;&gt; np.random.choice(aa_milne_arr, 5, p=[0.5, 0.1, 0.1, 0.3])
  array(['pooh', 'pooh', 'pooh', 'Christopher', 'piglet'],
        dtype='|S11')
  </code></pre>
  
  <p>If I have 3D array instead of aa_milne_arr, it doesn't let me proceed. I need to generate random things with the different probabilities for the 3 arrays, but the same for elements inside of them. For example, </p>
  
  <pre><code>&gt;&gt;&gt; arr0 = ['red', 'green', 'blue']
  &gt;&gt;&gt; arr1 = ['light', 'wind', 'sky']
  &gt;&gt;&gt; arr3 = ['chicken', 'wolf', 'dog']
  &gt;&gt;&gt; p = [0.5, 0.1, 0.4]
  </code></pre>
  
  <p>And I want the same probs for elements in arr0 (0.5), arr1 (0.1) and arr3 (0.4) so as a result I will see with the probability of 0.5 any element from arr0 etc.</p>
  
  <p>Is it any elegant way to do it?</p>