title: Calculating some statistics for each column of a numpy ndarray
body: <p>I have a 4D numpy array of input data where each column represents a quantity (say speed, acceleration, etc) and I would like to calculate some statistical information for each quantity (mean, st-dev. meadian, 75, 85 and 95 percentiles.</p>
  <p>So for example:</p>
  <pre><code>input_shape = (1,200,4)
  n_sample = 100
  
  X = np.random.uniform(0,1, (n_sample,) + input_shape)
  X.shape
  (100, 1, 200, 4)
  
  X[0]
  array([[[0.50410922, 0.82829892, 0.72460878, 0.0562701 ],
          [0.49223423, 0.14152948, 0.32285973, 0.49056405],
          ...
          [0.8299407 , 0.78446729, 0.40959698, 0.893117  ],
          [0.25150705, 0.56759064, 0.28280459, 0.0599566 ]]])
  </code></pre>
  <p>Each column of <code>X</code>  represents some physical quantity for 200 data-points. The statistics of each quantity is what I'm interested in.</p>
  <p><strong>EDIT</strong></p>
  <p>I would expect something like:</p>
  <pre><code>[[[col1_mean, col2_mean, col3_mean, col4_mean ],
     [col1_std, col2_std, col3_std, col4_mean],
     [col1_med, col2_med, col3_med, col4_med],
     [col1_p75, col2_p75, col3_p75, col4_p75 ],
     [col1_p85, col2_p85, col3_p85, col4_p85 ],
     [col1_p95, col2_p95, col3_p95, col4_p95 ]]]
  </code></pre>
  <p>So the result is shaped <code>(100, 1, 6, 4)</code></p>