title: Numpy , Python3.6 - not able to understand why address is different?
body: <p>Here is my Code</p>
  
  <pre><code>my_array_1 = np.arange(25).reshape(5, 5)
  print(my_array_1)
  
  my_array_red = my_array_1[:, 1::2]
  print(my_array_red)
  
  my_array_blue = my_array_1[1::2, 0:3:2]
  print(my_array_blue)
  
  my_array_yellow = my_array_1[-1, :]
  print(my_array_yellow)
  
  print(id(my_array_1))
  print(id(my_array_red))
  print(id(my_array_yellow))
  print(id(my_array_blue))
  
  print(my_array_1.data)
  print(my_array_red.data)
  print(my_array_blue.data)
  print(my_array_yellow.data)
  </code></pre>
  
  <p>Here is the Output:</p>
  
  <pre><code>[[ 0  1  2  3  4]
   [ 5  6  7  8  9]
   [10 11 12 13 14]
   [15 16 17 18 19]
   [20 21 22 23 24]]
  [[ 1  3]
   [ 6  8]
   [11 13]
   [16 18]
   [21 23]]
  [[ 5  7]
   [15 17]]
  [20 21 22 23 24]
  2606769150592
  2606769282544
  2607017647120
  2606769282624
  &lt;memory at 0x0000025EFE56CA68&gt;
  &lt;memory at 0x0000025EFE56CA68&gt;
  &lt;memory at 0x0000025EFE56CA68&gt;
  &lt;memory at 0x0000025EFE5A8F48&gt;
  </code></pre>
  
  <p>Question :
  Just check the last 4 lines of my output . why my_array_1.data.data , my_array_red.data, my_array_blue.data have same value , But where as my_array_yellow.data have a different value ?</p>