title: Row vs. Column Vector Return during Numpy Array Slicing
body: <p>I am currently learning Python and stumbled across a result that confused me a little bit when performing basic array slicing commands.</p>
  
  <p>I created a 4x5 matrix using this command:</p>
  
  <pre><code>&gt;&gt;&gt; a = numpy.arange(20).reshape(4,5)
  </code></pre>
  
  <p>Which gives:</p>
  
  <pre><code>[[ 0, 1, 2, 3, 4],
   [ 5, 6, 7, 8, 9],
   [10,11,12,13,14],
   [15,16,17,18,19]]
  </code></pre>
  
  <p>If I index the array like this:</p>
  
  <pre><code>&gt;&gt;&gt; a[0:3, 2]
  </code></pre>
  
  <p>I get a row vector: </p>
  
  <pre><code>[2, 7, 12]
  </code></pre>
  
  <p>But if I index the array like this:</p>
  
  <pre><code>&gt;&gt;&gt; a[0:3, 2:3]
  </code></pre>
  
  <p>I get a column vector:</p>
  
  <pre><code>[[ 2],
   [ 7],
   [12]]
  </code></pre>
  
  <p>When plugging the two commands in I expected the results to be the same, so why am I getting different types of vectors?</p>
  
  <p>Thank you!</p>