title: Reshape numpy (n,) vector to (n,1) vector
body: <p>So it is easier for me to think about vectors as column vectors when I need to do some linear algebra. Thus I prefer shapes like (n,1). </p>
  
  <p>Is there significant memory usage difference between shapes (n,) and (n,1)? </p>
  
  <p>What is preferred way? </p>
  
  <p>And how to reshape (n,) vector into (n,1) vector. Somehow b.reshape((n,1)) doesn't do the trick. </p>
  
  <pre><code>a = np.random.random((10,1))
  b = np.ones((10,))
  b.reshape((10,1))
  print(a)
  print(b)
  
  [[ 0.76336295]
   [ 0.71643237]
   [ 0.37312894]
   [ 0.33668241]
   [ 0.55551975]
   [ 0.20055153]
   [ 0.01636735]
   [ 0.5724694 ]
   [ 0.96887004]
   [ 0.58609882]]
  [ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.]
  </code></pre>