title: Effect of reshaping an numpy array from (2,) to (2,1)
body: <p>I was trying to calculate a covariance matrix of 2 arrays <code>a</code> and <code>b</code> via a dot product in python with the formula <code>a @ b.T</code>.</p>
  <p>The initial form of my input arrays are <code>(2,)</code> when the shape is printed. Obviously the result of this calculation is a single scalar but not the covariance matrix i need.<br />
  As it turns out i needed to reshape the arrays(i.e. <code>a.reshape(2,1)</code>) to a receive the desired <code>(2,2)</code> covariance matrix.</p>
  <p>Now my problem is that i dont understand what effect the reshaping of the arrays has on the data, more specifically why i am allowed to do it and receive the result i want.<br />
  How come i can just reshape the array to receive the covariance matrix, what is the thought process behind it?<br />
  I do understand the how the dot product works, but as i said i dont get why i am allowed to just reshape the array to receive the desired outcome dimensions.</p>
  <p>I hope i made my problem understandable, i have  a bit of trouble formulating it.</p>
  <p>Appreciate any help!</p>