title: Performance of row vs column operations in NumPy
body: <p>There are <a href="http://undocumentedmatlab.com/blog/matrix-processing-performance/">a few articles</a> that show that MATLAB prefers column operations than row operations, and that depending on you lay out your data the performance <a href="http://undocumentedmatlab.com/blog/matrix-processing-performance/">can vary significantly</a>.  This is apparently because MATLAB uses a <a href="http://en.wikipedia.org/wiki/Row-major_order#Column-major_order"><strong>column-major</strong></a> order for representing arrays. </p>
  
  <p>I remember reading that Python (NumPy) uses a <a href="http://en.wikipedia.org/wiki/Row-major_order"><strong>row-major</strong></a> order. With this, my questions are:</p>
  
  <ol>
  <li>Can one expect a similar difference in performance when working with NumPy? </li>
  <li>If the answer to the above is yes, what would be some <strong>examples that highlight this difference</strong>?</li>
  </ol>