title: Numpy select rows based on condition
body: <p>I'm trying to use numpy to remove rows from a two dimensional array where the first value of the row (so the element at index 0) does not match a certain condition.</p>
  <p>I am able to do this with regular python using two loops, but I would like to do it more efficiently with numpy, e.g. with <code>numpy.where</code></p>
  <p>I have been trying various things with <code>numpy.where</code> and <code>numpy.delete</code> but I struggle with the fact that I want to select rows by using a condition that only needs to be verified by the first element, and not the second (I dont care about the value of the second element)</p>
  <p>Here is an example where I only want to keep the rows where the first value of each row is 6.</p>
  <p>Input:</p>
  <pre><code>[[0,4],
   [0,5],
   [3,5],
   [6,8],
   [9,1],
   [6,1]]
  </code></pre>
  <p>Output:</p>
  <pre><code>[[6,8],
   [6,1]]
  </code></pre>