title: Which is the correct way to efficiently filter a numpy matrix by column values?
body: <p>I am working with a numpy matrix like this:</p>
  
  <pre><code>[[   0    1    2 ...,   97   98  0]
   [ 100  101  102 ...,  197  198  0]
   [ 200  201  202 ...,  297  298  1]
   ...,
   [9700 9701 9702 ..., 9797 9798 1]
   [9800 9801 9802 ..., 9897 9898 0]
   [9900 9901 9902 ..., 9997 9998 0]]
  </code></pre>
  
  <p>How can I remove all the rows that have one in the last column of my numpy matrix?:</p>
  
  <pre><code>[[   0    1    2 ...,   97   98  0]
   [ 100  101  102 ...,  197  198  0]
   ...,
   [9800 9801 9802 ..., 9897 9898 0]
   [9900 9901 9902 ..., 9997 9998 0]]
  </code></pre>
  
  <p>I tried to transform the matrix into a pandas dataframe and filter by the last column:</p>
  
  <pre><code>matrix = pd.DataFrame(data=second_round_mat[1:,1:])
  matrix = matrix[matrix['567'] != 1.0]
  </code></pre>
  
  <p>However, this is not very convinient, and maybe there's a similar way to do that in numpy, thus how can I filter by column value in numpy?</p>