title: numpy find the max value in a row and return back to it's column index
body: <p>I have a 180295* 10 numpy array called lda_trans, row means words, and column means 10 topics.</p>
  
  <pre><code>array([[0.01841009, 0.01840699, 0.35798764, ..., 0.38443892, 0.01841072,
          0.12870054],
         [0.1       , 0.1       , 0.1       , ..., 0.1       , 0.1       ,
          0.1       ],
         [0.1       , 0.1       , 0.1       , ..., 0.1       , 0.1       ,
          0.1       ],
         ...,
         [0.0416964 , 0.62473603, 0.0416964 , ..., 0.04169395, 0.04169796,
          0.04169232],
         [0.03772096, 0.03775132, 0.66048403, ..., 0.03771698, 0.03772411,
          0.0377139 ],
         [0.03754747, 0.03756587, 0.66206395, ..., 0.03754399, 0.037551  ,
          0.03753927]])
  </code></pre>
  
  <p>Now I want to turn back each row's maximum value's column name, I only know how to extract the max value in each row, but I don't know how to get the column name.
  I know in pandas can use idxmax. But is there any similar function in Numpy? Thanks! </p>
  
  <pre><code>for i in range(180295):
      lda_trans_max.append(np.max(lda_trans[i]))
  </code></pre>