title: Pandas DataFrame group by value and get column & row indexes
body: <p>I have a pandas <code>DataFrame</code> like following.</p>
  
  <pre><code>df = pandas.DataFrame(np.random.randn(5,5),columns=['1','2','3','4','5'])
  
           1         2         3         4         5
  0  0.877455 -1.215212 -0.453038 -1.825135  0.440646
  1  1.640132 -0.031353  1.159319 -0.615796  0.763137
  2  0.132355 -0.762932 -0.909496 -1.012265 -0.695623
  3 -0.257547 -0.844019  0.143689 -2.079521  0.796985
  4  2.536062 -0.730392  1.830385  0.694539 -0.654924
  </code></pre>
  
  <p>I need to get row and column indexes for following three groups. (In my original dataset there are no negative values)</p>
  
  <ol>
  <li>value is greater than 2.0</li>
  <li>value is between 1.0 - 2.0</li>
  <li>value is less than 1.0</li>
  </ol>
  
  <p>For e.g for "value is greater than 2.0" it should return [1,4]. I have tried using this which gives a boolean result.</p>
  
  <pre><code>df.values &gt; 2
  </code></pre>