title: Filter rows after groupby pandas
body: <p>I have a table in pandas: </p>
  
  <pre><code>import pandas as pd
  
  df = pd.DataFrame({
      'LeafID':[1,1,2,1,3,3,1,6,3,5,1],
      'pidx':[10,10,300,10,30,40,20,10,30,45,20],
      'pidy':[20,20,400,20,15,20,12,43,54,112,23],
      'count':[10,20,30,40,80,10,20,50,30,10,70],
      'score':[10,10,10,22,22,3,4,5,9,0,1]
  })
  
  LeafID  count       pidx     pidy   score
  0   1       10           10        20     10
  1   1       20           10        20     10
  2   2       30          300       400     10
  3   1       40           10        20     22
  4   3       80           30        15     22
  5   3       10           40        20      3
  6   1       20           20        12      4
  7   6       50           10        43      5
  8   3       30           20        54      9
  9   5       10           45       112      0
  10  1       70           20        23      1
  </code></pre>
  
  <p>I want to do a <code>groupby</code> and then filter the rows where occurrence of <code>pidx</code> is greater than 2.</p>
  
  <p>That is, filter rows where <code>pidx</code> is 10 and 20.</p>
  
  <p>I tried using <code>df.groupby('pidx').count()</code> but it didn't helped me. Also for those rows I have to do 0.4*count+0.6*score.</p>
  
  <p>Desired output is:</p>
  
  <pre><code>LeafID    count       pidx     pidy    final_score
     1       10           10        20
     1       20           10        20
     1       40           10        20
     6       50           10        43
     1       20           20        12
     3       30           20        54
     1       70           20        23
  </code></pre>