title: Faster than double for loop on Counter object
body: <p>I want to do a double loop on a Counter object, which is the result of two different counters subtraction.
  My counter is like this:</p>
  <pre><code>{'sun': 5,
   'abstract': 0.0,
   'action': 10,
   'ad': 0.0,
    ....}
  </code></pre>
  <p>And I have a dataframe like:</p>
  <pre><code>    0           1   
  0   sun         sunlight        
  2   river       water   
  3   stair       staircase
  4   morning     sunrise 
  n   ......
  </code></pre>
  <p>My purpose is to to keep in the dataframe only couples of words which the first word of the row have 0 of frequency and the second more than 0 (or the contrary, more than zero the first and 0 the second, so excluding couples both of 0 frequency or both of more than zero frequency).</p>
  <p>I've tried to do this, but it is too slow (it will take more than 5 hours to complete):</p>
  <pre><code>for i,j in counter_diff.items():       #extract i word and j counter number of a item
    for t,k in counter_diff.items():     #extract t word and k counter number of a item
      for s in range(len(df)):
        if ((df[0][s] == i and j==0) and (df[1][s] == t and k==0)):
          df = df.drop([s])
        elif ((df[0][s] == i and j&gt;0) and (df[1][s] == t and k&gt;0)):
          df = df.drop([s])
      df = df.reset_index(drop=True)
  </code></pre>
  <p>Have you any suggestion of a better way to do it?
  Thank you for your time!</p>