title: Pandas: Delete rows of a DataFrame if total count of a particular column occurs only 1 time
body: <p>I'm looking to delete rows of a DataFrame if total count of a particular column occurs only 1 time</p>
  
  <p>Example of raw table (values are arbitrary for illustrative purposes):</p>
  
  <pre><code>print df
  
       Country     Series          Value
  0    Bolivia     Population      123
  1    Kenya       Population      1234
  2    Ukraine     Population      12345
  3    US          Population      123456
  5    Bolivia     GDP             23456
  6    Kenya       GDP             234567
  7    Ukraine     GDP             2345678
  8    US          GDP             23456789
  9    Bolivia     #McDonalds      3456
  10   Kenya       #Schools        3455
  11   Ukraine     #Cars           3456
  12   US          #Tshirts        3456789
  </code></pre>
  
  <p>Intended outcome:</p>
  
  <pre><code>print df
  
       Country     Series          Value
  0    Bolivia     Population      123
  1    Kenya       Population      1234
  2    Ukraine     Population      12345
  3    US          Population      123456
  5    Bolivia     GDP             23456
  6    Kenya       GDP             234567
  7    Ukraine     GDP             2345678
  8    US          GDP             23456789
  </code></pre>
  
  <p>I know that <code>df.Series.value_counts()&gt;1</code> will identify which <code>df.Series</code> occur more than 1 time; and that the code returned will look something like the following:</p>
  
  <pre><code>     Population 
             True
       GDP
             True
       #McDonalds
            False
       #Schools
            False
       #Cars
            False
       #Tshirts
            False
  </code></pre>
  
  <p>I want to write something like the following so that my new DataFrame drops column values from df.Series that occur only 1 time, but this doesn't work:
  <code>df.drop(df.Series.value_counts()==1,axis=1,inplace=True)</code></p>