title: Filter a 2 columns of a DataFrame using a dictionary containing lists Python
body: <p>I have a pandas dataframe of employees that I need to filter based on 2 columns. I need to filter on department and level. So let's say we have department 'Human Resources' and within that it has level 1,2,3,4,5. I'm specifically looking for Human Resources level 2,4 and 5.</p>
  
  <p>I have my desired departments and levels stored in dictionary, for example:</p>
  
  <pre><code>departments = dict({'Human Resources' : ['2','4','5'] ,'IT' : ['1','3','5','6'], etc.... })
  </code></pre>
  
  <p>My dataframe will list every employee, for all departments and for all levels (plus lots more). I now want to filter that dataframe using the dictionary above. So in the Human Resources example, I just want returned the employees who are in 'Human Resouces' and are in levels 2, 4 and 5.</p>
  
  <p>An example of the df would be:</p>
  
  <pre><code>employee_ID   Department        Level
          001   Human Resources   1
          002   Human Resources   1
          003   Human Resources   2
          004   Human Resources   3
          005   Human Resources   4
          006   Human Resources   4
          007   Human Resources   5
          008   IT                1
          009   IT                2
          010   IT                3
          011   IT                4
          012   IT                5
          013   IT                6
  </code></pre>
  
  <p>Using the dictionary I've displayed above, my expected result would be</p>
  
  <pre><code>employee_ID   Department        Level
          003   Human Resources   2
          005   Human Resources   4
          006   Human Resources   4
          007   Human Resources   5
          008   IT                1
          010   IT                3
          012   IT                5
          013   IT                6
  </code></pre>
  
  <p>I have no idea how I'd do this?</p>