title: Pandas: Sort a dataframe based on multiple columns
body: <p>I know that this question has been asked several times. But none of the answers match my case.</p>
  
  <p>I've a pandas dataframe with columns,department and employee_count. I need to sort the employee_count column in descending order. But if there is a tie between 2 employee_counts then they should be sorted alphabetically based on department.</p>
  
  <pre><code>   Department Employee_Count
  0    abc          10
  1    adc          10
  2    bca          11
  3    cde          9
  4    xyz          15
  
  required output:
  
     Department Employee_Count
  0    xyz          15
  1    bca          11
  2    abc          10
  3    adc          10
  4    cde          9
  </code></pre>
  
  <p>This is what I've tried.</p>
  
  <pre><code>df = df.sort_values(['Department','Employee_Count'],ascending=[True,False])
  </code></pre>
  
  <p>But this just sorts the departments alphabetically.</p>
  
  <p>I've also tried to sort by Department first and then by Employee_Count. Like this:</p>
  
  <pre><code>df = df.sort_values(['Department'],ascending=[True])
  df = df.sort_values(['Employee_Count'],ascending=[False])
  </code></pre>
  
  <p>This doesn't give me correct output either:</p>
  
  <pre><code>   Department Employee_Count
  4    xyz          15
  2    bca          11
  1    adc          10
  0    abc          10
  3    cde          9
  </code></pre>
  
  <p>It gives 'adc' first and then 'abc'.
  Kindly help me.</p>