title: Pandas pivot_table not behaving as expected when having few different values in groupby.count
body: <p>I want to make a pivot table after grouping and counting the number of uniqueid per day and per license. This is what I usually use and it produces the expected result :</p>
  
  <pre><code>import pandas as pd
  
  raw_data = {'day' : ['Monday','Monday','Monday','Monday','Monday'], 
              'license':['A','A','C','B','B'],
              'uniqueid':[123,352,737,368,901]}
  df = pd.DataFrame(raw_data).groupby(['day','license']).count()
  pivot = df.pivot_table(index = 'day', columns = 'license', values = ['uniqueid'])
  pivot
  </code></pre>
  
  <p>Result :</p>
  
  <pre><code>        uniqueid      
  license        A  B  C
  day                   
  Monday         2  2  1
  </code></pre>
  
  <p>But if I change the 'C' license for a 'B' license in raw_data, I get the following :</p>
  
  <pre><code>         uniqueid
  day             2
  license         3
  </code></pre>
  
  <p>I would have liked to get the same result as before, minus the 'C' column. </p>
  
  <p>The problem seems to be in the pivot_table function, because the groupby/count function returns me properly separated data. It also works if I have two or more types of day. Any advice? Thank you!</p>