title: Using value_counts with False/True. How to get false/true = 0 when there is any false or true
body: <p>I am writing an application that generates a report. One part of the output shows how many matches are between two columns (match = True, no match = False). In order to do that I use <code>df.column.value_counts()</code> which output is</p>
  <pre><code>False    2
  True     1
  Name: column, dtype: int64
  </code></pre>
  <p>So I was thinking to show the result in the report something like</p>
  <pre><code># This is a simplify example
  print(&quot; Position with same genotype: &quot;, df.column.value_counts()[1])
  print(&quot; Position with different genotype: &quot;, df.column.value_counts()[0])
  </code></pre>
  <p>I have noticed that the order of this output change depending on what False or True is found first in the table ( I think I can solve this with sort ). However, another bigger concern I am thinking of is if there is no False or non True are found in the table the output is:</p>
  <pre><code># For example not Falses
  True     3
  Name: column, dtype: int64
  </code></pre>
  <p>I was expected this:</p>
  <pre><code># For example not Falses
  True     3
  False    0
  Name: column, dtype: int64
  </code></pre>
  <p>How can I solve this to avoid future errors? It is quite unlike that happen, it is going to be at least one false or true but I want to be sure that not error happens as this application is going to be run many times with different samples so theoretically  this situation can happen.</p>