title: Clean way to convert quarterly periods to datetime in pandas
body: <p><strong>EDIT:</strong><br>
  If you're coming to this question and your string looks like <code>1996-Q1</code>, then just use <code>pd.to_datetime(df['Quarter'])</code> to convert it to a proper pandas datetime. This question is about solving all the quarter dates that are not in this standard format.</p>
  <p><strong>ORIGINAL QUESTION:</strong><br>
  I'm looking for a nice, readable and understandable way (one that you can remember for the next time) to convert <code>Q3 1996</code> to a pandas datetime, for example <code>1996-07-01</code> in this case.
  Until now I found this, but it's mighty ugly:</p>
  <pre><code>df = pd.DataFrame({'Quarter':['Q3 1996', 'Q4 1996', 'Q1 1997']})
  ​
  df['date'] = (
      pd.to_datetime(
          df['Quarter'].str.split(' ').apply(lambda x: ''.join(x[::-1]))
  ))
  ​
  print(df)
     Quarter       date
  0  Q3 1996 1996-07-01
  1  Q4 1996 1996-10-01
  2  Q1 1997 1997-01-01
  </code></pre>
  <p>I was hoping the following would work, because it's readable, but unfortunately it doesn't:</p>
  <pre><code>df['date'] = pd.to_datetime(df['Quarter'], format='%q %Y')
  </code></pre>
  <p>The problem is also that quarter and year are apparently in the wrong order for pandas to do simple processing.</p>
  <p>Can anyone help me find a cleaner way of converting <code>Q3 1996</code> to a pandas datetime?</p>