title: Calculate dates differences in months beetwen dates in a groupby
body: <p>I have the following dataframe:</p>
  <pre><code>Id, country, date
  1, ar, 2019-01-01
  1, ar, , 2019-02-01
  1, ar, 2019-03-01
  1, it, , 2019-01-01
  1, it, , 2019-02-01
  1, it, 2019-03-01
  1, it, , 2019-04-01
  1, it, 2019-03-01
  2, ar, 2019-01-01
  2, ar, , 2019-02-01
  2, ar, 2019-03-01
  2, it, , 2019-01-01
  2, it, , 2019-02-01
  3, it, 2019-03-01
  3, it, , 2019-04-01
  4, it, 2019-05-01
  </code></pre>
  <p>I need to group by Id, country and calculate the difference beetwen the dates (in months) for each group.</p>
  <p>I tried:</p>
  <pre><code>df['daysdiff'] = df.sort_values('date').groupby(['id','country'])['date'].diff()
  </code></pre>
  <p>But it get the diff in days. I need the diff in months. I think dividing 'daysdiff' by 30 it's not accurate because of months have different numbers of days...and leap-years...</p>
  <p>Any help is welcome!</p>