title: Is it possible to use pandas.DataFrame.rolling with a step greater than 1?
body: <p>In R you can compute a rolling mean with a specified window that can shift by a specified amount each time.</p>
  <p>However maybe I just haven't found it anywhere but it doesn't seem like you can do it in pandas or some other Python library?</p>
  <p>Does anyone know of a way around this? I'll give you an example of what I mean:</p>
  <p><a href="https://i.stack.imgur.com/zUtKT.png" rel="noreferrer"><img src="https://i.stack.imgur.com/zUtKT.png" alt="example" /></a></p>
  <p>Here we have bi-weekly data, and I am computing the two month moving average that shifts by 1 month which is 2 rows.</p>
  <p>So in R I would do something like: <code>two_month__movavg=rollapply(mydata,4,mean,by = 2,na.pad = FALSE) </code>
  Is there no equivalent in Python?</p>
  <p>EDIT1:</p>
  <pre><code>DATE  A DEMAND   ...     AA DEMAND  A Price
      0  2006/01/01 00:30:00  8013.27833   ...     5657.67500    20.03
      1  2006/01/01 01:00:00  7726.89167   ...     5460.39500    18.66
      2  2006/01/01 01:30:00  7372.85833   ...     5766.02500    20.38
      3  2006/01/01 02:00:00  7071.83333   ...     5503.25167    18.59
      4  2006/01/01 02:30:00  6865.44000   ...     5214.01500    17.53
  </code></pre>