Pandas Rolling Window - datetime64[ns] are not implemented
<p>I'm attempting to use Python/Pandas to build some charts.  I have data that is sampled every second.  Here is a sample:</p>

<pre><code>Index, Time, Value

31362, 1975-05-07 07:59:18,  36.151612
31363, 1975-05-07 07:59:19,  36.181368
31364, 1975-05-07 07:59:20,  36.197195
31365, 1975-05-07 07:59:21,  36.151413
31366, 1975-05-07 07:59:22,  36.138009
31367, 1975-05-07 07:59:23,  36.142962
31368, 1975-05-07 07:59:24,  36.122680
</code></pre>

<p>I need to create a variety of windows to look at the data. 10, 100, 1000 etc.  Unfortunately when I attempt to window the entire data frame I get the error below...</p>

<pre><code>NotImplementedError: ops for Rolling for this dtype datetime64[ns] are not implemented
</code></pre>

<p>I checked out these docs: <a href="http://pandas.pydata.org/pandas-docs/stable/computation.html" rel="noreferrer">http://pandas.pydata.org/pandas-docs/stable/computation.html</a> as a reference, and they appear to be doing this on date ranges.  I did notice that the data type between what they have and what I have is different.</p>

<p>Is there an easy way to do this?</p>

<p>This is ideally what I'm trying to do:</p>

<pre><code>tmp = data.rolling(window=2)
tmp.mean()
</code></pre>

<p>I'm using plotly to plot the raw data and then the windowed data on top of it.  My goal is to find ideal windows for identifying cleaner trends in the data removing some of the noise.</p>

<p>Thanks!</p>

<p>Additional Notes:</p>

<p>I think I need to take my data from this format:</p>

<p>pandas.core.series.Series 
to this one:</p>

<p>pandas.tseries.index.DatetimeIndex</p>