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POAdd and fill in rows based on data above/below
 

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    <p>I've got a data set that looks like this:</p> <pre><code>Date&lt;-c("2009-05-1 10:00:00","2009-05-1 10:05:00","2009-05-1 10:10:00", "2009-05-1 10:15:00","2009-05-1 10:20:00","2009-05-1 10:25:00") Dates&lt;-strptime(Date, "%Y-%m-%d %H:%M:%S") DF&lt;-data.frame(Dates,X=1:6, Y=1:6) DF Dates X Y 1 2009-05-01 10:00:00 1 1 2 2009-05-01 10:05:00 2 2 3 2009-05-01 10:10:00 3 3 4 2009-05-01 10:15:00 4 4 5 2009-05-01 10:20:00 5 5 6 2009-05-01 10:25:00 6 6 </code></pre> <p>As is, the time stamp is every 5 minutes. But I need to have a data set that is every minute, so I'm looking to first add in the missing minute data, and then estimate the <code>X</code> and <code>Y</code> column data. With the <code>X</code> column being a simple fill of the data above, and the <code>Y</code> being an average of the above/below data.</p> <p>The results would hopefully look like this:</p> <pre><code> Dates X Y 2009-05-01 10:00:00 1 1 2009-05-01 10:01:00 1 1.5 2009-05-01 10:02:00 1 1.5 2009-05-01 10:03:00 1 1.5 2009-05-01 10:04:00 1 1.5 2009-05-01 10:05:00 2 2 2009-05-01 10:06:00 2 2.5 2009-05-01 10:07:00 2 2.5 2009-05-01 10:08:00 2 2.5 2009-05-01 10:09:00 2 2.5 2009-05-01 10:10:00 3 3 2009-05-01 10:11:00 3 3.5 2009-05-01 10:12:00 3 3.5 2009-05-01 10:13:00 3 3.5 2009-05-01 10:14:00 3 3.5 2009-05-01 10:15:00 4 4 2009-05-01 10:16:00 4 4.5 2009-05-01 10:17:00 4 4.5 2009-05-01 10:18:00 4 4.5 2009-05-01 10:19:00 4 4.5 2009-05-01 10:20:00 5 5 2009-05-01 10:21:00 5 5.5 2009-05-01 10:22:00 5 5.5 2009-05-01 10:23:00 5 5.5 2009-05-01 10:24:00 5 5.5 2009-05-01 10:25:00 6 6 </code></pre> <p>Any thoughts on how to go about doing this would be greatly appreciated.</p>
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    1. USVinterwoo
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    1. COWhy do you need to have it at each minute? (It doesn't add any information...)
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      1. USDavid Robinson
    2. COI was going to merge this data set with several others, all of which are by the minute. So I know it's cheating, but it's the only thing I can think to do.
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      1. USVinterwoo
    3. COIn that case, you should probably do a smoother to interpolate the values rather than assigning all the mid-row `Y`s to be the same average value. For example, in this case you want `Y` to look like `1, 1.2, 1.4, 1.6, 1.8, 2, 2.2, 2.4, 2.6...` You could use [smooth.spline](http://stat.ethz.ch/R-manual/R-patched/library/stats/html/smooth.spline.html) for that (your "x" in this case is the time). But even doing a strict linear interpolation between each pair of values (like `1, 1.2, 1.4` above) would make it a lot better.
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      1. USDavid Robinson
 

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