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POAggregate (count) occurences of values over arbitrary timeframe
 

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    <p>I have a CSV file with timestamps and certain event-types which happened at this time. What I want is count the number of occurences of certain event-types in 6-minutes intervals.</p> <p>The input-data looks like:</p> <pre><code>date,type "Sep 22, 2011 12:54:53.081240000","2" "Sep 22, 2011 12:54:53.083493000","2" "Sep 22, 2011 12:54:53.084025000","2" "Sep 22, 2011 12:54:53.086493000","2" </code></pre> <p>I load and cure the data with this piece of code:</p> <pre><code>&gt; raw_data &lt;- read.csv('input.csv') &gt; cured_dates &lt;- c(strptime(raw_data$date, '%b %d, %Y %H:%M:%S', tz="CEST")) &gt; cured_data &lt;- data.frame(cured_dates, c(raw_data$type)) &gt; colnames(cured_data) &lt;- c('date', 'type') </code></pre> <p>After curing the data looks like this:</p> <pre><code>&gt; head(cured_data) date type 1 2011-09-22 14:54:53 2 2 2011-09-22 14:54:53 2 3 2011-09-22 14:54:53 2 4 2011-09-22 14:54:53 2 5 2011-09-22 14:54:53 1 6 2011-09-22 14:54:53 1 </code></pre> <p>I read a lot of samples for xts and zoo, but somehow I can't get a hang on it. The output data should look something like:</p> <pre><code>date type count 2011-09-22 14:54:00 CEST 1 11 2011-09-22 14:54:00 CEST 2 19 2011-09-22 15:00:00 CEST 1 9 2011-09-22 15:00:00 CEST 2 12 2011-09-22 15:06:00 CEST 1 23 2011-09-22 15:06:00 CEST 2 18 </code></pre> <p>Zoo's aggregate function looks promising, I found this code-snippet:</p> <pre><code># aggregate POSIXct seconds data every 10 minutes tt &lt;- seq(10, 2000, 10) x &lt;- zoo(tt, structure(tt, class = c("POSIXt", "POSIXct"))) aggregate(x, time(x) - as.numeric(time(x)) %% 600, mean) </code></pre> <p>Now I'm just wondering how I could apply this on my use case.</p> <p>Naive as I am I tried:</p> <pre><code>&gt; zoo_data &lt;- zoo(cured_data$type, structure(cured_data$time, class = c("POSIXt", "POSIXct"))) &gt; aggr_data = aggregate(zoo_data$type, time(zoo_data$time), - as.numeric(time(zoo_data$time)) %% 360, count) Error in `$.zoo`(zoo_data, type) : not possible for univariate zoo series </code></pre> <p>I must admit that I'm not really confident in R, but I try. :-)</p> <p>I'm kinda lost. Could anyone point me into the right direction?</p> <p>Thanks a lot! Cheers, Alex.</p> <p>Here the output of dput for a small subset of my data. The data itself is something around 80 million rows.</p> <pre><code>structure(list(date = structure(c(1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885, 1316697885), class = c("POSIXct", "POSIXt"), tzone = ""), type = c(2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L)), .Names = c("date", "type"), row.names = c(NA, -23L), class = "data.frame") </code></pre>
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    1. COFirst of all, thanks for all the responses so far! I'm now going to go through the different hints you provided and let you know how far I get.
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