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    <p>Based on your code, I would guess that this would work the full data set (depending on your system's memory): </p> <pre><code>chr1 &lt;- 33132539 window &lt;- 100 pos &lt;- cut(1:chr1, seq(0, chr1, window)) meanrho.chr1 &lt;- tapply(spe$rho, INDEX = pos, FUN = mean) </code></pre> <p>I think you want a factor that defines groups of intervals for every 100 within the first column (<code>rho</code>), and then you can use the standard apply family of functions to get means within groups. </p> <p>Here is the data you posted in reproducible form. </p> <pre><code>spe &lt;- structure(list(pos = c(5380L, 5390L, 5393L, 5404L, 5428L, 5437L, 5440L, 5443L, 5459L, 5463L, 5480L, 5521L, 5538L, 5584L, 5673L, 5720L, 5841L, 5880L, 5913L, 5958L), rho = c(30.07383, 30.87, 0.07383, 6, 30.07383, 1, 9, 30.07383, 6, 30.07383, 7, 30.07383, 0, 20, 30.07383, 30.07383, 3, 30.07383, 4, 30.07383)), .Names = c("pos", "rho"), row.names = c(NA, -20L), class = "data.frame") </code></pre> <p>Define the intervals with <code>cut</code>, we just want every 100th value (but you might want the details tweaked as per your code for your real data set). </p> <pre><code>pos.index &lt;- cut(spe$pos, seq(0, max(spe$pos), by = 100)) </code></pre> <p>Now pass the desired function (<code>mean</code>) over each group. </p> <pre><code>tapply(spe$rho, INDEX = pos.index, FUN = mean) </code></pre> <p>(Lots of NAs since we didn't start at 0, then)</p> <pre><code>(5.2e+03,5.3e+03] (5.3e+03,5.4e+03] (5.4e+03,5.5e+03] (5.5e+03,5.6e+03] (5.6e+03,5.7e+03] (5.7e+03,5.8e+03] (5.8e+03,5.9e+03] 20.33922 14.90269 16.69128 30.07383 30.07383 16.53692 </code></pre> <p>(Add other arguments to FUN, such as na.rm as necessary, e.g:)</p> <pre><code>## tapply(spe$rho, INDEX = pos.index, FUN = mean, na.rm = TRUE) </code></pre> <p>See <code>?tapply</code> applying over groups in a vector (ragged array), and <code>?cut</code> for ways to generate grouping factors.</p>
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    1. POEfficiently average the second column by intervals defined by the first column
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    1. USmdsumner
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    1. CODear mdsumner, thanks a lot for your kind explanation. I learned much from you code, like cut().
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