On Nov 21, 2007, at 1:24 PM, Thibaut Jombart wrote: > Alexy Khrabrov wrote: > >> I get tables with millions of rows. For plotting to a screen-size >> jpg, obviously just about 1000 points are enough. Instead of feeding >> plot() the original millions of rows, I'd rather shrink the original >> dataframe, using some kind of the following interpolation: >> >> -- split dataframe into chunks of N rows each, e.g. 1000 rows each >> -- compute average for each column >> -- issue one new row of those averages into the shrunk result >> >> Is there any existing package to do that in R? Otherwise, which R >> idioms are most effective to achieve that? >> >> Cheers, >> Alexy
>> if you want to extract relevant information from such a table, >> splitting > rows in arbitrary chuncks may not solve your problem. Ordinations in > reduced space are designed for that kind of task, but hierachical > clustering may also help. See Legendre & Legendre (1998, Numerical > Ecology, Elsevier) for examples of such methods in Ecology, and the R > packages ade4, vegan and hclust. Well, in this case the function is monotonically decreasing, and so averages would do fine just to plot the curve. What I'm after is an R way -- preferably functional -- to split a vector into chunks of N elements and issue a new vector of the averages of those chunks. Cheers, Alexy ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
