similar to: from "table" to "dataframe"

It is easy to force a table into a data.frame and still keep the tabular structure, but I am not sure why you would want to do that. data.frame(df2[]) The columns of a data.frame are independent variables. The columns of df2 don't stand on their own. ---- Original message ---- >Date: Tue, 5 Dec 2006 15:33:13 +0000 (GMT) >From: Milton Cezar Ribeiro <milton_ruser at yahoo.com.br>

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Hi there, I have a binary matrix (dim 100x100) filled with values 0 and 1. I need select a record "n" positions of that matrix when values are 1. How can I do that? Thanks for all, Miltinho Brazil --------------------------------- [[alternative HTML version deleted]]

Dear all, I have a so large image (43,000 x 18,000 pixels) and I need clip this image with a smallest one (1000x1000 pixels). I can read the second image using rgdal package. But the first image can´t be read on my system because if memory limitation (I have about 2GB availabe). So I would like hear from you if anyone have some suggestin in this regards. I have also ArcGis 8.6 ans Erdas 8.3

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Hi there, I´m trying to use "simecol" package but I got the error showed below. I´m runnig R version 2.4.0 (2006-10-03). Kind regards, miltinho Brazil --- > require(simecol) Loading required package: simecol Error in loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : in 'simecol' methods specified for export, but

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Dear all, Every time that I need to generate I plot output as figure I use something like png("myoutput.png") plot(rnorm(100)*1.0,col=4) points(rnorm(100)*0.5,col=2,pch=0) dev.off() But now I need to generate a lot of outputs and it could not be done in a for looping where I can change the names. So I would like to know if is there a way of I automatically redirect the output from my

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Dear R-friends, I have to simple questions. First I would like to exclude some columns from a dataframe and after I need select rows that satisfy some conditions. My data frame looks like Region Species Bodysize Weigth Age Africa Sp1 10.2 20 2 Africa Sp2 12.2 12 2 Africa Sp3 15.3 18 3 Africa Sp4 11.5 40 4 Brazil Sp1 10.2 40 3 Brazil Sp2 22.2 32 2 Brazil Sp3 12.3