similar to: Plot overview xy plots from data frame?

Gracias, Carlos. Habia pensado en algo similar usando sapply(): sapply(seq(1, ncol(vtmp), by = 2), function(i) c(rbind(as.character(vtmp[, i]), as.character(vtmp[, i+1])))) Dependiendo de la dimension de los datos, quizas mapply() sea mas eficiente que sapply(). Saludos cordiales, Jorge.- 2015-02-25 1:01 GMT+11:00 Carlos Ortega <cof en qualityexcellence.es>: > Hola, > > Este

Hola, 0. La falta de 'elegancia' hace que sea mas dificil hacer cambios al codigo. Por ejemplo cambiar n.classrooms <- 4 a n.classrooms <- 20 1. Cuando tengo solo 4 puedo hacer esto: schoolGrade$A <- Teachers$Teacher.ID[1:cuttoff1] schoolGrade$B <- Teachers$Teacher.ID[1:cuttoff1] schoolGrade$C <- Teachers$Teacher.ID[(cuttoff1+1):n.teachers] schoolGrade$D <-

Perdon por no se lo suficientemente claro :( Tu codigo produce `validPairs` que tiene 7 variables y 360 observaciones. Donde > validPairs[1,] V1 V2 V3 V4 V5 V6 valid 60 e1 g1 c1 e1 g1 c2 Valid indica que un maestro tiene asignado c1 y c2 en la escuela e1 y el grado g1. Correcto? Si es asi, esto es casi lo que queira producir y creo que puedo llegar a donde quiero usando tu codigo de base.

Gracias Carlos, Tu codigo es un gran paso en el sentido correcto pero no produce exactamente lo que estoy buscando. Mi "solucion" en stackoverflow <http://stackoverflow.com/questions/31137940/randomly-assign-teachers-to-classrooms-imposing-restrictions/31143808#31143808> produce un data frame `schoolGrade` con 240 observaciones y 7 variables. Mi objetivo es poder generar un data

Excelente! Ahora corre muy rápido. No conocía ese método, creo que me va a resultar muy útil. Muchas gracias y saludos. Fernando Macedo El 24/02/15 a las 10:51, Jorge I Velez escribió: Fernando, Podrias intentar R> a <- rep('a', 5) R> b <- rep('b', 5) R> a [1] "a" "a" "a" "a" "a" R> b [1] "b"

Hi All, I have been able to modify the x-axis to start at zero by adding xlow and xhigh parameters; that was pretty simple. I have been unable to find the location of the code that would turn off the information weighting of the box size (I have smaller randomized trials getting less weight than a much larger non-randomized trial). The function is forestplot() from rmeta. Thanks for any

I am trying to age standardize using the svystandardize package in R. I have successfully managed to hit my SUDAAN based targets for estimates by sex, but not the total. The total is only a little different, but I'd like some help knowing why it isn't exact. I've included the SUDAAN code that generates the targets and my R script (and output) that I have so far. I can't supply the

On Wed, 30 Jul 2003 TSudler at ch.imshealth.com wrote: <SNIP> table1 <- tkwidget(tt,"table",variable="tclArray", rows=as.character(dim(datifram)[1]+1), cols=as.character(dim(datifram)[2]),titlerows="1", titlecols="3",selectmode="extended",height="27",

Hi all, I'm new to PCA in R, so this might be a basical thing, but I cannot find anything on the net about it. I need to make a PCA plot with two response variables (df$resp1 and df$resp2) against eight metabolites (df$met1, df$met2, ...) and I don't have a clue how to do... and I've only used the simplest PCAs before, like this: pcaObj=prcomp(t(df[idx, c(40:47)]))

how can I import/export data from ms excel? also is there a way to import/export data of the hdf format? is there a way to import/export hdf format for ms excel as well? thank you very much in advance. /js ###################################################################### This e-mail message has been scanned and cleared by MailMarshal http://www.marshalsoftware.com

Hi all, I'm have a matrix (X) with observations as rows and parameters as columns. I'm trying to exchange all missing values in a column by the column mean using the code below, but so far, nothing happens with the NAs... Can anyone see where the problem is? N<-nrow(X) # Calculate number of rows = 108 p<-ncol(X) # Calculate number of columns = 88 # Replace by columnwise

Hi all, I'm searching for a way to exclude outliers from my dataset while making xyplots. While plotting using pairs(), I exclude specific row in my data frame and save the settings as a variable which I later include as an argument: # Discard outliers and save settings as idx idx=with(fieldTrial0809, which(Pro>0 & Pro<0.95 & Fum>0 & Fum<0.4 & Mal>0.1 &

Dear expeRts, In the minimal example below, I have a data.frame containing three "blocks" of years (the years are subsets of 2000 to 2002). For each year and block a certain "value" is given. I would like to create a matrix that has row names given by all years ("2000", "2001", "2002"), and column names given by all blocks ("a",

Hi all, I would like to remove rows from a matrix, based on the frequency of missing values. If there are more than 10 % missing values, the row should be deleted. I use the following to calculate the frequencies, thereby getting a new matrix with the frequencies: freqNA=rowMeans(is.na(exprdata)) But is there a shorter way to remove the rows based on "(1-freqNA)>0.1"

Hi all, Does anyone know how to get the independent components and loadings from an Independent Component Analysis (ICA), as well as principal components and loadings from a Pricipal Component analysis (PCA) using the fastICA package? Or perhaps if there's another way to do ICAs in R? Below is an example from the fastICA manual (http://cran.r-project.org/web/packages/fastICA/fastICA.pdf)

Hi all, I need to replace missing values in a matrix by 10 % of the lowest available value in the matrix. I've got a function I've used earlier to replace negative values by the lowest value, in a data frame, but I'm not sure how to modify it... nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values to a small value, close to zero { min.val =

Hi all, I'm doing Multiple linear regression for a data set. However, it takes a lot of time, as I would like to check every possible combination of factors, evalute the results based for instance on their p values, and then choose the best regression model. So, I wonder if anyone might have a script for that? Or if not, do you have some suggestions how to create such a script? I've

Hi all, I guess this might be an easy question, but I've searched multiple help pages without finding any answear... so now I put my trust in you! I have a data frame (36 variables and 556 observations). One column contains three factors, and I would like to divide the data frame into three new ones, based on the value of the factors, thereby having only one value for all elements of the

Hi all, I'm making a PCA plot with eight variables (columns taken from a larger data frame "fieldTrial0809[idx,c(39:46)]"). I then want the symbols in the plot to be colored as a gradient from red to blue, depending on the value of another column in "fieldTrial0809[idx, c(48)]" containg temperatures from -12.1 to -5.4. I don't want to use the heat.colors(n)

Hi, I'm trying to plot a map with the location of the stations that I am using require(MASS)require(maps) mapaBrasil <- read.table("BASE_BR.txt",sep="") latlonRS <- read.csv2("coordenadas.txt",h=F,sep="") png(filename="mapa_grupos.png",width=600,height=800) # criating a map for RSmap(xlim=c(-80,-35),ylim=c(-45,10),