similar to: Averaging dataframes that are stored in a list

Hi, I am trying to merge data similar to the example data below > dat0 id var1 var2 var3 2 1 0 1 3 1 0 1 4 0 1 1 5 0 1 1 > dat1 id var4 var5 var6 2 1 0 1 3 1 0 1 6 0 1 1 7 0 1 1 > dat2 id

Dear R helpers   Following is a part of R code.   data_lab <- expand.grid(c("R11", "R12", "R13"), c("R21", "R22", "R23"), c("R31", "R32", "R33"), c("R41", "R42", "R43"), c("R51", "R52", "R53"), c("R61", "R62", "R63"),

Dear R-helpers: I am an R newbie and have a question related to writing functions that accept unlimited number of input arguments. (I tried to peek into functions such as paste and cbind, but failed, I cannot see their codes..) Can someone kindly show me through a summation example? Say, we have input scalar, 1 2 3 4 5 then the ideal function, say sum.test, can do

Dear all, I have a dataset that looks like this: x <- read.table(textConnection("col1 col2 3 1 2 2 4 7 8 6 5 10"), header=TRUE) I want to rewrite it as below: var1 var2 var3 var4 var5 var6 var7 var8 var9 var10 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0

Hi, I need to draw a line segment between two points on different plots in the same multigraph.I've tried looking at the zoominplot function in plotrix but havent understood much.any help is appreciated ~Aks [[alternative HTML version deleted]]

Dear All, I have a problem which *should* be pretty straightforward to resolve - but I can't work out how! I have a list of 3 coefficient estimates for 4 different datasets: Coefs<-list(c(1,0.6,0.5),c(0.98,0.65,0.4),c(1.05,0.55,0.45),c(0.99,0.50,0.47)) All I want to do is take the sum (or mean) of each coefficient across the 4 datasets. I can do this using a "for" loop, but

Hi, I wonder whether there is a way to generate a polygon (a triangle in my case) with color gradient using grid.polygon() in package grid? I tried something like library(grid) grid.polygon(x=c(0, 0.5, 1), y=c(0.5, 1, 0.5), gp=gpar(col=NA, fill=colorRampPalette(c("green", "lightgray"), space="Lab")(200))) But am only

I'm sure this is easy, but I'm having a hard time figuring out how to recode some data in R. I have a variable "numpeers" which is valued 1, 2, or 3. I also have three other variables called "w9zd9_1," "w9zd9_2," and "w9zd9_3." I want to use these variables to create a new item called "distot." Specifically, here is what I want to do:

Dear useRs, I have a list, each entry of which is a matrix of constant dimensions. Is there a good way (i.e., not using a for loop) to apply a mean to each matrix entry *across list entries*? Example: foo <- list(rbind(c(1,2,3),c(4,5,6)),rbind(c(7,8,9),c(10,11,12))) some.sort.of.apply(foo,FUN=mean) I'm looking for a componentwise mean across the two entries of foo, i.e., the

I have a dataframe called "data" with 5 records (in rows) each of which has been scored on each of many variables (in columns). Five of the variables are named var1, var2, var3, var4, var5 using headers. The other variables are named using other conventions. I can create a new variable called var6 with the value 15 for each record with this code: > var6=var1+var2+var3+var4+var5

Hello R-helpers, I have 10 dataframes (named data1, data2, ... data10) and I would like to add 5 new columns to each dataframe using the following code: data1$LogDepth<-log10(data1[,2]/data1[,4]) data1$LogArea<-log10(data1[,3]/data1[,5]) data1$p<-2*data1[,6]/data1[,7] data1$Exp<-data1[,2]^(2/data1[,8]) data1$s<-data1[,3]/data1[,9] ...but I would prefer not to repeat this chunk of

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Hello, I have a large data set that has more columns than rows (sample data below). I am trying to perform a partitioning cluster analysis and then plot that using pca. I have tried using CLUSPLOT(), but that only allows for 'princomp' where I need 'prcomp' as I do not want to reduce my columns. Is there a way to edit the CLUSPLOT() code to use 'prcomp', please? #

var1 var2 var3 var4 var5 var6 var7 var8 var9 var10 gold 2 3 1 2 4 0 1 4 4 3 2 2 4 2 4 3 4 2 4 4 4 2 3 3 0 0 4 1 0 2 4 4 2 1 4 0 3 2 0 0 2 4 4 2 3 4 0 2 2 0 0 0 3 4 2 2 2 3 2 2 0 0 0 2 4 2 2 4 1 1 2 0 0 3 3 3 2 3 4 1 4 0 0 0 0 3 4 2 3 1 0 2 2 1 0 2 3 3 2 0 3 1 1 1 1 2 1 2 3 2 1

Hello, I have trouble converting a character string to a R object. Let me describe this by an example; > dim(a) [1] 270 14 > dim("a") NULL > names(a) [1] "Var1" "Var2" "Var3" "Var4" "Var5" "Var6" "Var7" "Var8" "Var9" [10] "Var10" "Var11" "Var12"

Hi R-helpers, I have a dataframe with 60columns and I would like to convert several columns to factor, others to numeric, and yet others to dates. Rather than having 60 lines like this: data$Var1<-as.factor(data$Var1) I wonder if it's possible to write one line of code (per data type, e.g. factor) that would apply a function (e.g., as.factor) to several (non-contiguous) columns. So, I

Dear all, I have a dataframe with 132 columns and 100 rows. Every 2nd column is a repeat measurement so that the columns could be titled, a a b b c c d d etc. I would like to average the repeats such that I am left with a data frame of 66 columns (of means) and 100 rows. I have been trying to use rowMeans but have not been able to average the pairs of columns, only the whole dataframe. Any

Hi, I've used the following command in qplot qplot(a$V1,geom="histogram",binwidth=0.15,fill = factor(a$V2),ylab="Frequency",xlab="Rate"); but the title in the legend shows up as factor(a$V2)...how can i change this? -- Rajesh.J [[alternative HTML version deleted]]

Hi, I have a graph with seven parallel horizontal lines. Is it possible to shade the area between two adjacent lines? Thank you in advance, Hannu

Dear list, I've written a function that plots subjects. Something like: myplot <- function(subject) { plot(subject) } Subjects are vectors, e.g. ... s1 <- c(200,200,190,180) ... and plotting them works fine, e.g. ... myplot(s1) Now I want to have "s1" etc appear in the plot title, but I don't know how to refer to this generically (the object "name"? I tried