r-factor

I would like to take a data frame with characters and numbers, and concatenate all of the elements of the each row into a single string, which would be stored as a single element in a vector. As an example, I make a data frame of letters and numbers, and then I would like to concatenate the first row via the paste function, and hopefully return the value "A1" df <- data.frame(letters = LETTERS[1:5], numbers = 1:5) df ## letters numbers ## 1 A 1 ## 2 B 2 ## 3 C 3 ## 4 D 4 ## 5 E 5 paste(df[1,], sep =".") ## [1] "1" "1" So paste is converting each element of the row into an integer that

This question follows from this other one . I was unable to implement answers there. Define: df2 <- data.frame(variable=rep(c("vnu.shr","vph.shr"),each=10), value=seq(1:20)) Plot: require(ggplot2) qplot(variable,value, data=df2,geom="boxplot")+ geom_jitter(position=position_jitter(w=0.1,h=0.1)) I would like to have the boxplots in the reverse order (e.g. one in right on left and so on). I have tried various ways of reordering the factors using levels , ordered , relevel , rev and so on, but I simply cannot seem to get the syntax right. Have you tried this: df2$variable <- factor(df2$variable,

I am making a scatter plot of two variables and would like to colour the points by a factor variable. Here is some reproducible code: data <- iris plot(data$Sepal.Length, data$Sepal.Width, col=data$Species) This is all well and good but how do I know what factor has been coloured what colour?? data<-iris plot(data$Sepal.Length, data$Sepal.Width, col=data$Species) legend(7,4.3,unique(data$Species),col=1:length(data$Species),pch=1) should do it for you. But I prefer ggplot2 and would suggest that for better graphics in R. The command palette tells you the colours and their order when col =

I have the following code anna.table<-data.frame (anna1,anna2) write.table<-(anna.table, file="anna.file.txt",sep='\t', quote=FALSE) my table in the end contains numbers such as the following chr start end score chr2 41237927 41238801 151 chr1 36976262 36977889 226 chr8 83023623 83025129 185 and so on...... after that i am trying to to get only the values which fit some criteria such as score less than a specific value so i am doing the following anna3<-"data/anna/anna.file.txt" anna.total<-read.table(anna3,header=TRUE) significant.anna<-subset(anna.total,score <=0.001) Error: In Ops.factor

I want to convert variables into factors using apply() : a <- data.frame(x1 = rnorm(100), x2 = sample(c("a","b"), 100, replace = T), x3 = factor(c(rep("a",50) , rep("b",50)))) a2 <- apply(a, 2,as.factor) apply(a2, 2,class) results in: x1 x2 x3 "character" "character" "character" I don't understand why this results in character vectors instead of factor vectors. Marek apply converts your data.frame to a character matrix. Use lapply : lapply(a, class) # $x1 # [1] "numeric" # $x2 # [1] "factor" # $x3 # [1] "factor" In second command apply converts result to character matrix, using lapply : a2 <-

I recently saw Matt Dowle write some code with as.factor() , specifically for (col in names_factors) set(dt, j=col, value=as.factor(dt[[col]])) in a comment to this answer . I used this snippet, but I needed to explicitly set the factor levels to make sure the levels appear in my desired order, so I had to change as.factor(dt[[col]]) to factor(dt[[col]], levels = my_levels) This got me thinking: what (if any) is the benefit to using as.factor() versus just factor() ? as.factor is a wrapper for factor , but it allows quick return if the input vector is already a factor: function (x) { if (is