I would suggest you next approach. If you want error bars you can compute it based on mean and standard deviation. In the next code is sketched the way to do that. I have used one standard deviation but you can set any other value. Also as you want to see different samples, I have … Read more
The general (non ggplot-specific) answer is to use reorder() to reset the factor levels in a categorical column, based on some function of the other columns. ## Examine the default factor order levels(samp.data$fullname) ## Reorder fullname based on the the sum of the other columns samp.data$fullname <- reorder(samp.data$fullname, rowSums(samp.data[-1])) ## Examine the new factor order … Read more
Is this anything like what you’re after? With stat_summary, as requested: # function for number of observations give.n <- function(x){ return(c(y = median(x)*1.05, label = length(x))) # experiment with the multiplier to find the perfect position } # function for mean labels mean.n <- function(x){ return(c(y = median(x)*0.97, label = round(mean(x),2))) # experiment with the … Read more
The package RColorBrewer contains the palettes and you can use the function brewer.pal to return a colour palette of your choice. For example, a sequential blue palette of 5 colours: library(RColorBrewer) my.cols <- brewer.pal(5, “Blues”) my.cols [1] “#EFF3FF” “#BDD7E7” “#6BAED6” “#3182BD” “#08519C” You can get a list of valid palette names in the ?brewer.pal help … Read more
I know that this is an old question and the answer by DatamineR already provides one solution for the problem. But I recently created a ggplot-extension that simplifies the whole process of adding significance bars: ggsignif Instead of tediously adding the geom_line and annotate to your plot you just add a single layer geom_signif: library(ggplot2) … Read more
Unlike many other languages, in R, the dot is perfectly valid in identifiers. In this case, ..count.. is an identifier. However, there is special code in ggplot2 to detect this pattern, and to strip the dots. It feels unlikely that real code would use identifiers formatted like that, and so this is a neat way … Read more
You can pass in arguments such as min() and max() in your call to ggplot to dynamically specify the breaks. It sounds like you are going to be applying this across a wide variety of data so you may want to consider generalizing this into a function and messing with the formatting, but this approach … Read more
You can use grid.arrange() in the gridExtra package like this: grid.arrange(p1, p2)
You have to manually choose the number of characters to wrap at, but the combination of strwrap and paste will do what you want. wrapper <- function(x, …) { paste(strwrap(x, …), collapse = “\n”) } my_title <- “This is a really long title of a plot that I want to nicely wrap and fit onto … Read more
Richie’s answer is very thorough, but I wanted to show something simpler. Since lines are not drawn to NA points, another approach is drop these points when drawing lines. This implicitly makes a linear interpolation between points (as straight lines do). Using dfr from Richie’s answer, without needing the calculation of z step: ggplot(dfr, aes(x,y)) … Read more