R plot two series of means with 95% confidence intervals

Question

I am trying to plot the following data

factor <- as.factor(c(1,2,3))
V1_mean <- c(100,200,300)
V2_mean <- c(350,150,60)
V1_stderr <- c(5,9,3)
V2_stderr <- c(12,9,10)

plot <- data.frame(factor,V1_mean,V2_mean,V1_stderr,V2_stderr)

I want to create a plot with factor on the x-axis, value on the y-axis and seperate lines for V1 and V2 (hence the points are the values of V1_mean on one line and V2_mean on the other). I would also like to add error bars for these means based on V1_stderr and V2_stderr

Many thanks

Answer 1

I'm not sure regarding your desired output, but here's a possible solution.

First of all, I wouldn't call your data plot as this is a stored function in R which is being commonly used

Second of all, when you want to plot two lines in ggplot you'll usually have to tide your data using functions such as melt (from reshape2 package) or gather (from tidyr package).

Here's an a possible approach

library(ggplot2)
library(reshape2)

dat <- data.frame(factor, V1_mean, V2_mean, V1_stderr, V2_stderr)
mdat <- cbind(melt(dat[1:3], "factor"), melt(dat[c(1, 4:5)], "factor"))
names(mdat) <- make.names(names(mdat), unique = TRUE)

ggplot(mdat, aes(factor, value, color = variable)) +
  geom_point(aes(group = variable)) + # You can also add `geom_point(aes(group = variable)) + ` if you want to see the actual points
  geom_errorbar(aes(ymin = value - value.1, ymax = value + value.1))