r - using the arrows function to add confidence limits stored in a dataframe to a barplot -
i'm sure simple problem of :) have looked around r pages , on here , know function need (arrows think) don't understand how use it. question is:
i have dataframe (data) results of experiment have simplified this:
treatment y lower_limit_ci upper_limit_ci 1 0.13284413 0.1224 0.1438 2 0.263072558 0.2458 0.2809 3 0.234218546 0.217 0.2521 4 0.394980185 0.3702 0.4201 5 0.474533107 0.4457 0.5035 6 0.583333333 0.5526 0.6136
i have drawn barplot of data so:
plot <- barplot(data$y)
and know need function arrows (yes?) add confidence limits stored in dataframe plot.
can please show me how use arrows correct info. dataframe? have tried on advice of someone:
arrows(plot, data$y - data$lower_limit_ci, plot, data$y + data$upper_limit_ci, code=3, angle=90, length =0.1)
which gives giant bars incorrect. can help?
thanks!
i suggest instead of barplot
, arrows
functions, use more flexible , powerful ggplot2 package. here's how ggplot
, geom_bar
, geom_errorbar
functions can used create barchart confidence interval:
ggplot(data, aes(treatment, y, fill=1:6)) + geom_bar(position=position_dodge(), stat="identity") + geom_errorbar(aes(ymin=data$lower_limit_ci, ymax=data$upper_limit_ci), width=.2, position=position_dodge(.9))
the output looks this: