How to make a bar plot using ggplot that uses multiple columns for the x-axis?

Question

I am trying to use multiple column names as the x-axis in a barplot. So each column name will be the "factor" and the data it contains is the count for that.

I have tried iterations of this:

 ggplot(aes( x = names, y = count)) + geom_bar()

I tried concatenating the x values I want to show with aes(c(col1, col2)) but the aesthetics length does not match and won't work.

library(dplyr) library(ggplot2) head(dat) Sample Week Response_1 Response_2 Response_3 Response_4 Vaccine_Type 1 1 1 300 0 2000 100 1 2 2 1 305 0 320 15 1 3 3 1 310 0 400 35 1 4 4 1 400 1 410 35 1 5 5 1 405 0 180 35 2 6 6 1 410 2 800 75 2 dat %>% group_by(Week) %>% ggplot(aes(c(Response_1, Response_2, Response_3, Response_4)) + geom_boxplot() + facet_grid(.~Week) dat %>% group_by(Week) %>% ggplot(aes(Response_1, Response_2, Response_3, Response_4)) + geom_boxplot() + facet_grid(.~Week) > Error: Aesthetics must be either length 1 or the same as the data > (24): x

Both of these failed (kind of expected based on aes length error code), but hopefully you know the direction I was aiming for and can help out.

Goal is to have 4 separate groups, each with their own boxplot (1 for every response). And also have them faceted by week.

Something like these stackoverflow.com/a/50649629/786542 & stackoverflow.com/a/50751486/786542? — Tung
– Tung, Commented Apr 7, 2019 at 20:15

s__ · Accepted Answer · 2019-04-08 07:08:15Z

Using the simple code below got mostly what I want. Unfortunately I don't think it would be as easy to include the points and other characteristics to the plot like you can with ggplot.

boxplot(dat[,3:6], use.cols = TRUE)

And I could pretty easily just filter by the different weeks and use mfrow for faceting. Not as informative as ggplot, but gets the job done. If anyone else has other workarounds, I'd be interested in seeing.

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