Using R and ggplot2 is there a better way to visualize TRUE and FALSE Boolean Value columns?-CodePudding

So I've got a larger data set, but for simplicity's sake I've done my best to offer a simplified version of my problem/dataset:

So there are a total of 3 Little Pigs. One of the pigs owns just one house I want to plot on the Y axis the total home values and then a faceted view of how much each pig owns.

HOUSES	HOUSEVALUE	PIG1	PIG2	PIG3
Hay	30000	TRUE	FALSE	FALSE
Sticks	70000	TRUE	TRUE	FALSE
Bricks	100000	TRUE	TRUE	TRUE

And here's a quick sketch of what I'd like this to look like:

I'm very rusty with my R usage as well as my GGPLOT2 usage. I'm doing all kinds of crazy stuff with this data, such as:

library(ggplot2)
library(readr)
piggies <- read_csv("piggies.csv")
ggplot(piggies, aes(x=PIG1, fill=as.factor(HOUSEVALUE))) geom_bar(position='dodge')
ggplot(piggies, aes(x=PIG2, fill=as.factor(HOUSEVALUE))) geom_bar(position='dodge')

I understand the above ggplot2 visualizations are borderline insane, but I'm having the hardest time tracking down solid resources for columns that are boolean values and making the Y axis represent something other than "Count"

(Edited the example GGPlot formulae to be slightly less insane than my original example)

CodePudding user response：

I'm not sure if this is what you are looking for, it would give the total amount each pig owns of each type stacked. Similar to what @Akrun said, it uses pivot_longer before plotting:

dat<-data.frame("HOUSES" = c("Hay", "Sticks", "Bricks"), "HOUSEVALUE" = c(30000, 70000, 100000), "PIG1" = c(T,T,T), "PIG2" = c(F,T,T), "PIG3" = c(F,F,T))


library(dplyr)
library(tidyr)
library(ggplot2)

dat%>%
  pivot_longer(cols = starts_with("PIG"))%>%
  filter(value)%>%
  ggplot() 
  aes(name, HOUSEVALUE, fill = HOUSES) 
  geom_bar(stat = "identity")