Following is my dataset:

I want to plot a grouped bar graph. I am able to plot following graphs but I want both the results in same graph.

par(mfrow=c(1,1))
options(scipen=999)
coul <- brewer.pal(3, "Set2") 

# Bar graph for passed courses 
result_pass <-data %>% filter(Result=='Pass') %>%  summarize(c1_tot=sum(course1), 
        c2_tot = sum(course2), c3_tot = sum(course3) )
col_sum <- colSums(result_pass[,1:3])
barplot(colSums(result_pass[,1:3]), xlab = "Courses", ylab = "Total Marks", col = coul, ylim=range(pretty(c(0, col_sum))), main = "Passed courses ")

# Bar graph for Failed courses 
result_fail <-data %>% filter(Result=='Fail') %>%  summarize(c1_tot=sum(course1), 
        c2_tot = sum(course2), c3_tot = sum(course3) )
col_sum <- colSums(result_fail[,1:3])
barplot(colSums(result_fail[,1:3]), xlab = "Courses", ylab = "Total Marks", col = coul, ylim=range(pretty(c(0, col_sum))), main = "Failed courses ")

Any suggestion for which I can merge both the above plots and create grouped bar graph for Pass and Fail courses.

CodePudding user response：

It's probably easier than you think. Just put the data directly in aggregate and use as formula . ~ Result, where . means all other columns. Removing first column [-1] and coerce as.matrix (because barplot eats matrices) yields exactly the format we need for barplot.

This is the basic code:

barplot(as.matrix(aggregate(. ~ Result, data, sum)[-1]), beside=TRUE)

And here with some visual enhancements:

barplot(as.matrix(aggregate(. ~ Result, data, sum)[-1]), beside=TRUE, ylim=c(0, 70),
        col=hcl.colors(2, palette='viridis'), legend.text=sort(unique(data$Result)),
        names.arg=names(data)[-1], main='Here could be your title',
        args.legend=list(x='topleft', cex=.9))
box()

Data:

data <- structure(list(Result = c("pass", "pass", "Fail", "Fail", "pass", 
"Fail"), course1 = c(15L, 12L, 9L, 3L, 14L, 5L), course2 = c(17L, 
14L, 13L, 2L, 11L, 0L), course3 = c(18L, 19L, 3L, 0L, 20L, 7L
)), class = "data.frame", row.names = c(NA, -6L))