Multiple bar graph with ggplot2 and shiny R - r

Question

I'm trying to plot a multiple bar graph for a customer satisfaction data set using Ggplot on R Shiny. Satisfaction varies from 1 to 5, where 1 being the lowest and 5 being the highest. This is how it looks like: (This is a sample of the original data set)
Satisfaction_Level <- c(4 ,4 ,5 ,5 ,3 ,4 ,4 ,4 ,4 ,5 ,1 ,4 ,1 ,3 ,4 ,4 ,1 ,4 ,4 ,1 ,4 ,4 ,4 ,4 ,2 ,4 ,2 ,4 ,3 ,1)
Location <- c("C" ,"C" ,"C" ,"B" ,"C" ,"C" ,"C" ,"A" ,"B" ,"C" ,"C" ,"C" ,"C" ,"B" ,"C" ,"C" ,"C" ,"B" ,"C" ,"B" ,"C" ,"C" ,"C" ,"B" ,"B" ,"B" ,"B" ,"B" ,"B" ,"B")
With the below code, I was able to generate this graph:
#satisfaction counts
satisCounts <- data.frame(table(mydata[,1]))
colnames(satisCounts) <- c("satisLevel", "satisCount")
satisCounts$perc3 <- as.character(round(100* satisCounts$satisCount / sum(satisCounts$satisCount)), 2)
satisCounts$lab3 <- paste(satisCounts$satisCount, paste("(",satisCounts$perc3,"%)",sep=""),sep=" ")
output$graph3 <- renderPlot({
satisCounts %>%
ggplot(aes(x=satisLevel, y=satisCount)) +
geom_bar(stat = "identity", aes(fill=satisLevel)) +
labs(y= "Customer count", x="Satisfaction Level") +
scale_fill_manual(values = c("#de425b", "#f2955a", "#ffe48f", "#a9b957", "#488f31")) +
labs(fill = "Satisfaction Level") +
geom_text(aes(label=lab3), vjust=-.5)
})
But what I actully want is to make this a multiple bar graph where all the satisfaction levels broken down by the location. Could you please help me fix this? Thank you!

Answer 1

From your question is is not clear how the final plot should look like. One option would be to use facetting. Another option would be to use a dodged bar chart. But the basis idea is to first compue counts by loacation and satisfaction levels. Have a look at this.
library(dplyr)
library(ggplot2)
Satisfaction_Level<-c(4 ,4 ,5 ,5 ,3 ,4 ,4 ,4 ,4 ,5 ,1 ,4 ,1 ,3 ,4 ,4 ,1 ,4 ,4 ,1 ,4 ,4 ,4 ,4 ,2 ,4 ,2 ,4 ,3 ,1)
Location <- c("C" ,"C" ,"C" ,"B" ,"C" ,"C" ,"C" ,"A" ,"B" ,"C" ,"C" ,"C" ,"C" ,"B" ,"C" ,"C" ,"C" ,"B" ,"C" ,"B" ,"C" ,"C" ,"C" ,"B" ,"B" ,"B" ,"B" ,"B" ,"B" ,"B")
df <- data.frame(
satisLevel = Satisfaction_Level,
Location = Location,
stringsAsFactors = FALSE
)
#satisfaction counts
# satisCounts <- data.frame(table(mydata[,1]))
# colnames(satisCounts) <- c("satisLevel", "satisCount")
# satisCounts$perc3 <- as.character(round(100* satisCounts$satisCount / sum(satisCounts$satisCount)), 2)
# satisCounts$lab3 <- paste(satisCounts$satisCount, paste("(",satisCounts$perc3,"%)",sep=""),sep=" ")
satisCounts <- df %>%
count(Location, satisLevel, name = "satisCount") %>%
mutate(satisLevel = factor(satisLevel))
satisCounts$perc3 <- as.character(round(100* satisCounts$satisCount / sum(satisCounts$satisCount)), 2)
satisCounts$lab3 <- paste(satisCounts$satisCount, paste("(",satisCounts$perc3,"%)",sep=""),sep=" ")
# Option 1: Use facetting
satisCounts %>%
ggplot(aes(x=satisLevel, y=satisCount)) +
geom_bar(stat = "identity", aes(fill=satisLevel)) +
labs(y= "Customer count", x="Satisfaction Level") +
scale_fill_manual(values = c("#de425b", "#f2955a", "#ffe48f", "#a9b957", "#488f31")) +
labs(fill = "Satisfaction Level") +
geom_text(aes(label=lab3), vjust=-.5) +
facet_wrap(~ Location, ncol = 1)
# Option 2: Dodged bar chart
satisCounts %>%
ggplot(aes(x=Location, y=satisCount, fill=satisLevel)) +
geom_bar(stat = "identity", position = position_dodge2(preserve = "single")) +
labs(y= "Customer count", x="Satisfaction Level") +
scale_fill_manual(values = c("#de425b", "#f2955a", "#ffe48f", "#a9b957", "#488f31")) +
labs(fill = "Satisfaction Level") +
geom_text(aes(label=lab3), vjust=-.5, position = position_dodge2(.9, preserve = "single"))
Created on 2020-04-05 by the reprex package (v0.3.0)