Create Bar Chart With Relative Frequency / From Table Object in R - r

Question

I have a dataset about accidents in the UK. Among other variables it contains the month of the accident and the severity (ranging from 1 to 3). Thus, you can imagine the dataset like this:
ID
Month
Accident_Severity
1
01
3
2
01
2
3
04
1
4
07
2
I would like to produce a bar chart with the months on the x-axis and the relative share of accidents out of the given severity class that happend in this month on the y-axis. This means each month should have three bars, let's say red, blue and green. Summing the relative share indicated by all bars of one color should equal to 100% for each color. I.e. if blue means Accident_Severity = 2 and the blue bar indicates 10% for January, this would mean 10% of all accidents with severity of 2 happend in january.
I managed to get these numbers as a table doing the following:
pivot_rel <- df %>%
select(month, Accident_Severity) %>%
group_by(month) %>%
table()
for (i in c(1,2,3)) {
for (j in seq(1,12)) {
pivot_rel[j,i] <- round(pivot_rel[j,i]/sum_severity[i],3)
}
}
pivot_rel
pivot_rel
However, i cannot use the object with ggplot. When trying I receive the error: "Fehler: data must be a data frame, or other object coercible by fortify(), not an S3 object with class table"
How do I visualize this table or is there an easier way to do what I try to achieve? Many Thanks!

Answer 1

Use xtabs to table the data and colSums to get the proportions. Then, with packages ggplot2 and scales, plot the graph.
library(ggplot2)
library(scales)
tbl <- xtabs( ~ Month + Accident_Severity, df1)
t(tbl)/colSums(tbl)
# Month
#Accident_Severity 1 4 7
# 1 0.0 1.0 0.0
# 2 0.5 0.0 0.5
# 3 1.0 0.0 0.0
as.data.frame(t(tbl)/colSums(tbl)) |>
ggplot(aes(factor(Month), Freq, fill = factor(Accident_Severity))) +
geom_col(position = position_dodge()) +
scale_fill_manual(values = c("red", "green", "blue")) +
scale_y_continuous(labels = percent_format()) +
xlab("Month") +
guides(fill = guide_legend(title = "Accident Severity"))
Data
df1 <- read.table(text = "
ID Month Accident_Severity
1 01 3
2 01 2
3 04 1
4 07 2
", header = TRUE)

Answer 2

A simple fix would be to change table to dataframe which can be used with ggplot.
pivot_rel <- as.data.frame.matrix(pivot_rel)
However, you might also go a step back and use count instead of table to generate the frequency counts of month and Accident_Severity.
library(dplyr)
pivot_rel <- df %>% count(month, Accident_Severity)

Answer 3

Using proportions on xtabs and base barplot.
proportions(xtabs( ~ Month + Accident_Severity, d), margin=2) |>
as.data.frame() |>
with(barplot(Freq ~ Accident_Severity + Month, beside=T, col=2:4,
main='Relative Frequencies',
legend.text=sort(unique(d$Accident_Severity)),
args.legend=list(title='Accident_Severity')))
Data:
d <- read.table(header=T, text='
ID Month Accident_Severity
1 01 3
2 01 2
3 04 1
4 07 2')