A circular barplot is a barplot where bars are displayed along a circle
instead of a line. This page aims to teach you how to make a grouped and
stacked circular barplot with R
and
ggplot2
.
A circular barplot is a barplot where bars are displayed along a circle instead of a line. This page aims to teach you how to make a grouped and stacked circular barplot. I highly recommend to visit graph #295, #296 and #297 Before diving into this code, which is a bit rough.
You first need to understand how to make a stacked barplot with ggplot2. Then understand how to properly add labels, calculating the good angles, flipping them if necessary, and adjusting their position. The trickiest part is probably the one allowing to add space between each group. All these steps are described one by one in the circular barchart section.
First we need to load the tidyverse
and the
viridis
package.
Then, we create a fake dataset for the purpose of this chart.
# library
library(tidyverse)
library(viridis)
# Create dataset
data <- data.frame(
individual=paste( "Mister ", seq(1,60), sep=""),
group=factor(c( rep('A', 10), rep('B', 30), rep('C', 14), rep('D', 6))) ,
value1=sample( seq(10,100), 60, replace=T),
value2=sample( seq(10,100), 60, replace=T),
value3=sample( seq(10,100), 60, replace=T)
)
# Transform data in a tidy format (long format)
data <- data %>% gather(key = "observation", value="value", -c(1,2))
Here are some concise bullet points explaining the R code for beginners:
Adding Empty Bars: Append placeholder rows with no data at the end of each group in the dataset to ensure clear visualization.
Sorting Data: Rearrange the dataset by group and individual to maintain consistent ordering.
Labeling: Calculate the position and orientation for labels that display total values, ensuring readability based on their placement.
Base and Grid Lines: Set up baseline and grid lines to provide a reference scale on the plot, which helps in understanding data magnitude and distribution.
Building the Plot: Utilize ggplot2 to create a polar bar chart with stacked bars, value labels, and reference lines.
Saving the Output: Export the finalized chart as a PNG file, setting appropriate dimensions for clarity and presentation.
# Set a number of 'empty bar' to add at the end of each group
empty_bar <- 2
nObsType <- nlevels(as.factor(data$observation))
to_add <- data.frame( matrix(NA, empty_bar*nlevels(data$group)*nObsType, ncol(data)) )
colnames(to_add) <- colnames(data)
to_add$group <- rep(levels(data$group), each=empty_bar*nObsType )
data <- rbind(data, to_add)
data <- data %>% arrange(group, individual)
data$id <- rep( seq(1, nrow(data)/nObsType) , each=nObsType)
# Get the name and the y position of each label
label_data <- data %>% group_by(id, individual) %>% summarize(tot=sum(value))
number_of_bar <- nrow(label_data)
angle <- 90 - 360 * (label_data$id-0.5) /number_of_bar # I substract 0.5 because the letter must have the angle of the center of the bars. Not extreme right(1) or extreme left (0)
label_data$hjust <- ifelse( angle < -90, 1, 0)
label_data$angle <- ifelse(angle < -90, angle+180, angle)
# prepare a data frame for base lines
base_data <- data %>%
group_by(group) %>%
summarize(start=min(id), end=max(id) - empty_bar) %>%
rowwise() %>%
mutate(title=mean(c(start, end)))
# prepare a data frame for grid (scales)
grid_data <- base_data
grid_data$end <- grid_data$end[ c( nrow(grid_data), 1:nrow(grid_data)-1)] + 1
grid_data$start <- grid_data$start - 1
grid_data <- grid_data[-1,]
# Make the plot
p <- ggplot(data) +
# Add the stacked bar
geom_bar(aes(x=as.factor(id), y=value, fill=observation), stat="identity", alpha=0.5) +
scale_fill_viridis(discrete=TRUE) +
# Add a val=100/75/50/25 lines. I do it at the beginning to make sur barplots are OVER it.
geom_segment(data=grid_data, aes(x = end, y = 0, xend = start, yend = 0), colour = "grey", alpha=1, linewidth=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 50, xend = start, yend = 50), colour = "grey", alpha=1, linewidth=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 100, xend = start, yend = 100), colour = "grey", alpha=1, linewidth=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 150, xend = start, yend = 150), colour = "grey", alpha=1, linewidth=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 200, xend = start, yend = 200), colour = "grey", alpha=1, linewidth=0.3 , inherit.aes = FALSE ) +
# Add text showing the value of each 100/75/50/25 lines
ggplot2::annotate("text", x = rep(max(data$id),5), y = c(0, 50, 100, 150, 200), label = c("0", "50", "100", "150", "200") , color="grey", size=6 , angle=0, fontface="bold", hjust=1) +
ylim(-150,max(label_data$tot, na.rm=T)) +
theme_minimal() +
theme(
legend.position = "none",
axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
plot.margin = unit(rep(-1,4), "cm")
) +
coord_polar() +
# Add labels on top of each bar
geom_text(data=label_data, aes(x=id, y=tot+10, label=individual, hjust=hjust), color="black", fontface="bold",alpha=0.6, size=5, angle= label_data$angle, inherit.aes = FALSE ) +
# Add base line information
geom_segment(data=base_data, aes(x = start, y = -5, xend = end, yend = -5), colour = "black", alpha=0.8, size=0.6 , inherit.aes = FALSE ) +
geom_text(data=base_data, aes(x = title, y = -18, label=group), hjust=c(1,1,0,0), colour = "black", alpha=0.8, size=4, fontface="bold", inherit.aes = FALSE)
# Save at png
ggsave(p, file="output.png", width=10, height=10)
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