Definition

A circular barplot is a barplot, with each bar displayed along a circle instead of a line. Thus, it is advised to have a good understanding of how barplot works before making it circular. Circular bar chart is very ‘eye catching’ and allows a better use of the space than a long usual barplot.

Here is an example showing the quantity of weapons exported by the top 20 largest exporters in 2017 (more info here):

# Libraries
library(tidyverse)
library(hrbrthemes)
library(kableExtra)
options(knitr.table.format = "html")
library(viridis)

# Load dataset from github
data <- read.table("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/7_OneCatOneNum.csv", header=TRUE, sep=",")

# Order data
tmp <- data %>%
  filter(!is.na(Value)) %>%
  arrange(desc(Value)) %>%
  mutate(Country=factor(Country, Country))

# Set a number of 'empty bar'
empty_bar=10

# Add lines to the initial tmpset
to_add = matrix(NA, empty_bar, ncol(tmp))
colnames(to_add) = colnames(tmp)
tmp=rbind(tmp, to_add)
tmp$id=seq(1, nrow(tmp))

# Get the name and the y position of each label
label_tmp=tmp
number_of_bar=nrow(label_tmp)
angle= 90 - 360 * (label_tmp$id-0.5) /number_of_bar     # I substract 0.5 because the letter must have the angle of the center of the bars. Not extreme right(1) or extreme left (0)
label_tmp$hjust<-ifelse( angle < -90, 1, 0)
label_tmp$angle<-ifelse(angle < -90, angle+180, angle)
label_tmp$Country <- gsub("United States", "US", label_tmp$Country)
label_tmp$Country <- paste(label_tmp$Country, " (", label_tmp$Value,")", sep="")

# Make the plot
ggplot(tmp, aes(x=as.factor(id), y=Value)) +       # Note that id is a factor. If x is numeric, there is some space between the first bar
  geom_bar(stat="identity", fill=alpha("#69b3a2", 0.8)) +
  ylim(-7000,13000) +
  theme_minimal() +
  theme(
    axis.text = element_blank(),
    axis.title = element_blank(),
    panel.grid = element_blank(),
    plot.margin = unit(rep(-1,4), "cm") 
  ) +
  coord_polar(start = 0) + 
  geom_text(data=label_tmp, aes(x=id, y=Value+200, label=Country ), color="black", fontface="bold",alpha=0.6, size=2.5, angle= label_tmp$angle, hjust=label_tmp$hjust, inherit.aes = FALSE ) +
  geom_text( aes(x=24, y=8000, label="Who sells more weapons?"), color="black", inherit.aes = FALSE)

Note:

Here no Y scale is displayed since exact values are written on each bar.
More representation of this dataset are available here, with further explanation.

What for

Circular barplot is really eye catching but makes it more difficult to read the differences between each bar size. Thus, circular barcharts make sense only if you have a huge number of bar to display, and if an obvious pattern pops out.

In my opinion, circular barplot gets even more interesting with a grouping variable. In the following example that uses dummy data, it is easy to compare groups and entities into each group.

# Create dataset
data=data.frame(
  individual=paste( "Mister ", seq(1,60), sep=""),
  group=c( rep('A', 10), rep('B', 30), rep('C', 14), rep('D', 6)) ,
  value=sample( seq(10,100), 60, replace=T)
)
data = data %>% arrange(group, value)

# Set a number of 'empty bar' to add at the end of each group
empty_bar=3
to_add = data.frame( matrix(NA, empty_bar*nlevels(data$group), ncol(data)) )
colnames(to_add) = colnames(data)
to_add$group=rep(levels(data$group), each=empty_bar)
data=rbind(data, to_add)
data=data %>% arrange(group)
data$id=seq(1, nrow(data))
 
# Get the name and the y position of each label
label_data=data
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, aes(x=as.factor(id), y=value, fill=group)) +       # Note that id is a factor. If x is numeric, there is some space between the first bar
  
  geom_bar(aes(x=as.factor(id), y=value, fill=group), stat="identity", alpha=0.5) +
  
  # 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 = 80, xend = start, yend = 80), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
  geom_segment(data=grid_data, aes(x = end, y = 60, xend = start, yend = 60), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
  geom_segment(data=grid_data, aes(x = end, y = 40, xend = start, yend = 40), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
  geom_segment(data=grid_data, aes(x = end, y = 20, xend = start, yend = 20), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
  
  # Add text showing the value of each 100/75/50/25 lines
  annotate("text", x = rep(max(data$id),4), y = c(20, 40, 60, 80), label = c("20", "40", "60", "80") , color="grey", size=3 , angle=0, fontface="bold", hjust=1) +
  
  geom_bar(aes(x=as.factor(id), y=value, fill=group), stat="identity", alpha=0.5) +
  ylim(-100,120) +
  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() + 
  geom_text(data=label_data, aes(x=id, y=value+10, label=individual, hjust=hjust), color="black", fontface="bold",alpha=0.6, size=2.5, 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)
 
p

Variation

Most of the variations presented for the barplot are obviously available for the circular barplot. For instance, you can group your variable and stack the group to get a stacked circular barplot:

# Create dataset
data=data.frame(
  individual=paste( "Mister ", seq(1,60), sep=""),
  group=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)) 
 
# 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, size=0.3 , inherit.aes = FALSE ) +
  geom_segment(data=grid_data, aes(x = end, y = 50, xend = start, yend = 50), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
  geom_segment(data=grid_data, aes(x = end, y = 100, xend = start, yend = 100), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
  geom_segment(data=grid_data, aes(x = end, y = 150, xend = start, yend = 150), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
  geom_segment(data=grid_data, aes(x = end, y = 200, xend = start, yend = 200), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
  
  # Add text showing the value of each 100/75/50/25 lines
  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=2 , 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=1, 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)
p

Common mistakes

The proportion of the inner circle must be huge (>1/2). Otherwise bars are very skewed like on the next example. In my opinion this distorts reality: biggest bars look even bigger that they are. You can read more about that in the dedicated article.

# Create dataset
data=data.frame(
  individual=paste( "Mister ", seq(1,30), sep=""),
  group=c( rep('A', 10), rep('C', 14), rep('D', 6)) ,
  value=sample( seq(10,100), 30, replace=T)
)
data = data %>% arrange(group, value)

# Set a number of 'empty bar' to add at the end of each group
empty_bar=1
to_add = data.frame( matrix(NA, empty_bar*nlevels(data$group), ncol(data)) )
colnames(to_add) = colnames(data)
to_add$group=rep(levels(data$group), each=empty_bar)
data=rbind(data, to_add)
data=data %>% arrange(group)
data$id=seq(1, nrow(data))
 
# Get the name and the y position of each label
label_data=data
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)
 

# Make the plot
p = ggplot(data, aes(x=as.factor(id), y=value, fill=group)) +       # Note that id is a factor. If x is numeric, there is some space between the first bar
  
  geom_bar(aes(x=as.factor(id), y=value, fill=group), stat="identity", alpha=0.5) +
  ylim(-10,120) +
  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() + 
  geom_text(data=label_data, aes(x=id, y=value+10, label=individual, hjust=hjust), color="black", fontface="bold",alpha=0.6, size=2.5, angle= label_data$angle, inherit.aes = FALSE ) 
  
p

Works only if you have many levels to display (> ~40) and a clear pattern
Keep displaying a Y axis all along the circle.
Order your bars. If the levels of your categoric variable have no obvious order, order the bars following their values.
Several values per group? Don’t use a barplot. Even with error bars, it hides information and other type of graphic like boxplot or violin are much more appropriate.

Barplot

Represents the value of entities using bar of various length.

Lollipop plot

A fancy barplot where bars are replaced with a dot and a segment. Allows even more options when it comes to stacking.

Spider / Radar

One or more series of values over multiple common quantitative variables. Axis are joint on the middle of the figure.

Boxplot

Summarize the distribution of several numeric variables using boxes. Use it if you have a limited dataset size.

Build your own

The R and Python graph galleries are 2 websites providing hundreds of chart example, always providing the reproducible code. Click the button below to see how to build the chart you need with your favorite programing language.

R graph gallery

Comments

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