Pie Chart

BarChart circular with coord_polar()

# Create Data
data <- data.frame(
  group=LETTERS[1:5],
  value=c(13,7,9,21,2)
)

# Basic piechart
ggplot(data, aes(x="", y=value, fill=group)) +
  geom_bar(stat="identity", width=1, color="white") +
  coord_polar("y", start=0) +
  theme_void() # remove background, grid, numeric labels

# Basic piechart
ggplot(data, aes(x="", y=value, fill=group)) +
  geom_bar(stat="identity", width=1) +
  coord_polar("y", start=0) +
  labs(title="Add Title Here...",
       x="",
       y="") +
  theme(axis.line = element_blank(),  
        axis.ticks = element_blank(),
        panel.grid  = element_blank())

Adding labels with geom_text()

# Create Data
data <- data.frame(
  group=LETTERS[1:5],
  value=c(13,7,9,21,2)
)

# Compute the position of labels
data <- data %>% 
  arrange(desc(group)) %>%
  mutate(prop = value / sum(data$value) *100) %>%
  mutate(ypos = cumsum(prop)- 0.5*prop )

# Basic piechart
ggplot(data, aes(x="", y=prop, fill=group)) +
  geom_bar(stat="identity", width=1, color="white") +
  coord_polar("y", start=0) +
  theme_void() + 
  theme(legend.position="none") +
  
  geom_text(aes(y = ypos, label = group), color = "white", size=6) +
  scale_fill_brewer(palette="Pastel1")

Add Lable in Legend

data <- data.frame(
  group=c("Severe retinal detachments", 
          "Traumatic retinal detachments", 
          "Giant retinal tears",
          "Other retinal detachments",
          "Lifting of the subluxated lens",
          "Other diseases"),
  value=c(7468 , 2843 , 2889 ,827 ,1320 ,235 )
)
# Compute the position of labels
data <- data %>% 
  arrange(desc(group)) %>%
  mutate(prop = paste(round(value / sum(data$value) *100,1),"%"),
         group = paste(group,"(",prop, ")")) 
### Converting all chr variables
data[sapply(data, is.character)] <- lapply(data[sapply(data, is.character)], as.factor)

data$group

## [1] Traumatic retinal detachments ( 18.2 % )
## [2] Severe retinal detachments ( 47.9 % )   
## [3] Other retinal detachments ( 5.3 % )     
## [4] Other diseases ( 1.5 % )                
## [5] Lifting of the subluxated lens ( 8.5 % )
## [6] Giant retinal tears ( 18.5 % )          
## 6 Levels: Giant retinal tears ( 18.5 % ) ...

# Basic piechart
ggplot(data, aes(x="", y=value, fill=group)) +
  geom_bar(stat="identity", width=1, color="white") +
  coord_polar("y", start=0) +
  scale_color_brewer(palette="Dark2") +
  scale_fill_discrete(name = "Disease",
                      breaks=c("Severe retinal detachments ( 47.9 % )",
                              "Traumatic retinal detachments ( 18.2 % )",
                              "Giant retinal tears ( 18.5 % )",
                              "Other retinal detachments ( 5.3 % )",
                              "Lifting of the subluxated lens ( 8.5 % )",
                              "Giant retinal tears ( 18.5 % )",
                              "Other diseases ( 1.5 % )")) +
  labs(title="Add Title Here...",
       x="",
       y="") +
  theme(legend.position="right")+
  theme(axis.line = element_blank(), 
        axis.text = element_blank(),
        axis.ticks = element_blank(),
        panel.grid  = element_blank())

Interactive Pie Chart

# library(plotly)
# Create fake data
df <- data.frame(
  genre=c("Pop", "HipHop", "Latin", "Jazz"), 
  values = c(33,22,25,20)
)
  
plot_ly(data=df,labels=~genre, values=~values, type="pie") %>% 
    layout(title = 'United States Music Genre Prevalent in 1999',
           xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
           yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

Donut chart

Basic Doughnut

# Create test data.
data <- data.frame(
  category=c("A", "B", "C"),
  count=c(10, 60, 30)
)
 
# Compute percentages
data$fraction = data$count / sum(data$count)

# Compute the cumulative percentages (top of each rectangle)
data$ymax = cumsum(data$fraction)

# Compute the bottom of each rectangle
data$ymin = c(0, head(data$ymax, n=-1))
 
# Make the plot
ggplot(data, aes(ymax=ymax, ymin=ymin, xmax=4, xmin=3, fill=category)) +
  geom_rect() +
  coord_polar(theta="y") + # Try to remove that to understand how the chart is built initially
  xlim(c(2, 4)) +
  theme_bw()

Customization

# Create test data.
data <- data.frame(
  category=c("A", "B", "C"),
  count=c(10, 60, 30)
)
 
# Compute percentages
data$fraction <- data$count / sum(data$count)

# Compute the cumulative percentages (top of each rectangle)
data$ymax <- cumsum(data$fraction)

# Compute the bottom of each rectangle
data$ymin <- c(0, head(data$ymax, n=-1))

# Compute label position
data$labelPosition <- (data$ymax + data$ymin) / 2

# Compute a good label
data$label <- paste0(data$category, "\n value: ", data$count)

# Make the plot
ggplot(data, aes(ymax=ymax, ymin=ymin, xmax=4, xmin=3, fill=category)) +
  geom_rect() +
  geom_label( x=3.5, aes(y=labelPosition, label=label), size=5) +
  scale_fill_brewer(palette=4) +
  coord_polar(theta="y") +
  xlim(c(2, 4)) +
  theme_void() +
  theme(legend.position = "none")

Donut Thickness

# Create test data.
data <- data.frame(
  category=c("A", "B", "C"),
  count=c(10, 60, 30)
)
 
# Compute percentages
data$fraction <- data$count / sum(data$count)

# Compute the cumulative percentages (top of each rectangle)
data$ymax <- cumsum(data$fraction)

# Compute the bottom of each rectangle
data$ymin <- c(0, head(data$ymax, n=-1))

# Compute label position
data$labelPosition <- (data$ymax + data$ymin) / 2

# Compute a good label
data$label <- paste0(data$category, "\n value: ", data$count)

# Make the plot
ggplot(data, aes(ymax=ymax, ymin=ymin, xmax=4, xmin=3, fill=category)) +
  geom_rect() +
  geom_text( x=2, aes(y=labelPosition, label=label, color=category), size=6) + # x here controls label position (inner / outer)
  scale_fill_brewer(palette=3) +
  scale_color_brewer(palette=3) +
  coord_polar(theta="y") +
  xlim(c(-1, 4)) +
  theme_void() +
  theme(legend.position = "none")

Treemap

Basic Treemap

# library("treemap")
group <- c("group-1","group-2","group-3")
value <- c(13,5,22)
data <- data.frame(group,value)
data %>% gt()

group	value
group-1	13
group-2	5
group-3	22

# treemap
treemap(data,
        index="group",
        vSize="value",
        type="index"
        )

Treemap with subgroups

# Build Dataset
group <- c(rep("group-1",4),rep("group-2",2),rep("group-3",3))
subgroup <- paste("subgroup" , c(1,2,3,4,1,2,1,2,3), sep="-")
value <- c(13,5,22,12,11,7,3,1,23)
data <- data.frame(group,subgroup,value)
data %>% gt()

group	subgroup	value
group-1	subgroup-1	13
group-1	subgroup-2	5
group-1	subgroup-3	22
group-1	subgroup-4	12
group-2	subgroup-1	11
group-2	subgroup-2	7
group-3	subgroup-1	3
group-3	subgroup-2	1
group-3	subgroup-3	23

# General features:
treemap(data, index=c("group","subgroup"), 
        vSize="value", 
        type="index",    
        palette = "Set1",  
        title="My Treemap",  
        fontsize.title=11,                       # Size of the title
) 

Interactive Treemap

## devtools::install_github("sada1993/d3treeR")
# library(d3treeR)

# dataset
group <- c(rep("group-1",4),rep("group-2",2),rep("group-3",3))
subgroup <- paste("subgroup" , c(1,2,3,4,1,2,1,2,3), sep="-")
value <- c(13,5,22,12,11,7,3,1,23)
data <- data.frame(group,subgroup,value)
 
# basic treemap
p <- treemap(data,
            index=c("group","subgroup"),
            vSize="value",
            type="index",
            palette = "Set2",
            bg.labels=c("white"),
            align.labels=list(
              c("center", "center"), 
              c("right", "bottom")
            )  
          )            

# make it interactive ("rootname" becomes the title of the plot):
inter <- d3tree2( p ,  rootname = "General" )
inter