Custom lollipop chart



A lollipop chart is constituted of a circle (made with geom_point()) and a segment (made with geom_segment()). This page explains how to customize the chart appearance with R and ggplot2.

Lollipop section Data to Viz

Marker


A lollipop plot is constituted of a marker and a stem. You can customize the marker as usual with ggplot2:

  • size, color
  • alpha → transparency
  • shape → see list of available shape here
  • stroke and fill → only for shapes that have stroke, like the 21

# Library
library(tidyverse)
 
# Create data
data <- data.frame(
  x=LETTERS[1:26],
  y=abs(rnorm(26))
)
 
# plot
ggplot(data, aes(x=x, y=y)) +
  geom_segment( aes(x=x, xend=x, y=0, yend=y)) +
  geom_point( size=5, color="red", fill=alpha("orange", 0.3), alpha=0.7, shape=21, stroke=2) 

Stem


The stem is built using geom_segment() and can be customized as well:

  • size, color
  • linetype → can be an integer (see list), a word like dotted, dashed, dotdash and more (type help(linetype))

# Libraries
library(ggplot2)

# Create data
data <- data.frame(
  x=LETTERS[1:26],
  y=abs(rnorm(26))
)

# Plot
ggplot(data, aes(x=x, y=y)) +
  geom_segment( aes(x=x, xend=x, y=0, yend=y) , size=1, color="blue", linetype="dotdash" ) +
  geom_point()

General appearance with theme()


As usual, you can customize the general appearance of the chart using the theme() function.

Note: another solution is to use the pre-built theme_ipsum() offered in the hrbrthemes package.

# Libraries
library(ggplot2)

# Create data
data <- data.frame(
  x=LETTERS[1:26],
  y=abs(rnorm(26))
)

# Plot
ggplot(data, aes(x=x, y=y)) +
  geom_segment( aes(x=x, xend=x, y=0, yend=y), color="grey") +
  geom_point( color="orange", size=4) +
  theme_light() +
  theme(
    panel.grid.major.x = element_blank(),
    panel.border = element_blank(),
    axis.ticks.x = element_blank()
  ) +
  xlab("") +
  ylab("Value of Y")

Horizontal version


It is pretty straightforward to flip the chart using the coord_flip() function.

It makes sense to do so if you have long labels → they will be much easier to read.

# Libraries
library(ggplot2)

# Create data
data <- data.frame(
  x=LETTERS[1:26],
  y=abs(rnorm(26))
)

# Horizontal version
ggplot(data, aes(x=x, y=y)) +
  geom_segment( aes(x=x, xend=x, y=0, yend=y), color="skyblue") +
  geom_point( color="blue", size=4, alpha=0.6) +
  theme_light() +
  coord_flip() +
  theme(
    panel.grid.major.y = element_blank(),
    panel.border = element_blank(),
    axis.ticks.y = element_blank()
  )

Baseline


Lastly, you can easily change the baseline of the chart. It gives more insight to the figure if there is a specific threshold in the data that interests you.

You just have to change the y argument in the geom_segment() call.

# Libraries
library(ggplot2)

# Create data
data <- data.frame(
  x=LETTERS[1:26],
  y=abs(rnorm(26))
)

# Change baseline
ggplot(data, aes(x=x, y=y)) +
  geom_segment( aes(x=x, xend=x, y=1, yend=y), color="grey") +
  geom_point( color="orange", size=4) +
  theme_light() +
  theme(
    panel.grid.major.x = element_blank(),
    panel.border = element_blank(),
    axis.ticks.x = element_blank()
  ) +
  xlab("") +
  ylab("Value of Y")

What’s next


The lollipop chart is one of my favourite. There is so much to do with it and it is under-utilized in favor of barplot. Visit the dedicated section for more examples produced with R, or data-to-viz to learn about the available variations and caveats to avoid.

Lollipop section Data to Viz

Related chart types


Barplot
Spider / Radar
Wordcloud
Parallel
Lollipop
Circular Barplot



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