Overview

After experimenting with a few different radar plot libraries in R, I wanted to see if I could create a custom radar plot with ggplot2. In this tutorial, we’ll cover how to create your own custom ggplot2 radar graph. Before we begin, here’s a list of the packages we’ll be using:

tidyverse
geomtextpath
ggimage

Read & Reshape The Data

Let’s kick off with bringing in the data. For our tutorial, we’ll be working with a Superhero data set I collected from an earlier project.

The data set includes information about power abilities per character (intelligence, combat, strength, etc). Before plotting our data, we need to make sure it’s in the right shape- dplyr to the rescue! For this exercise, we’ll need it in a long format - each record should represent a super power per character.

When we import tidyverse, we automatically import both dplyr and ggplot2.

library(tidyverse)
library(knitr)
library(kableExtra)

#import data
df<-read.csv("https://raw.githubusercontent.com/tashapiro/superhero-comics/main/data/superheroes.csv")

#avengers
avengers<-c(106, 107, 149, 226, 313, 332, 346, 414, 659)

#avengers dataset
df_avengers<-df%>%
  filter(id %in% avengers)%>%
  select(name, full_name, intelligence, combat, strength, power, speed, durability)%>%
  pivot_longer(intelligence:durability, names_to = "ability", values_to = "stat")

#preview data
kable(head(df_avengers,6))%>%
    kable_styling(latex_options = "HOLD_position")

name	full_name	ability	stat
Black Panther	T'Challa	intelligence	88
Black Panther	T'Challa	combat	100
Black Panther	T'Challa	strength	16
Black Panther	T'Challa	power	41
Black Panther	T'Challa	speed	30
Black Panther	T'Challa	durability	60

Basic Radar Plot

Our data set contains all the Avengers characters. For our tutorial, we’ll pick on one of my favorites to focus on- Black Widow.

To create a basic radar plot, we’ll use geom_col and build on this with coord_polar - curving our bar on a polar coordinate grid.

black_widow <- df_avengers%>%filter(name=="Black Widow")

ggplot(data=black_widow, aes(x=ability,y=stat))+
  geom_col()+
  coord_polar()

Starting from Scratch

To make this truly custom, we’ll need to work with a blank canvas, using ggplot’s theme_void. From there, we’ll add back the things we need - namely grid lines and axis labels.

We can add our y grid lines them back in with ggplot’s geom_segment.

To create our x axis labels, we will use new ggplot extension package, geomtextpath. This library helps us create curved labels around our radar plot with geom_textpath.

library(geomtextpath)

#custom dataframe for line segments
segments<- data.frame(
  x1=rep(0,5),
  x2=rep(5.5,5),
  y1=c(0,25,50,75,100),
  y2=c(0,25,50,75,100)
)

plot<-ggplot(black_widow, aes(x=ability, y=stat, fill=ability))+
  #circular coordinates
  coord_polar()+
  #blank canvas
  theme_void()+
  #new x labels
  geom_textpath(inherit.aes=FALSE,
               mapping=aes(x=ability, label=ability, y=130),
               fontface="bold", upright=TRUE, text_only=TRUE, size=3)+
  #new grid lines - leave space to add in our y axis labels later
  geom_segment(inherit.aes=FALSE,
               data = segments,
               mapping=aes(x=x1,xend=x2,y=y1,yend=y2), linewidth=0.35)

plot

Keep Building

Now that we have our new outline, we’ll overlay our Black Widow data and continue to customize.

Add in the data with ggplot geom_col. We’ve already set the aes mapping in the first step, but we’ll use the width argument to adjust the column size and suppress the legend by setting show.legend to FALSE.

To create the donut hole in the center, we’ll use scale_y_continuous to adjust the lower limit of our y scale. We’ll also add some padding at the top by creating an upper bound limit.

Finally, we’ll add back in our y axis labels using geomtextpath::geom_textsegment.

labels<-data.frame(
  y = c(25,50,75,100),
  x = rep(0.25,4)
)

plot<-plot+
  #overlay dataset
  geom_col(width=.8, show.legend = FALSE)+
  #create donut hole and add some room at the top with limits (our labels are at 130)
  scale_y_continuous(limits=c(-70,135))+
  #add the y axis labels
  geom_textsegment(inherit.aes=FALSE,
                   data=labels,
                   mapping=aes(x=5.5, xend=6.5, y= y, yend=y, label=y),
                   linewidth=0.35, size=2.5)

plot

Finishing Touches

Time for finishing touches! We’ll work with one of my favorite R packages, ggimage. Using geom_image, we can add png or jpeg images directly in our plot. Let’s go ahead and fill our donut hole with a portrait of Black Widow. I have one ready to use from my GitHub!

We’ll spruce up our bar graph color palette with scale_fill_manual. I love playing around with online palette generators like Coolors. You’re welcome to change them with your own hex colors!

Finally, we’ll add our plot titles and labels with ggplot labs and format their look and feel with our own theme. Put it all together, and it should look something like this:

library(ggimage)

#link to png file
image<-'https://raw.githubusercontent.com/tashapiro/superhero-comics/main/images/character-icons/black_widow.png'


plot+
  #add portrain in center
  geom_image(mapping=aes(y=-70,x=1), image=image, size=0.225)+
  #customize bar colors
  scale_fill_manual(values=c("#E1341A","#FF903B","#ffe850","#27f897",
                             "#4bd8ff" ,"#6F02CE"))+
  #add plot titles and labels
  labs(title="BLACK WIDOW",
       subtitle="Power Stats by Superhero. Abilities scaled from 0 to 100.",
       caption = "Data from Superhero API | Graphic @tanya_shapiro")+
  #make some tweaks to plot theme
  theme(
    plot.title=element_text(face="bold", hjust=0.5, size=18, vjust=-2),
    plot.subtitle=element_text(hjust=0.5, vjust=-5),
  )

Next Level Stuff

Below is the code for the final Avengers Radar plot I created. Uses all of our ggplot2 tricks and applies them to select characters with ggplot’s facet_wrap!

You can check out more Superhero radar plots on my GitHub. If you have any questions, feel free to reach out to me on Twitter @tanya_shapiro. Thank you!

Code

#add image links to dataset
df_avengers<-df_avengers%>%
  mutate(image = paste0('https://raw.githubusercontent.com/tashapiro/superhero-comics/main/images/character-icons/',tolower(str_replace(name, " ","_")),".png"))

#set color aesthetics as variables
#palettes
pal_font<-"white"
pal_bg <-"#131314"
pal_line <-"#D0D0D0"
pal<-c("#E1341A","#FF903B","#ffe850","#27f897","#4bd8ff","#6F02CE")

ggplot(df_avengers, aes(x=ability, y=stat, fill=ability))+
  #create y axis text
  geom_textpath(inherit.aes=FALSE,
                mapping=aes(x=ability, label=ability, y=130),
                fontface="bold", upright=TRUE, text_only=TRUE, linewidth=3, color=pal_font
                )+
  #image with cahracter icon in the center
  geom_image(mapping=aes(y=-70,x=1,image=image), size=0.225)+
  #text for actual name below superhero name
  geom_text(inherit.aes=FALSE,
            mapping=aes(label=full_name, x=1, y=-70),
            vjust=-13.6, color="white", size=3.25)+
  #create curved coordinate system, curvedpolar accomodates text
  coord_curvedpolar()+
  #create linesegments to represent panel gridlines
  geom_segment(inherit.aes=FALSE,
               data = segments,
               mapping=aes(x=x1,xend=x2,y=y1,yend=y2),
               linewidth=0.45, color=pal_line)+
  #bars
  geom_col(show.legend = FALSE, width=.8)+
  #text for panel gridlines
  geom_textsegment(inherit.aes=FALSE,
                   data=labels,
                   mapping=aes(x=5.5, xend=6.5, y= y, yend=y, label=y),
                   color = pal_line, textcolour= pal_font, linewidth=0.45, size=2.5)+
  #adjist scales for fill (custom palette) & create y scale limits (create blank circle at center to store image)
  scale_fill_manual(values=pal)+
  scale_y_continuous(limits=c(-70,135))+
  #iterate per character
  facet_wrap(~toupper(name))+
  #add labels & theme
  labs(title="THE AVENGERS",
       subtitle="Power Stats by Superhero. Abilities scaled from 0 to 100.",
       caption="Data from Superhero API | Graphic @tanya_shapiro")+
  theme_minimal()+
  theme(text=element_text(color=pal_font),
        plot.background = element_rect(fill=pal_bg),
        plot.title=element_text(face="bold", hjust=0.5, size=18, margin=margin(t=5)),
        plot.subtitle=element_text(hjust=0.5, margin=margin(t=5, b=20)),
        plot.caption = element_text(margin=margin(t=15)),
        axis.title=element_blank(),
        panel.grid = element_blank(),
        plot.margin=margin(t=10,b=5,l=10,r=10),
        axis.text=element_blank(),
        axis.ticks = element_blank(),
        strip.text=element_text(face="bold", color=pal_font, size=12, vjust=-0.5))