[This article was first published on https://pacha.dev/blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
< !DOCTYPE html>
< charset="utf-8">
< http-equiv="X-UA-Compatible" content="IE=edge">
< name="viewport" content="width=device-width, initial-scale=1.0">
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
< header class="site-top">
HOME 🏠
< !-- categories are printed below this-->
< nav class="sidebar-nav">
Mauricio “Pachá” Vargas Sepúlveda
Blog with notes about R, Shiny, SQL, Python, Linux and C++. This blog is listed on R-Bloggers.
Categories
- Armadillo
- Arrow
- BibTeX
- Blogdown
- C++
- CRAN
- D3po
- DigitalOcean
- DuckDB
- Education
- GitHub
- Google Sheets
- Inkscape
- International Trade
- Interviews
- Kubernetes
- Latex
- Linear algebra
- Linear models
- Linux
- Manjaro
- Microsoft Excel
- NLP
- Non-English datasets
- OS X
- OpenBLAS
- Pelican
- Positron
- PostGIS
- PostgreSQL
- Python
- Quarto
- R
- R Packages
- R-Universe
- R4DS
- REST API
- RStudio
- RStudio Server
- Redatam
- Rick and Morty
- SPSS
- SQL
- Selenium
- Shiny
- Spreadsheets
- Stan
- Stata
- Statistics
- Tabler
- Tidyverse
- Ubuntu
- VSCode
- Windows
- Zotero
- cpp11
- cpp4r
- ggplot2
- golem
- plotnine
- purrr
- wbstats
< header id="title-block-header" class="quarto-title-block default">
How do you make a histogram with equally sized dots or squares for each observation, and colour them by another variable
Answering reader’s questions.
Author
Mauricio “Pachá” Vargas S.
Published
August 29, 2025
Because of delays with my scholarship payment, if this post is useful to you I kindly ask a minimal donation on Buy Me a Coffee that shall be used to continue my Open Source efforts. If you need an R package or Shiny dashboard for your team, you can email me or inquiry on Fiverr. The full explanation is here: A Personal Message from an Open Source Contributor
You can send me questions for the blog using this form.
I got this question from a reader: How do you make a histogram with equally sized dots or squares for each observation, and colour them by another variable?
I shall use the Palmer’s Penguins dataset to answer this, which contains observation about the species and body mass for a sample of penguins:
if (!require(palmerpenguins)) install.packages("palmerpenguins")
if (!require(dplyr)) install.packages("dplyr")
library(palmerpenguins)
library(dplyr)
glimpse(penguins)
Rows: 344 Columns: 8 $ species <fct> Adelie, Adelie, Adelie, Adelie, Adelie, Adelie, Adel… $ island <fct> Torgersen, Torgersen, Torgersen, Torgersen, Torgerse… $ bill_length_mm <dbl> 39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, … $ bill_depth_mm <dbl> 18.7, 17.4, 18.0, NA, 19.3, 20.6, 17.8, 19.6, 18.1, … $ flipper_length_mm <int> 181, 186, 195, NA, 193, 190, 181, 195, 193, 190, 186… $ body_mass_g <int> 3750, 3800, 3250, NA, 3450, 3650, 3625, 4675, 3475, … $ sex <fct> male, female, female, NA, female, male, female, male… $ year <int> 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007…
To use squares, one possibility is to create a discrete body mass variable by intervals and count by species and interval:
if (!require(tidyr)) install.packages("tidyr")
Loading required package: tidyr
if (!require(ggplot2)) install.packages("ggplot2")
Loading required package: ggplot2
if (!require(tintin)) install.packages("tintin")
Loading required package: tintin
library(tidyr) library(ggplot2) library(tintin) # Create quantile-based bins (wider bins) n_bins <- 5 # number of quantile bins d <- penguins %>% drop_na(body_mass_g, species) %>% mutate(body_mass_d = cut(body_mass_g, breaks = 4, dig.lab = 6)) %>% group_by(species, body_mass_d) %>% count() d
# A tibble: 9 × 3 # Groups: species, body_mass_d [9] species body_mass_d n <fct> <fct> <int> 1 Adelie (2696.4,3600] 71 2 Adelie (3600,4500] 73 3 Adelie (4500,5400] 7 4 Chinstrap (2696.4,3600] 26 5 Chinstrap (3600,4500] 40 6 Chinstrap (4500,5400] 2 7 Gentoo (3600,4500] 17 8 Gentoo (4500,5400] 72 9 Gentoo (5400,6303.6] 34
Now I can create a Tetris-style column plot where each square represents 5 penguins:
square_size <- 5 # square = 5 observations
d_squares <- d %>%
mutate(
full_squares = n %/% square_size, # number of full squares
remainder = n %% square_size, # remaining observations
partial_height = remainder / square_size # height of partial square
)
# Create full squares
full_squares_df <- d_squares %>%
filter(full_squares > 0) %>%
uncount(full_squares) %>%
group_by(species, body_mass_d) %>%
mutate(square_id = row_number() - 1,
y = square_id + 0.5,
height = 1,
square_type = "full") %>%
ungroup()
# Create partial squares
partial_squares_df <- d_squares %>%
filter(remainder > 0) %>%
mutate(square_id = full_squares,
y = full_squares + partial_height/2,
height = partial_height,
square_type = "partial")
# Combine both
d_squares <- bind_rows(full_squares_df, partial_squares_df)
# Create Tetris-style column plot with grouped squares
ggplot(d_squares, aes(x = body_mass_d, y = y, fill = species)) +
geom_tile(aes(height = height), width = 0.9, color = "white", linewidth = 0.5) +
scale_x_discrete(name = "Body mass intervals") +
scale_y_continuous(name = paste0("Count (each full square = ", square_size, " penguins)"),
expand = expansion(add = 0)) +
scale_fill_tintin_d(option = "the black island", direction = -1) +
labs(title = "Column plot with grouped squares") +
facet_wrap(~species) +
theme_minimal(base_size = 13) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
I hope this is useful 🙂
Loading…
