Using dbscan with tidyverse

In dbscan: Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms

knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

The dbscan package provides tidy(), augment(), and glance() methods for its clustering algorithms, making them easy to use with tidyverse, ggplot2, and tidymodels.

Load the packages and prepare the numeric variables from the iris data:

library(dbscan)
library(tidyverse)

x <- iris[, 1:4]
db <- x %>% dbscan(eps = .42, minPts = 5)

Get cluster statistics as a tibble:

tidy(db)

Visualize the clustering with ggplot2, using an x for noise points:

augment(db, x) %>%
  ggplot(aes(x = Petal.Length, y = Petal.Width)) +
  geom_point(aes(color = .cluster, shape = noise)) +
  scale_shape_manual(values = c(19, 4))

dbscan documentation built on Oct. 5, 2026, 9:07 a.m.