Using dbscan from Python

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

### run with: 
#DBSCAN_RUN_PYTHON_VIGNETTE=true Rscript -e 'rmarkdown::render("vignettes/python.Rmd")'

run_python <- identical(
  tolower(Sys.getenv("DBSCAN_RUN_PYTHON_VIGNETTE")),
  "true"
)
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

if (run_python) {
  Sys.setenv(RETICULATE_PYTHON = "managed")
  reticulate::py_require(c("numpy", "pandas", "rpy2"))
}

R, the R package dbscan, and the Python package rpy2 need to be installed. The following example reads the iris data and calls the R implementation of DBSCAN from Python.

The Python chunks are not run during a normal package build. To execute them while rendering this vignette, set the environment variable DBSCAN_RUN_PYTHON_VIGNETTE=true. The first run uses reticulate to create a managed Python environment and install numpy, pandas, and rpy2. The environment is cached for later use, and all Python chunks run in one shared session.

```{python, eval=run_python} import pandas as pd import numpy as np import rpy2.robjects as ro

Prepare data.

iris = pd.read_csv( "https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data", header=None, names=["SepalLength", "SepalWidth", "PetalLength", "PetalWidth", "Species"], ) iris_numeric = iris[["SepalLength", "SepalWidth", "PetalLength", "PetalWidth"]]

Import the R dbscan package.

from rpy2.robjects import packages from rpy2.robjects import pandas2ri dbscan = packages.importr("dbscan")

Convert the pandas data frame using local conversion rules.

conversion_rules = ro.default_converter + pandas2ri.converter with conversion_rules.context(): iris_r = ro.conversion.get_conversion().py2rpy(iris_numeric)

db = dbscan.dbscan(iris_r, eps=0.5, minPts=5) print(db)

Extract the cluster assignment vector as a NumPy array:

```{python, eval=run_python}
labels = np.asarray(db.rx2("cluster"), dtype=int)
labels

Cluster label 0 identifies noise; positive integers identify clusters.

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