Using dbscan from Python

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.

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)

labels = np.asarray(db.rx2("cluster"), dtype=int)
labels

Using dbscan from Python

Michael Hahsler