ModelData

Modeldata is an R package that serves as a curated repository of datasets and accompanying metadata intended for modeling tutorials and demonstrations. It is part of the tidymodels ecosystem, a collection of packages that promote tidy data principles and reproducible modeling workflows in R.

The primary purpose of modeldata is to provide clean, well-documented datasets that illustrate common data science tasks such as regression, classification, preprocessing, and feature engineering. Datasets within modeldata are typically prepared to have consistent column naming, data types, and missing-value handling to facilitate learning and to provide stable examples across tutorials and vignettes.

In addition to raw data, the package often includes descriptive metadata describing variable meanings, data sources, and licensing information. This metadata supports reproducibility and helps users understand the context for modeling tasks. The package is designed to be lightweight and easily installed from CRAN, and it is frequently used in documentation, package vignettes, and practice exercises within the tidymodels ecosystem.

Users interact with modeldata by loading the package and accessing its datasets via usual data loading commands; the project maintains compatibility with tidyverse tools and common modeling workflows. Because datasets come from public sources with varying licenses, licensing for individual data records is specified where applicable.

See also tidymodels, data science education, and reproducible research. Modeldata serves as a stable, educational resource for demonstrating data preparation, modeling pipelines, evaluation, and benchmarking in a consistent, incremental manner.