dataCleanr is designed for addressing common data management tasks encountered when preparing data for archive and reuse. Many of these functions were created by the Environmental Data Initiative's Data Curation Team to accelerate their data curation efficiency, and we welcome contributions from anyone.
# Install from GitHub
remotes::install_github("EDIorg/dataCleanr")
Check out example use cases in the dataCleanr website articles
dataCleanr focuses on user friendly high level functions for common data cleaning tasks in preparation for archive. Functionality should be accessible to R beginners.
We welcome contributions of all forms including bug reports, feature requests, and new functionality. Please reference our code conduct and contributing guidelines for submitting pull requests.
Unit tests are implemented with testthat.
Versioning for the dataCleanr follows semantic versioning.