moai-lang-r

What problem does it solve?

Performing robust data analysis and statistical modeling in R requires adherence to best practices for code quality, testing, and reproducibility. This Skill provides expert guidance for R 4.4+, integrating testthat 3.2 for testing and lintr 3.2 for code quality, ensuring your data science projects are reliable and maintainable.

Core Features & Use Cases

• R 4.4+ Best Practices: Guides on leveraging new language features, efficient data manipulation, and statistical modeling techniques.
• Reproducible Testing: Implement test-driven development for R scripts and packages using testthat 3.2.
• Code Quality & Style: Enforce consistent code style and catch common errors with lintr 3.2.
• Data Analysis Patterns: Provides patterns for data cleaning, transformation, visualization, and model building.
• Use Case: When developing a new statistical model, this Skill can help you structure your R code, write unit tests for your functions, and ensure your script adheres to best practices for reproducibility and maintainability.

Quick Start

Install R packages

install.packages(c("testthat", "lintr"))

Run tests

testthat::test_dir("tests/")

Lint R code

lintr::lint("my_script.R")

Claude can then assist with data manipulation and model development.