Search Results for "dependencies"

easystats is a meta‑package that installs and unifies a suite of R packages for post‑processing statistical models. It delivers a consistent API to assess model performance, effect sizes, parameters, and to generate reports and visualizations, all with minimal dependencies and maximum clarity.

data.table is an R package that extends base R’s data.frame for high-performance data manipulation. It offers concise syntax, blazing speed, and memory-efficient operations. It supports fast file reading/writing, joins, grouping, reshaping, and updates by reference. It is heavily used in large data workflows, big data in R, production pipelines, etc. Extremely efficient grouping/aggregation/summarization; can handle very large datasets (hundreds of millions to billions of rows) in memory (if...

paletteer is an R package by Emil Hvitfeldt that aggregates color palettes from many other R packages, providing a unified, streamlined interface to access discrete, continuous, and dynamic palettes. It is intended to simplify choosing color schemes when plotting, remove the friction of remembering different palette package APIs, and make high‐quality color aesthetics more accessible. Some palettes change depending on the number of colors requested; the ability to reverse palettes. Support...

The targets package is a pipeline / workflow management tool in R, designed to coordinate multi‐step computational workflows in data science / statistics. It tracks dependencies between “targets” (computational steps), skips steps whose upstream data or code hasn’t changed, supports parallel computation, branching (dynamic generation of sub‐targets), file format abstractions, and encourages reproducible and efficient analyses. It’s something like GNU Make for R, but more integrated. Skipping computation for up-to-date targets so that unchanged parts of the workflow are not recomputed. ...

box is an R package providing a modular system / module loader for organizing reusable R code outside of full packages. It allows users to treat R scripts (files/folders) as modules — possibly nested — with explicit exports, imports, and scoping. The idea is to let users structure code in a more modular, composable way, without needing every reusable component to be a full CRAN-style package. It also provides a cleaner syntax for importing functions or modules (via box::use) that allows...

reprex is an R package (from the tidyverse / Posit ecosystem) that helps users make reproducible examples (reprexes) of R code: self-contained, shareable, minimal examples capturing an issue or showing desired behavior. It formats code and its output nicely (often using Markdown or syntax appropriate to posting on forums, GitHub, StackOverflow etc.), handles dependencies, session info, etc. The goal is to make debugging, asking for help, or demonstrating code easier through rigorous reproducible examples. Get slightly different Markdown, optimized for Slack messages. Handles dependencies (e.g. load required libraries inside the reprex) so that code example is self-contained. Captures session information (R version, package versions etc.) so that context is preserved when sharing.

rpkgs (in GitHub via hadley/r-pkgs) is the source (text + examples) for the book R Packages by Hadley Wickham and Jenny Bryan. The book teaches how to develop, document, test, and share R packages: the practices, tools, infrastructure, workflows, and best practices around package development in R. The repository contains the code, text, site content for building the book, examples, exercises, etc. It is not a software library to be loaded in R (except perhaps the examples), but a...

Code for modeling estimated deaths and infections for COVID-19 from "Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe", Flaxman, Mishra, Gandy et al, Nature, 2020, the published version of our original Report 13. This is the release related to our Tiers paper, where we use the latent factor model to estimate the effectiveness of tiers systems in England. Peer-reviewed version is to be out soon. All other code is still the same for previous releases. The code...

palmerpenguins is an R package offering real-world ecological data from the Palmer Archipelago penguin species—Adélie, Chinstrap, and Gentoo. Designed as a more engaging alternative to the classical iris dataset, it provides size measurements, clutch information, and blood isotope data for teaching, visualization, and analytics practice.