Bookdowns

In this chapter we aim at adding HTTP testing infrastructure to exemplighratia2 using httptest2. For this, we start from the initial state of exemplighratia2 again. Back to square one!...

This is a compilation of lecture notes that accompany my Intro to GIS and Spatial Analysis course.

Welcome | Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data.

A book created with bookdown.

Oui.

A book about engineering shiny application that will later be sent to production. This book cover project management, structuring your project, building a solid testing suite, and optimizing your codebase. We describe in this book a specific workflow: design, prototype, build, strengthen and deploy.

An introductory book to R written by, and for, R pirates

Writing R Extensions covers how to create your own packages, write R help files, and the foreign language (C, C++, Fortran, …) interfaces.

This is a workshop for RStudio::conf(2020) in San Francisco, California

Second edition of R Cookbook

This guide aims to introduce the reader to the main elements of the R ecosystem.

Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It’s about both computational and programmer efficiency.

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Extended version of the rOpenSci packaging guide. This book is a guide for authors, maintainers, reviewers and editors of rOpenSci. The first section of the book contains our guidelines for creating and testing R packages. The second section is dedicated to rOpenSci’s software peer review process: what it is, our policies, and specific guides for authors, editors and reviewers throughout the process. The third and last section features our best practice for nurturing your package once it has been onboarded: how to collaborate with other developers, how to document releases, how to promote your package and how to leverage GitHub as a development platform. The third section also features a chapter for anyone wishing to start contributing to rOpenSci packages.

An introduction to Docker and PostgreSQL for R users to simulate use cases behind corporate walls.