Building reproducible analytical pipelines with R
Build reproducible analytical pipelines to output consistent, high-quality data products using R, Github and Docker. Learn about functional and literate programming to keep your code concise, easier to test and share and easily understandable by others by packaging it. Run your pipelines on Github Actions and focus on what matters: analysing data!
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Build reproducible analytical pipelines to output consistent, high-quality data products using R, Github and Docker. Learn about functional and literate programming to keep your code concise, easier to test and share and easily understandable by others by packaging it. Run your pipelines on Github Actions and focus on what matters: analysing data!
About
About the Book
This book will not teach you about the R programming language, machine learning, statistics or visualisation. The goal is to teach you a set of tools, practices and project management techniques that should make your projects easier to reproduce, replicate and retrace. These tools and techniques can be used right from the start of your project at a minimal cost, such that once you’re done with the analysis, you’re also done with making the project reproducible. Your projects are going to be reproducible simply because they were engineered, from the start, to be reproducible.
Building on your knowledge of R, you will learn about several packages to build reproducible analytical pipelines: {renv}, {targets}, {fusen} but also about trunk-based development with Git and Github, and Docker.
You can read the online version for free here: https://raps-with-r.dev/
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About the Author
Bruno Rodrigues, Phd
Hi I'm Bruno and have been programming with the R language in a professional setting as well as a hobby for quite some time now. In my free time I'm either taking care of my family, working out, or reading ancient philosophy.
Episode 263
An Interview with Bruno Rodrigues, Phd
Contents
Table of Contents
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