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The primary goal of this book is to get you up to speed with tidy evaluation and how to write functions around tidyverse pipelines and grammars.

A modest and very incomplete listing of resources for tackling data science problems in R.

This is official open data science training for the Ocean Health Index.

This book is an introduction to functional programming and unit testing with the R programming language, for the purpose of data muning

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

Using Git and GitHub with R, Rstudio, and R Markdown

Learn from Virtual Workshops that take you through the entire Data-Science-for-Business process of solving problems with data science, using machine learning to create interactive applications, and distributing solutions within an organization.

The R task Force - R experts for all your needs

All the best Open Source & Software as a Tool (SaaS) tools in one place, ranked by developers and companies using them. Compare and browse tech stacks from thousands of companies and software developers from around the world.

Astral is the best way to manage your starred repositories on GitHub using tags, notes and a powerful search feature.

The book covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing useful data science results and products. You will obtain rigorous training in the R language, including the skills for handling complex data, building R packages and developing custom data visualizations. You will learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers.

An intuitive and practical approach to data analysis, data preparation and machine learning, suitable for all ages!

The Getting Things Done blog

David Allen's Getting Things Done® (GTD®) is the work-life management system that alleviates overwhelm, and instills focus, clarity, and confidence.David Allen's Getting Things Done®

Unpacking Data Science One Step At A Time.

A curated list of awesome READMEs. Contribute to matiassingers/awesome-readme development by creating an account on GitHub.

crosswalkr

I am working on a Shiny application which allows the user to upload data, do some analysis and processing on each variable in the data, and finally use the processed variables to build a statistical model. As there may be hundreds of variables in the data, the user may want ...

A book for Geospatial Health Analysis with R.

Well organized and easy to understand Web building tutorials with lots of examples of how to use HTML, CSS, JavaScript, SQL, PHP, Python, Bootstrap, Java and XML.