No Clocks

I write about self-development and performance improving. I share lessons and thoughts weekly here and to my popular newsletter – The Monday Digest.

It seems that the line between humans and technology is dissolving. This Goodsync review is one of the most futurists that emphasizes imminent dissolution focusing on artificial intelligence, noting how smart our machines have become in recent years, practically rivaling human intelligence.Yet, humans have also cha ...

A project template and directory structure for Python data science projects.

Fast, offline, and free documentation browser for developers. Search 100+ docs in one web app including HTML, CSS, JavaScript, PHP, Ruby, Python, Go, C, C++, and many more.

A free test data generator and API mocking tool - Mockaroo lets you create custom CSV, JSON, SQL, and Excel datasets to test and demo your software.

Becoming Minimalist inspires others to journey towards simple living. Own less, live more.

Online syntax highlighting for more than 100 languages, including C#, Java, PHP, Basic, Perl, Python, Pascal, SQL, JavaScript and others including rare and obscure ones!.

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.

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

A guide to making visualizations that accurately reflect the data, tell a story, and look professional.

This is a guide on how to conduct Meta-Analyses in R.

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.

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

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.

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

This site is powered by knitr and Jekyll. If you find any errors, please email winston@stdout.org

Business Analytics with R

A guide to authoring books with R Markdown, including how to generate figures and tables, and insert cross-references, citations, HTML widgets, and Shiny apps in R Markdown. The book can be exported to HTML, PDF, and e-books (e.g. EPUB). The book style is customizable. You can easily write and preview the book in RStudio IDE or other editors, and host the book wherever you want (e.g. bookdown.org).

Discover and install useful RStudio addins . Contribute to daattali/addinslist development by creating an account on GitHub.

A list of commonly used Git commands. Contribute to joshnh/Git-Commands development by creating an account on GitHub.

🔑 Password protected markdown html reports in R using libsodium - dirkschumacher/encryptedRmd