webR, Sanjiv Ranjan Das, and Causal Inference in R

Week 03-2024 [Issue 17]

Welcome to The Repo! 🚀

Great work deserves to be shared. Especially in data science.
Each edition, I'll curate three gems from the data science community:

🗄️ Re: Remarkable Repository
💻 P:   Prolific Programmer
🏢 O:  Outstanding Organization

I hope you find them as valuable and insightful as I do.
You can find me on GitHub finnoh!

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r-wasm/webr

🗄️ Repository | Teaching R in your browser

webR allows running R in your browser without requiring a dedicated server that executes the R code. Why is this relevant?

For example, it allows you new ways to teach a programming class, e.g., this talk by Nicola Rennie shows. Her slide deck illustrates, how anyone with a link to her presentation, can execute the R code right then and there. No more hassle of trying to get R running on every student, individual and different, laptop.

Consider leaving r-wasm/webr a star! ⭐️

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Sanjiv Ranjan Das

💻 Programmer | A massive book/blog on data science

For an open-source, 500 page, resource on all things data science, visit the website of Sanjiv Ranja Das. The author writes about a broad range of topics, with chapters on math for data science, open-source software, econometrics, Fourier transformations, digital portfolios, networks, text data, and more.

Thank you for your work Sanjiv Ranja Das!

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Causal Inference in R

🏢 Organization | Answering Causal Questions

Causal Inference in R is another open-source book, that is aptly named. In this resource, you find theory and R implementations from the start, e.g. from asking causal questions, all the way to estimating causal effects. I recommend taking a look at the sub-chapter on DAGs, as well as the use of machine learning for the estimation of causal effects.

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