awesome-R VS freeCodeCamp

Compare awesome-R vs freeCodeCamp and see what are their differences.

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awesome-R freeCodeCamp
6 40
5,811 390,270
- 1.2%
4.0 10.0
3 months ago 4 days ago
R TypeScript
- BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

awesome-R

Posts with mentions or reviews of awesome-R. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-13.

freeCodeCamp

Posts with mentions or reviews of freeCodeCamp. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-13.

What are some alternatives?

When comparing awesome-R and freeCodeCamp you can also consider the following projects:

fontawesome - Easily insert FontAwesome icons into R Markdown docs and Shiny apps

developer-roadmap - Interactive roadmaps, guides and other educational content to help developers grow in their careers.

easystats - :milky_way: The R easystats-project

hardhat-starter-kit - A repo for boilerplate code for testing, deploying, and shipping chainlink solidity code.

sf - Simple Features for R

html5-boilerplate - A professional front-end template for building fast, robust, and adaptable web apps or sites.

lab02_R_intro - Vežbe 2: Uvod u R

tech-interview-handbook - 💯 Curated coding interview preparation materials for busy software engineers

viridis - Colorblind-Friendly Color Maps for R

free-programming-books - :books: Freely available programming books

fastverse - An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R

coding-interview-university - A complete computer science study plan to become a software engineer.