Finally, this part closes by listing the various methods with which one might make JavaScript work with R. Then it briefly describes concepts essential to understanding the rest of the book to ensure the reader can follow along. The book opens with an introduction to illustrate its premise better it provides rationales for using JavaScript in conjunction with R, which it supports with existing R packages that use JavaScript and are available on CRAN. All of these, along with the code for the entire book, can be found on the GitHub repository: /JohnCoene/javascript-for-r. Throughout the book, several Shiny applications and R packages are put together as examples. Moreover, the book focuses on generalisable learnings so the reader can transfer takeaways from the book to solve real-world problems. Therefore, the focus is on integrating external JavaScript libraries and only limited knowledge of JavaScript is required in order to learn from the book. In that respect, the book is not teaching one JavaScript but instead demonstrates how little JavaScript can significantly support and enhance R code.
The ultimate aim of this work is to demonstrate to readers the many great benefits can reap by inviting JavaScript into their data science workflow. Little known to many, R works just as well with JavaScript-this book delves into the various ways both languages can work together. The R programming language has seen the integration of many languages C, C++, Python, to name a few, can be seamlessly embedded into R so one can conveniently call code written in other languages from the R console. 15.4.6 Subscribe and Unsubscribe Inputs.
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