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Extract colors from any website or an existing CSS code, regroup/order colors, then generate a palette including a CSS/Sass file.

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Effortlessly convert Excel (or other spreadsheets) to Markdown Table. Utilize the Table Editor to create and modify Markdown Table online.

Build CLI applications in R.

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The Colormind has a REST API that allows you to build applications with beautiful generated color palettes

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Create an interactive table of Shiny inputs by providing data and a table definition.

How to fix error & warning messages in R - List of most common errors & warnings - Tutorials & examples on how to fix in RStudio

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Shiny is a package that makes it easy to create interactive web apps using R and Python.

a small data filter module for shiny.

Rectangling is the art and craft of taking a deeply nested list (often sourced from wild caught JSON or XML) and taming it into a tidy data set of rows and columns. This vignette introduces you to the main rectangling tools provided by tidyr: `unnest_longer()`, `unnest_wider()`, and `hoist()`.

Working with modern APIs you will often have to wrangle with data in JSON format. This article presents some tools and recipes for working with JSON data with R in the tidyverse. We’ll use purrr::map functions to extract and transform our JSON data. And we’ll provide intuitive examples of the cross-overs and differences between purrr ... Read more

R - JSON Files - JSON file stores data as text in human-readable format. Json stands for JavaScript Object Notation. R can read JSON files using the rjson package.

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Working with complex, hierarchically nested JSON data in R can be a bit of a pain. In this post, I illustrate how you can convert JSON data into tidy tibbles with particular emphasis on what I’ve found to be a reasonably good, general approach for converting nested JSON into nested tibbles. I use three illustrative examples of increasing complexity to help highlight some pitfalls and build up the logic underlying the approach before applying it in the context of some real-world rock climbing competition data.