Data visualization is important for communicating results. Selecting the right graphical representation of your data can enhance your data storytelling. In this article, I’ll show you how to implement drill-down using the echarts4r package, set and observe custom inputs, and use e_on() observers. We’ll do this ...

Sometimes, when you develop a Shiny application you want to download the results of their analysis as a report. Generating reports from Shiny applications is a very broad topic. So in this tutorial, we’ll focus on generating Word documents from table data. The example dataset used considers a scenario ...

In this post, you’ll learn how to scrape dynamic websites in R using {RSelenium} and {rvest}. Although some basic knowledge of rvest, HTML, and CSS is required, I will explain basic concepts through the post. So even beginners will find some use in this tutorial for webscraping dynamic sites ...

SAS is losing its footing across industries due to the rise of Shiny, an R package giving users bespoke interactivity on top of their R routines. In this article, we’ll discuss SAS vs R Programming in the context of the pharmaceutical industry, but the topic of conversation applies to ...

R Markdown is a format for writing reproducible, dynamic reports with R. The output from R Markdown is a markdown file that contains chunks of embedded R code. With R Markdown you can create different types of files: HTML documents, PDFs, Word Documents, slideshows, and more. It’s a versatile ...