R Shiny is a go-to technology when making apps and dashboards for companies using the R programming language. Shiny helps solve problems in complex business areas with large datasets, such as agriculture and life sciences. It’s also used extensively in business workflows from supply chain management to improving the ...

Real-world data is often messy and full of missing values. As a result, data scientists spend the majority of their time cleaning and preparing the data, and have less time to focus on predictive modeling and machine learning. If there’s one thing all data preparation steps share, then it’...

The shiny.benchmark package by Appsilon allows you to compare the performance of different versions of R Shiny applications. You can write instructions that will be executed and evaluated on different versions of your app and easily measure the performance differences. In today’s article, you’ll learn how to ...

Spatial data is always tougher to visualize than it seems at first. Well, not anymore. R ggmap is an amazing package you can start using almost instantly, after some light configuration. It won’t take you more than a couple of minutes to configure everything and have your first map ...

R programming language can read all sorts of data, and XML is no exception. There are many ways to read, parse, and manipulate these markup language files in R, and today we’ll explore two. By the end of the article, you’ll know how to use two R packages ...

Geospatial data is everywhere around us, and it’s essential for data professionals to know how to work with it. One common way to store this type of data is in GPX files. Today you’ll learn everything about it, from theory and common questions to R and GPX file ...

If you haven’t been living under a rock for the past couple of weeks, you’ve likely noticed some groundbreaking news in the Shiny department. Yes, it’s finally available for Python! But how is the current Shiny for Python version? How does R Shiny compare vs Shiny for ...

Data Science has (unnecessarily) divided the world into two halves – R users and Python users. Irrelevant of the group you belong to, there’s one thing you have to admit – each language individually has libraries far superior to anything available in the alternative. For example, R Shiny is much easier ...

R Shiny bslib is a package that makes working with Bootstrap themes a breeze. Let’s face it – Shiny apps look dull and mainstream by default. Not everyone has a keen eye for design, and sometimes spending days or weeks playing around with CSS isn’t an option. You need ...

If there’s one thing that can make your dashboards more intuitive to use, it’s icons. High-quality SVG icons can further explain, or sometimes replace long sections of text, and give your applications a fresh look. The best part is – you don’t have to be an expert designer ...

It’s easy to get down the basics of R and Shiny, but the learning curve becomes significantly steeper after a point. Reactive values? Reactive events? Reactive observers? Let’s face it – it’s easy to get lost. We’re here to help. Today you’ll learn all about the ...

R Quarto is a next-gen version of R Markdown. The best thing is – it’s not limited to R programming language. It’s also available in Python, Julia, and Observable. In this R Quarto tutorial, we’ll stick with the most popular statistical language and create Markdown documents directly in ...

It’s crucial you address R Shiny accessibility early on. Why? Because you want to make sure your data products can be used by all users – inclusivity matters. In a nutshell, that’s what web accessibility development means, but you’ll learn more about it in the context of R ...

Are your Shiny dashboards getting slow? Maybe it’s time to explore some R Shiny caching options. We’ve been there – a client wants dozens of charts on a single dashboard page, and wants it running smoothly. It’s easier said than done, especially if there’s a lot of ...

Being able to monitor user behavior lets you know why something works (or doesn’t) in your dashboard. It helps build your user adoption strategy with user behavior analytics. So what’s the best tool for the job? It’s Hotjar for R Shiny. And today you’ll learn how ...

If you want to talk about tried and tested programming paradigms, look no further than Object-Oriented Programming (OOP). The term was coined by Alan Kay way back in 1966, which means developers worldwide have been using it for more than five decades! Today we’ll dive deep into the basics of ...

R Shiny is a no-brainer dashboarding choice for companies and individuals. There are thousands of Shiny dashboards in production today in every sector you can imagine – agriculture being no exception. Today we bring you 5 dashboard examples of R Shiny in agriculture. We’ll show you what’s possible using Shiny ...

Visualizing spatial data is always more challenging than it seems at first. There are too many moving parts, and the whole thing can quickly slow down your dashboard. Today you’ll learn how to connect Google Earth Engine with R Shiny. We’ll start by signing up for a free ...

Can you monitor user adoption for R Shiny apps? What is user adoption anyway? We’ll answer these questions and show you how to do it yourself in this article. Put simply, user adoption is the process by which new users become familiar with your product and/or service and ...

Data Science take-home challenges will definitely get you out of your comfort zone. But you know what? That’s a good thing – it’s the only zone in which you’ll learn something, after all. Taming the take-home challenges is necessary both for beginner and advanced R programmers, but the ...