shiny.semantic::grid() The main job of a data scientist is to provide meaningful insights, mostly through data visualizations and dashboards. More often than not, data science professionals struggle with HTML and...continue reading.
This article is part of a series on speeding up Shiny. Learn how to omit the server.r bottleneck and push actions to the browser in this article by Marcin Dubel....continue reading.
Updated: May 2020 by Appsilon Data Science How to Work Faster in RStudio In this article we have compiled many of our favorite RStudio keyboard shortcuts, tips, and tricks to...continue reading.
Updated August 2020: If you’d like to learn more about best practices for Remote Data Science Teams, read this article by Appsilon Senior Data Scientist Olga Mierzwa-Sulima. Much more of...continue reading.
The RStudio Conference in San Francisco last month was an amazing experience, and I will definitely attend again next year in Orlando. In this post, Pedro Coutinho Silva and I...continue reading.
Machine learning models grow more powerful every week, but the earliest models and the most recent state-of-the-art models share the exact same dependency: data quality. The maxim “garbage in –...continue reading.
Shiny is a great tool for fast prototyping. When a data science team creates a Shiny app, sometimes it becomes very popular. From that point this app becomes a tool used...continue reading.
In the last couple of years, real estate companies have shifted their focus to the digital world, and now almost all investments have an online system showing what apartments are...continue reading.
At Appsilon we frequently build advanced R/Shiny dashboards that need user authentication. I would like to share with you how we implement user management – user accounts, the authorization process...continue reading.
GIS / R / R News / Shiny / Visualization
Interactive visualization of geospatial data with R Shiny
April 17, 2021
