R-bloggers

Introduction Are you working with a dataset in R that has missing values? Don’t worry, it’s a common issue that every R programmer faces. In this in-depth guide, we’ll cover various techniques to effectively handle and replace missing values in...

Yellow post box – CC-BY-SA by Elliott Brown Day 30 of 30DayMapChallenge: « The final map » (previously). Creating a raw polygon layer of french postal codes from points This data, although not a “real” administrative lim...

I recently read John Cox’s 2018 book Fast Money Schemes: Hope and Deception in Papua New Guinea and gave it a rare (for me) five star rating. It’s fascinating research into those involved in the U-Vistract pyramid scheme. At the time of writing U-Vist...

Introduction The command line is an essential part of working with Linux, and the bash prompt is your gateway to this powerful interface. While the default prompt gets the job done, customizing it can greatly enhance your productivity and make ...

Introduction Missing data is a common problem in data analysis. Fortunately, R provides powerful tools to handle missing values, including the zoo library and the na.approx() function. In this article, we’ll explore how to use these tools to in...

Joseph Rickert and I put together an experiment trying to both run a standard meta-analysis and then reproduce similar results directly using Bayesian methods. I think it came out really interesting and we share it here at R Works and also here on Github. A meta-analysis is an attempt to […]

Developing a Shiny app is relatively straightforward, but deploying it to a production environment is a whole another set of challenges. If you’re unfamiliar, R Shiny is a powerful web application framework for building interactive data visualizations, dashboards, and other data-driven applications. At Appsilon, we’re a big fan ...

If your organization is looking to build dynamic and interactive dashboards with a strong emphasis on performance or large scale, the Observable Framework could be an ideal fit. This article introduces the framework, its core features, and real-world use cases to illustrate how it can help your data science team ...

Introduction Loops are a fundamental concept in programming that allow you to execute a block of code repeatedly until a specified condition is met. In C, two commonly used loop constructs are the while loop and the do while loop. As a beginner...

I’m super stoked to announce {geotargets} version 0.2.0! The {geotargets} package extends {targets} to work with geospatial data formats. I’d like to firstly acknowledge the strong work by Eric Scott on getting this release ready. I do want...

Quite often, the involvement of a designer in a project is temporary, depending on the budget, deadlines, planning, etc. This approach is mainly used in projects with small budgets or at the POC stages, where a working prototype needs to be built to test hypotheses. From a utilization standpoint, this ...

Monitoring the Single-Celled Powerhouses of the Sea – CC-BY-NC by NASA’s Marshall Space Flight Center Day 26 of 30DayMapChallenge: « Map projections » (previously). After seeing this post by Cédric Vidonne I had to try to...

In this edition of Shiny Gatherings x Pharmaverse, we were thrilled to welcome Nina and Dony, Principal Data Scientists at Genentech, for an insightful session on building clinical data analysis apps using the {teal} framework. Explore how {teal} and {pharmaverseadam} simplify clinical dashboards for faster insights. Learn how these tools ...

Introduction When working with data frames in R, it’s common to encounter situations where you need to delete or drop multiple columns at once. Whether you’re cleaning up your dataset, removing unnecessary variables, or narrowing down your anal...

Introduction As an R programmer, comparing strings is a fundamental task you’ll encounter frequently. Whether you’re working with text data, validating user input, or performing string matching, knowing how to compare strings effectively is cru...