Abstract R is an open-source programming language and environment with powerful and extensive features for data analysis, data visualization, and statistical computing. Although R first appeared in ...

Several packages aim to streamline ggplot2 so common data visualizations are either simpler or more intuitive. If you tend to forget which geoms to use for what, I recommend giving ggblanket a try.

See how to query documents using natural language, LLMs, and R—including dplyr-like filtering on metadata. Plus, learn how to use an LLM to extract structured data for text filtering.

This year, my pitch on 5 data visualizations in R in 5 minutes, all in 5 lines of code or less was one of the winning proposals. Here is a version of that talk I recorded in advance.

Thanks to the Complete R Programming Certification Bundle, you can take a deep dive into over 35 hours of training to perfect your data wrangling and visualization skills.

The first commandment of data visualization is to define or identify the purpose—i.e., what to visualize or show. Purpose comes from knowing your stakeholders and their objectives.

In the hands of skilled analysts, data can make a powerful impression on its viewers and can change opinions. It can influence society and inform human behavior. Data analysis and visualization ...