See how to query documents using natural language, LLMs, and R—including dplyr-like filtering on metadata. Plus, learn how to ...

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 the 1990s, ...

Colors are an effective medium for communicating meaning. Of all the design elements in a given data visualization – the headings, the analysis, the comparisons, and so on – color is arguably ...

Designed to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of ...

Aesthetics—the use of the right visual size, typography, flow and color—can significantly bolster data visualization. Some recommendations include the following.

Leverage Color: Color is a subtle, yet highly effective way to map data. For example: you could choose to make an anomalous point in your dataset red to immediately differentiate it from other points.

The best data visualization tools should be easy to use (or come with a comprehensive tutorial), handle large amounts of data points, and be able to convert different data subsets into multiple ...

Instead of telling people about a story, data, or information, show them. Here are tips to make your data visualization more engaging and effective.