Visual charts help patterns and trends stand out faster than raw numbers alone. Different visualization types suit different data goals and levels of detail. Clear visuals improve understanding across ...

As the data center backlash grows, support is growing for server factories and the hundreds of jobs they’re expected to bring. Save this story Save this story Last month, Pamela Griffin and two other ...

Every year, designers at Pew Research Center create hundreds of charts, maps and other data visualizations. We also help make a range of other digital products, from “scrollytelling” features to ...

Here, projects are written in R, one of the most popular programming languages for data analysis and Data Science. Whether you're a beginner or an experienced programmer, you'll find something here ...

Successfully built a crop yield prediction system using advanced machine learning in R, which leverages agro-environmental, soil, and weather data to forecast agricultural yield (in tons per hectare).

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

The social science data analysis and visualization minor introduces students to the fundamentals and current innovations of research and data analysis across social science disciplines. It equips ...

Data visualizations are some of the most powerful tools in a climate science communicator’s playbook. The most famous have taken on enormous symbolic value—like the “Hockey Stick” graph showing rising ...

Representative visualization features of the GseaVis R package showing enhanced GSEA plots, multi-pathway comparisons, heatmap annotations, and circular layout options for comprehensive gene set ...

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. One of the ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.