R Weekly Highlights Issue 2024-W49 Highlights
6 snips
Dec 4, 2024 The hosts explore a unique R package that honors contributors to open-source projects, perfect for the holiday spirit. They dive into innovative strategies for addressing missing data using interpolation techniques. A spotlight on analyzing NBA shot data uncovers predictive modeling secrets for superstars like Steph Curry. Plus, hear about performance optimization in Shiny applications with clever caching methods. Community engagement takes center stage as listeners are invited to participate and connect.
AI Snips
Chapters
Transcript
Episode notes
Acknowledge Contributors
- Acknowledge open-source contributions with the
allcontributorsR package. - It automates contributor recognition in READMEs, linking to their contributions.
Handling Missing Data
- Missing data is a common challenge in real-world data analysis.
- Interpolation, using packages like
zoo, helps address missing values, but consider the implications.
Shiny App Performance
- Optimize Shiny app performance with caching.
- Explore various caching methods like reactive caching, in-memory caching, and Redis.