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Data Science · R Programming

R for Data Science

Hadley Wickham, Mine Çetinkaya-Rundel, Garrett Grolemund · 2nd edition · 2023

🆓 FreeBeginner★★★★★548 pages

Free online book covering the full tidyverse workflow: import, tidy, transform, visualize, model, and communicate data.

Why you should read this
If you work in academia or statistics, R is often preferred over Python. This book teaches the modern tidyverse approach.

Key Topics

ggplot2dplyrtidyrreadrData WranglingVisualizationModelingR Markdown

Chapters (5)

1Data Visualization14 key concepts

ggplot2 grammar of graphics

2Workflow Basics6 key concepts

Scripts, projects, file management

3Data Transformation16 key concepts

filter, select, mutate, summarize, group_by

4Tidy Data10 key concepts

Pivoting, separating, uniting

5Data Import12 key concepts

CSV, Excel, databases, APIs

Real-World Applications
  • Academic research
  • Biostatistics
  • Social science analysis
  • Financial modeling
Best For
R beginnersAcademic researchersStatisticians

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