Great Books About Data Analysis

These are the textbooks that I love and that I use as a daily reference. They are all openly accessible.


  • R for Data Science: An introduction to data analysis with R/Tidyverse by Hadley Wickham and Garret Grolemund.
  • Introduction to Data Science - A detailed introduction to Data science by the biostatistician Rafael A. Irizarry.
  • Advanced R - All you wish to know about programming in R by Hadley Wickham.
  • Introduction to Statistical Learning - A detailed introductio to modern statistical methods, implemented in R by Gareth James, Jeffrey Heer, Dominik Moritz, Jake VanderPlas, and Brock Craft, Trevor Hastie and Rob Tibshirani.
  • Text Mining in R Analyzing natural language and written text in R, by Julia Silge and David Robinson.
  • Tidy Modeling with R An introduction to the tools that compose R’s machine learning framework, by Max Kuhn and Julia Silge.
  • Analising Data Using Linear Models, for students in social, behavioural and management science, by Stéphanie M. van den Berg.



Git / Github

Project management

Dataviz Design



Computer Science

  • Missing Semester A generic intro to basic CS productivity tips and tools, by Anish Athalye.

Bayesian Statistics in R and Python


  • Geocomputation with R; a book on geographic data analysis, visualization and modeling by Robin Lovelace, Jakub Nowosad and Jannes Muenchow.
  • Spatial Data Science; concepts, packages and models for spatial data science in R, by Edzer Pebesma, Roger Bivand.

More Books at Bookdown

  • Check out the bookdown repository for many more.


Support the authors of these textbooks with the means that are available to you, they are heroes.


Sourced from my github repo Great Books About Data Analysis, check it for the most updated version.