The Data Science Books To Invest in Right Now
This list of data science books originates from a #DataEveryone Twitter chat in 2019. But a new friend @MendyYButler suggested that I recirculate it, given that the quest for data science knowledge is relevant now more than ever.
With each title, I will put the Twitter handle of the data scientist who suggested it so that if you want to interact or as questions about the title you can. Happy Reading!
For Embarking on the Journey
“An Introduction to R” by William Venables from @tladeras
“R for Data Science by Hadley Wickham and Garrett Grolemund” from @thedariaedits - “There were so many times I was talking to people with more experience who were just discovering some of the packages I already knew about because of the book.”
“Weapons of Math Destruction” by Cathy O’Neil from @daniebrant
“Fundamentals of Data Visualization” by Claus O’Wilke from @thomas_mock
“The Man Who Counted: A Collection of Mathematical Adventures” by Malba Tahan from @ogustavo_com
“R Programming for Data Science” by Roger D. Peng from @thomas_mock
“Statistical Programming in R for Dummies" from @dikayodata - “It’s well-written and engaging. I got really into it when I learned R the summer of 2018.”
For Diving off the Cliff (with a harness)
The Handbook of Discrete-Valued Time Series” from @ogustavo_com
“Advanced R” by Hadley Wickham from @JonTheGeek
“Information Dashboard Design” by Stephen Few from @tladeras
“Naked Statistics” by Charles Wheelan from @daniebrant
Building Shiny Apps” by Colin Fay from @tladeras
For Finding Data in the Details
Just because a book doesn’t formally come in the format of a data science tutorial doesn’t mean it doesn’t have important data-related lessons to contribute. The following titles may be rooted in the dealings of other industries, but isn’t also data science itself?
“The Immortal Life of Henrietta Lacks” by Shoshana Zuboff from @Bouzoulay - “It taught me a lot about ethics in data collection and informed consent.”
“The Age of Surveillance Capitalism” by Shoshana Zuboff from @suminisweird
“The Drunkard’s Walk: How Randomness Rules Our Lives” by Leonard Mlodinow from @ogustavo_com - “It’’s one thing to learn how to do the calculations. It’s another to perceive how it’s always around us.”
“Universal Principles of Design” by William Lidwell from @daniebrant - “I read it in my Design Principles class but I thought a lot how it could be applied to data visualizations.”
“The Lady Tasting Tea (translated from Portuguese)” by David Salsburg from @ogustavo_com - “It gives a historical view on how some statistical methods were created and developed as well as the motivation behind their creation.”
“The Emperor of All Maladies” by Siddhartha Mukherjee from @tladeras - “It’s about cancer and reminds me that the patients who undergo risky treatments are real heroes, and I need to be respectful of their data.”
“The Up Side of Down” by Megan McArdle from @dikayodata - “It has so many case students examining the ways that data can be interpreted and often tragically misused.”