The Top Ten Bestselling Leanpub Books In 2015

by Len Epp

published Dec 15, 2015

2015 was Leanpub’s best year in a number of ways, but the most important thing to us was seeing so many great books published by both new and incumbent Leanpub authors, reaching tens of thousands of new readers.

Every successful book has its own story. This is perhaps true in a unique way for Leanpub books, given our in-progress pubishing and variable pricing sales models.

So before we get to the list, here are some of the highlights:

Jeff Geerling’s book, Ansible for DevOps: Server and configuration management for humans made $25,000 in sales before he finished writing it, as he details in his great post, $25K in book sales, and I’m almost ready to publish.

Axel Rauschmayer’s book, Exploring ES6: Upgrade to the next version of JavaScript, made it to #9 on the list of the top ten bestsellers while simultaneously being available for free online outside the Leanpub bookstore.

Roger D. Peng’s R Programming for Data Science became the first Leanpub book to reach over 50,000 readers.

Data Science books had a huge presence on Leanpub this year, thanks largely to the contributions of a number of US-based academics. This movement was led by four scientists in particular, and we’d like to offer them special thanks and congratulations for their achievements and generosity (many of their books are available for a free minimum price on Leanpub): Brian Caffo, Jeff Leek, Roger D. Peng, and Elizabeth Matsui. For interviews with Roger, Jeff, and Brian, check out the Leanpub Podcast (full transcriptions are available on our blog).

Leanpub’s 2015 Top Ten Bestseller List

#10. Data Analysis for the Life Sciences by Rafael A Irizarry and Michael I Love

Data Analysis for the Life Sciences by Rafael A Irizarry and Michael I Love Title: Data Analysis for the Life Sciences
Authors: Rafael A Irizarry and Michael I Love
Description: Data analysis is now part of practically every research project in the life sciences. In this book we use data and computer code to teach the necessary statistical concepts and programming skills to become a data analyst. Instead of showing theory first and then applying it to toy examples, we start with actual applications and describe the theory as it becomes necessary to solve specific challenges. The book includes links to computer code that readers can use to follow along as they program.

Tweet to Rafael and Mike at @rafalab and @mikelove

#10. Ansible for DevOps: Server and configuration management for humans by Jeff Geerling

Ansible for DevOps: Server and configuration management for humans by Jeff Geerling Title: Ansible for DevOps: Server and configuration management for humans
Author: Jeff Geerling
Description: Ansible is a simple, but powerful, server and configuration management tool. Learn to use Ansible effectively, whether you manage one server—or thousands.

Tweet to Jeff at @geerlingguy

#9. Exploring ES6: Upgrade to the next version of JavaScript by Axel Rauschmayer

Exploring ES6: Upgrade to the next version of JavaScript by Axel Rauschmayer Title: Exploring ES6: Upgrade to the next version of JavaScript
Author: Axel Rauschmayer
Description: An in-depth book on ECMAScript 6, for JavaScript programmers.

Tweet to Axel at @rauschma

#8. The Art of Data Science: A Guide for Anyone Who Works with Data by Roger D. Peng and Elizabeth Matsui

The Art of Data Science: A Guide for Anyone Who Works with Data by Roger D. Peng and Elizabeth Matsui Title: The Art of Data Science: A Guide for Anyone Who Works with Data
Authors: Roger D. Peng and Elizabeth Matsui
Description: This book describes the process of analyzing data in simple and general terms. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science.

Tweet to Roger and Elizabeth at @rdpeng and @eliza68!

#7. Software Architecture for Developers: Technical leadership by coding, coaching, collaboration, architecture sketching and just enough up front designThe Art of Data Science: A Guide for Anyone Who Works with Data by Simon Brown

The Art of Data Science: A Guide for Anyone Who Works with Databy Simon Brown Title: Software Architecture for Developers: Technical leadership by coding, coaching, collaboration, architecture sketching and just enough up front design Author: Simon Brown
Description: A developer-friendly, practical and pragmatic guide to lightweight software architecture, technical leadership and the balance with agility.

Tweet to Simon at @simonbrown

#6. Exploratory Data Analysis with R by Roger D. Peng

Exploratory Data Analysis with R by Roger D. Peng
Title: Exploratory Data Analysis with R Author: Roger D. Peng Description: This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies. This book is based on the industry-leading Johns Hopkins Data Science Specialization, the most widely subscribed data science training program ever created.

Tweet to Roger at @rdpeng

#5. Build APIs You Won’t Hate: Everyone and their dog wants an API, so you should probably learn how to build them by Phil Sturgeon

Build APIs You Won't Hate: Everyone and their dog wants an API, so you should probably learn how to build them Title: Build APIs You Won’t Hate: Everyone and their dog wants an API, so you should probably learn how to build them.
Author: Phil Sturgeon
Description: Tasked with building an API for your company but don’t have a clue where to start? Taken over an existing API and hate it? Built your own API and still hate it? This book is for you.

Tweet to Phil at @philsturgeon

#4. ember 101: Learn Ember.js with ember-cli by Adolfo Builes

ember 101: Learn Ember.js with ember-cli by Adolfo Builes Title: ember 101: Learn Ember.js with ember-cli.
Author: Adolfo Builes
Description: Everything you wish you had known while learning to write Ember.js applications.

Tweet to Adolfo at @abuiles

#3. MEAN Machine: A beginner’s practical guide to the JavaScript stack by Chris Sevilleja and Holly Lloyd

MEAN Machine: A beginner's practical guide to the JavaScript stack by Chris Sevilleja and Holly Lloyd Title: MEAN Machine: A beginner’s practical guide to the JavaScript stack. Authors: Chris Sevilleja and Holly Lloyd
Description: A beginner’s practical guide to the JavaScript stack.

Tweet to Chris and Holly at @sevilayha and @hollylawly

#2. The Elements of Data Analytic Style: A guide for people who want to analyze data by Jeff Leek

The Elements of Data Analytic Style: A guide for people who want to analyze data Title: The Elements of Data Analytic Style: A guide for people who want to analyze data.
Author: Jeff Leek
Description: A guide for people who want to analyze data.

Tweet to Jeff at @jtleek

1. R Programming for Data Science by Roger D. Peng

R Programming for Data Science by Roger D. Peng Title: R Programming for Data Science
Author: Roger D. Peng
Description: This book brings the fundamentals of R programming to you, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization. The skills taught in this book will lay the foundation for you to begin your journey learning data science.

Tweet to Roger at @rdpeng

– Posted by Len Epp

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