Google full text of our books:


Statistics, Data Mining, and Machine Learning in Astronomy:
A Practical Python Guide for the Analysis of Survey Data
Željko Ivezić, Andrew J. Connolly, Jacob T. VanderPlas & Alexander Gray

Winner of the 2016 IAA Outstanding Publication Award, International Astrostatistics Association

Hardcover | 2014 | $99.95 | £83.95 | ISBN: 9780691151687
552 pp. | 7 x 10 | 12 color illus. 2 halftones. 173 line illus.
Add to Shopping Cart

eBook | ISBN: 9781400848911 |
Our eBook editions are available from these online vendors

Reviews | Table of Contents
Chapter 1[PDF] pdf-icon

Google full text of this book:

Errata (GitHub)

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers.

Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest.

  • Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets
  • Features real-world data sets from contemporary astronomical surveys
  • Uses a freely available Python codebase throughout
  • Ideal for students and working astronomers


"Ivezic and colleagues at the University of Washington and the Georgia Institute of Technology have written a comprehensive, accessible, well-thought-out introduction to the new and burgeoning field of astrostatistics. . . . The authors provide another valuable service by discussing how to access data from key astronomical research programs."--Choice

"A substantial work that can be of value to students and scientists interesting in mining the vast amount of astronomical data collected to date. . . . A well-prepared introduction to this material. . . . If data mining and machine learning fall within your interest area, this text deserves a place on your shelf."--International Planetarium Society


"This comprehensive book is surely going to be regarded as one of the foremost texts in the new discipline of astrostatistics."--Joseph M. Hilbe, president of the International Astrostatistics Association

"In the era of data-driven science, many students and researchers have faced a barrier to entry. Until now, they have lacked an effective tutorial introduction to the array of tools and code for data mining and statistical analysis. The comprehensive overview of techniques provided in this book, accompanied by a Python toolbox, free readers to explore and analyze the data rather than reinvent the wheel."--Tony Tyson, University of California, Davis

"The authors are leading experts in the field who have utilized the techniques described here in their own very successful research. Statistics, Data Mining, and Machine Learning in Astronomy is a book that will become a key resource for the astronomy community."--Robert J. Hanisch, Space Telescope Science Institute

Table of Contents


Subject Areas:

Shopping Cart options:

  • For ebooks:

Our eBook editions are available
from these online vendors:

  • Amazon Kindle Store
  • Many of our ebooks are available through
    library electronic resources including these platforms:

  • Books at JSTOR
  • Ebrary
  • Ebook Library
  • EBSCO Ebooks
  • MyiLibrary
  • Dawsonera (UK)

    • For hardcover/paperback orders in United States, Canada, Latin America, Asia, and Australia

     Hardcover : $99.95 ISBN: 9780691151687

    Add to shopping cart
    View contents of your shopping cart

    • For hardcover/paperback orders in Europe, Africa, the Middle East, India, and Pakistan

     Hardcover  £83.95 ISBN: 9780691151687

    Add to shopping cart
    View contents of your shopping cart

    Prices subject to change without notice

    File created: 7/11/2017

    Questions and comments to:
    Princeton University Press

    New Book E-mails
    New In Print
    PUP Blog
    Princeton APPS
    Sample Chapters
    Princeton Legacy Library
    Exam/Desk Copy
    Recent Awards
    Princeton Shorts
    Freshman Reading
    PUP Europe
    About Us
    Contact Us
    PUP Home

    Bookmark and Share 
    Send me emails
    about new books in:
    Astronomy And Cosmology
    More Choices