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Python programming and visualization for scientists / Alex J. DeCaria.

By: Publisher: Madison, WI Sundog Pub., LLC, 2016Description: pages 270 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780972903387 (soft cover)
  • 0972903380 (soft cover)
Subject(s): Summary: Python has rapidly become a dominant language in the scientific community for analyzing and visualizing data, in part due to its concise, intuitive syntax and free availability without the purchase of an expensive license. The syntax of the language itself is easy to pick up, but learning how to plot, visualize, and analyze scientific data has required more effort in the past, as the relevant resources are spread across the Internet. Hence, the idea for this book. Specifically, the author wrote it from the perspective of, "What book would I have wanted to have when I was transitioning to Python?" This book will be useful not only as a classroom text but also as a guide and reference for students, educators, and researchers who have some programming experience already and want to start creating plots and analyzing data using Python. It is not meant for the person who is completely new to programming, nor is it an introductory computer science textbook. The author s assumption is that the reader has some experience programming, though not necessarily with Python. Although the new Python programmer may wish to read the book cover to cover, the book is organized such that the experienced Python programmer who wants to get started in plotting data can readily jump to the appropriate chapter. The last few chapters include topics that are more advanced, such as using regular expressions for matching text patterns, performing spectral analysis of data, and solving systems of linear equations.
Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
BOOK BOOK NCAR Library Mesa Lab QA76.73 .P98 .D43 2016 1 Checked out 07/01/2024 50583020004564
Total holds: 0

Python has rapidly become a dominant language in the scientific community for analyzing and visualizing data, in part due to its concise, intuitive syntax and free availability without the purchase of an expensive license. The syntax of the language itself is easy to pick up, but learning how to plot, visualize, and analyze scientific data has required more effort in the past, as the relevant resources are spread across the Internet. Hence, the idea for this book. Specifically, the author wrote it from the perspective of, "What book would I have wanted to have when I was transitioning to Python?"

This book will be useful not only as a classroom text but also as a guide and reference for students, educators, and researchers who have some programming experience already and want to start creating plots and analyzing data using Python. It is not meant for the person who is completely new to programming, nor is it an introductory computer science textbook. The author s assumption is that the reader has some experience programming, though not necessarily with Python.

Although the new Python programmer may wish to read the book cover to cover, the book is organized such that the experienced Python programmer who wants to get started in plotting data can readily jump to the appropriate chapter. The last few chapters include topics that are more advanced, such as using regular expressions for matching text patterns, performing spectral analysis of data, and solving systems of linear equations.

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