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Paperback. Etat : Very Good. Python has become a dominant computer programming language for analyzing and visualizing scientific 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 and can at times be confusing to the novice. This book is intended to provide a handy, clearly written tutorial on the most essential features of the language and its most widely used plotting and analysis libraries. Specifically, the author wrote it from the perspective of What book would I want to have had when I was transitioning to Python from another programming language? 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 quickly creating plots and analyzing data using Python. 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.…

Perfect Paperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Paperback. Etat : Very Good. Python has become a dominant computer programming language for analyzing and visualizing scientific 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 and can at times be confusing to the novice. This book is intended to provide a handy, clearly written tutorial on the most essential features of the language and its most widely used plotting and analysis libraries. Specifically, the author wrote it from the perspective of What book would I want to have had when I was transitioning to Python from another programming language? 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 quickly creating plots and analyzing data using Python. 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.…

paperback. Etat : Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

Paperback. Etat : Fair. Python continues to gain dominance as a language of choice for analyzing and visualizing scientific data. Although it has concise, intuitive syntax, learning how to plot and visualize data requires scouring the internet for documentation and examples. This book was written from the perspective of What book would the authors want to have had when they were transitioning to Python?A second edition of the book was made necessary by the transition to Python 3, which did not maintain full backward compatibility with earlier versions of the language. The second edition has been completely revised to ensure that all code examples work in Python 3. Additional chapters on the Pandas library and Cartopy have been included, as well as an appendix on Jupyter notebooks, which have become an important tool for developing and communicating code in both the research and educational settings.The 90 figures are mostly in color, and color syntax highlighting is used with all code samples throughout the text to facilitate visual recognition of program structure.The first edition of the book has proven useful not only as a classroom text but also as a guide and reference for students, educators, and researchers who already have programming experience and want to start creating plots and analyzing data using Python. The second edition will serve the same role. It is not meant for the person who is completely new to programming, nor is it an introductory computer science textbook. The authors' assumptions are that the reader has some experience programming with a language other than Python.Although the new Python programmer may wish to read the book cover to cover, the book is organized such that an experienced programmer can readily jump to the appropriate chapter. An extensive index aids in searching for functions and methods useful for data visualization and analysis.…

Paperback. Etat : Fair. Python continues to gain dominance as a language of choice for analyzing and visualizing scientific data. Although it has concise, intuitive syntax, learning how to plot and visualize data requires scouring the internet for documentation and examples. This book was written from the perspective of What book would the authors want to have had when they were transitioning to Python?A second edition of the book was made necessary by the transition to Python 3, which did not maintain full backward compatibility with earlier versions of the language. The second edition has been completely revised to ensure that all code examples work in Python 3. Additional chapters on the Pandas library and Cartopy have been included, as well as an appendix on Jupyter notebooks, which have become an important tool for developing and communicating code in both the research and educational settings.The 90 figures are mostly in color, and color syntax highlighting is used with all code samples throughout the text to facilitate visual recognition of program structure.The first edition of the book has proven useful not only as a classroom text but also as a guide and reference for students, educators, and researchers who already have programming experience and want to start creating plots and analyzing data using Python. The second edition will serve the same role. It is not meant for the person who is completely new to programming, nor is it an introductory computer science textbook. The authors' assumptions are that the reader has some experience programming with a language other than Python.Although the new Python programmer may wish to read the book cover to cover, the book is organized such that an experienced programmer can readily jump to the appropriate chapter. An extensive index aids in searching for functions and methods useful for data visualization and analysis.…

Paperback. Etat : Good. Book in Good condition.

Etat : Good. Exact ISBN match. Immediate shipping. No funny business.

paperback. Etat : Very Good. Complete and clean. All pages present and readable, binding intact. Highlighting or writing is absent or limited to a handful of pages. No water damage. Cover and spine may show light shelf wear, edge bumping, or minor creasing. May have a remainder mark, stickers or sticker residue, or a previous owner's name. Access codes, CDs, DVDs, and other bundled supplements may not be included and should be assumed used or missing unless the listing explicitly states otherwise.…

Etat : New.

Paperback or Softback. Etat : New. Python Programming and Visualization for Scientists. Book.

Etat : As New. Unread book in perfect condition.

Etat : New.

Paperback. Etat : New. 2nd ed.

Paperback. Etat : New. 2nd ed.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Paperback. Etat : Brand New. 8.90x5.90x0.70 inches. In Stock.

Paperback. Etat : New. 2nd ed.

Paperback. Etat : New. 2nd ed.

Paperback. Etat : new. New Copy. Customer Service Guaranteed.

PF. Etat : New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

PAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 210.

Etat : New. Print on Demand.

Etat : New. Print on Demand.

Etat : New. PRINT ON DEMAND.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Python continues to gain dominance as a language of choice for analyzing and visualizing scientific data. Although it has concise, intuitive syntax, learning how to plot and visualize data requires scouring the internet for documentation and examples. This book was written from the perspective of 'What book would the authors want to have had when they were transitioning to Python 'A second edition of the book was made necessary by the transition to Python 3, which did not maintain full backward compatibility with earlier versions of the language. The second edition has been completely revised to ensure that all code examples work in Python 3. Additional chapters on the Pandas library and Cartopy have been included, as well as an appendix on Jupyter not Elektronisches Buch, which have become an important tool for developing and communicating code in both the research and educational settings.The 90 figures are mostly in color, and color syntax highlighting is used with all code samples throughout the text to facilitate visual recognition of program structure.The first edition of the book has proven useful not only as a classroom text but also as a guide and reference for students, educators, and researchers who already have programming experience and want to start creating plots and analyzing data using Python. The second edition will serve the same role. It is not meant for the person who is completely new to programming, nor is it an introductory computer science textbook. The authors' assumptions are that the reader has some experience programming with a language other than Python.Although the new Python programmer may wish to read the book cover to cover, the book is organized such that an experienced programmer can readily jump to the appropriate chapter. An extensive index aids in searching for functions and methods useful for data visualization and analysis.…