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Synopsis
The Python Data Science Handbook provides a reference to the breadth of computational and statistical methods that are central to data-intensive science, research, and discovery. People with a programming background who want to use Python effectively for data science tasks will learn how to face a variety of problems: e.g., how can I read this data format into my script? How can I manipulate, transform, and clean this data? How can I visualize this type of data? How can I use this data to gain insight, answer questions, or to build statistical or machine learning models?
This book is a reference for day-to-day Python-enabled data science, covering both the computational and statistical skills necessary to effectively work with . The discussion is augmented with frequent example applications, showing how the wide breadth of open source Python tools can be used together to analyze, manipulate, visualize, and learn from data.
"synopsis" may belong to another edition of this title.
About the Author
Jake VanderPlas is a long-time user and developer of the Python scientific stack. He currently works as an interdisciplinary research director at the University of Washington, conducts his own astronomy research, and spends time advising and consulting with local scientists from a wide range of fields.
"About this title" may belong to another edition of this title.
- PublisherO′Reilly
- Publication date2016
- ISBN 10 1491912057
- ISBN 13 9781491912058
- BindingPaperback
- LanguageEnglish
- Number of pages548
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Python Data Science Handbook: Essential Tools for Working with Data
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O'Reilly Media (edition 1), 2017
ISBN 10: 1491912057
ISBN 13: 9781491912058
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