Python Tools for Data Scientists Pocket Primer Oswald Campesato

Python Tools for Data Scientists Pocket Primer

Author: Oswald Campesato
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Book Title
Python Tools for Data Scientists Pocket Primer
Author
Oswald Campesato
ISBN
9781683928232
As part of the best-selling Pocket Primer series, this book is designed to provide a thorough introduction to numerous Python tools for data scientists. The book covers features of NumPy and Pandas, how to write regular expressions, and how to perform data cleaning tasks. It includes separate chapters on data visualization and working with Sklearn and SciPy. Companion files with source code are available. FEATURES: Introduces Python, NumPy, Sklearn, SciPy, and awk Covers data cleaning tasks and data visualization Features numerous code samples throughout Includes companion files with source code Binding Type: PaperbackAuthor: Oswald CampesatoPublisher: Mercury Learning and InformationPublished: 11/23/2022ISBN: 9781683928232Pages: 300Weight: 1.10lbsSize: 8.98h x 5.91w x 0.47d
As part of the best-selling Pocket Primer series, this book is designed to provide a thorough introduction to numerous Python tools for data scientists. The book covers features of NumPy and Pandas, how to write regular expressions, and how to perform data cleaning tasks. It includes separate chapters on data visualization and working with Sklearn and SciPy. Companion files with source code are available.

FEATURES:
  • Introduces Python, NumPy, Sklearn, SciPy, and awk
  • Covers data cleaning tasks and data visualization
  • Features numerous code samples throughout
  • Includes companion files with source code


Binding Type: Paperback
Author: Oswald Campesato
Publisher: Mercury Learning and Information
Published: 11/23/2022
ISBN: 9781683928232
Pages: 300
Weight: 1.10lbs
Size: 8.98h x 5.91w x 0.47d
As part of the best-selling Pocket Primer series, this book is designed to provide a thorough introduction to numerous Python tools for data scientists. The book covers features of NumPy and Pandas, how to write regular expressions, and how to perform data cleaning tasks. It includes separate chapters on data visualization and working with Sklearn and SciPy. Companion files with source code are available.

FEATURES:
  • Introduces Python, NumPy, Sklearn, SciPy, and awk
  • Covers data cleaning tasks and data visualization
  • Features numerous code samples throughout
  • Includes companion files with source code


Binding Type: Paperback
Author: Oswald Campesato
Publisher: Mercury Learning and Information
Published: 11/23/2022
ISBN: 9781683928232
Pages: 300
Weight: 1.10lbs
Size: 8.98h x 5.91w x 0.47d