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  • Format: ePub

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 …mehr

  • Geräte: eReader
  • mit Kopierschutz
  • eBook Hilfe
  • Größe: 1.43MB
  • FamilySharing(5)
Produktbeschreibung
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

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