Python 3 and Data Analytics Pocket Primer
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Python 3 and Data Analytics Pocket Primer

Oswald Campesato
Paperback
March 2021
9781683926542
More details
  • Publisher
    Mercury Learning and Information
  • Published
    29th March 2021
  • ISBN 9781683926542
  • Language English
  • Pages 238 pp.
  • Size 6" x 9"
  •    Request Exam Copy
$39.95
Add to Cart
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March 2021
9781683926528
More details
  • Publisher
    Mercury Learning and Information
  • Published
    19th March 2021
  • ISBN 9781683926528
  • Language English
  • Pages 238 pp.
  • Size 6" x 9"
  •    Request E-Exam Copy
$39.95
Add to Cart
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March 2021
9781683926535
More details
  • Publisher
    Mercury Learning and Information
  • Published
    19th March 2021
  • ISBN 9781683926535
  • Language English
  • Pages 238 pp.
  • Size 6" x 9"
$129.95

As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data analytics using Python 3. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, and data cleaning. The book includes numerous code samples using NumPy, Pandas, Matplotlib, Seaborn, and features an appendix on regular expressions. Companion files with source code and color figures are available online by emailing the publisher with proof of purchase at info@merclearning.com.

FEATURES:

  • Includes a concise introduction to Python 3
  • Provides a thorough introduction to data and data cleaning
  • Covers NumPy and Pandas
  • Introduces statistical concepts and data visualization (Matplotlib/Seaborn)
  • Features an appendix on regular expressions
  • Includes companion files with source code and figures

1: Introduction to Python
2: Working with Data
3: Introduction to NumPy
4: Introduction to Pandas
5: Introduction to Probability and Statistics
6: Data Visualization
Appendix
Regular Expressions
Index

Oswald Campesato

Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty-five books including Google Gemini for Python, Large Language Models, and GPT-4 for Developers (all Mercury Learning).

Computer Science; Data Analytics; Programming; Python; NumPy; Pandas; Matplotlib; Seaborn