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MERCURY LEARNING and INFORMATION provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets. We embrace both traditional and innovative publishing models designed to accommodate the needs of the intended audience by using the appropriate delivery methods.
Python 3 and Data Analytics Pocket Primer
ISBN: 9781683926542
Pub Date: March 2021
Specs: 7 x 9 Paperback
Pages: 250
Price: $39.95
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.
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
BRIEF TOC
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.
ABOUT THE AUTHOR
Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the Python Pocket Primer (Mercury Learning).