Python for Data Science (No Starch Press)
Monday, 15 August 2022

This book provides  a hands-on introduction to the Pythonic world of data analysis with a learn-by-doing approach rooted in practical examples and activities. Yuli Vasiliev shows how to write Python code to obtain, transform, and analyze data, practicing state-of-the-art data processing techniques and looks at Python’s rich set of built-in data structures for basic operations, as well as its robust ecosystem of open-source libraries for data science, including NumPy, pandas, scikit-learn and matplotlib.

<ASIN:1718502206>

Examples show how to load data in various formats, how to streamline, group, and aggregate data sets, and how to create charts, maps, and other visualizations.

Author: Yuli Vasiliev
Publisher: No Starch
Date: August 2022
Pages: 240
ISBN: 978-1718502208
Print: 1718502206
Kindle: B09BKLV68X
Audience: Python developers interested in data analysis
Level: Intermediate
Category: Python

 

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HTML, CSS & JavaScript (In Easy Steps)

Author: Mike McGrath
Publisher: In Easy Steps
Date: July 2020
Pages: 480
ISBN: 978-1840788785
Print: 184078878X
Kindle: B08FBGXGF1
Audience: would-be web developers
Rating: 5
Reviewer Mike James
The three core web technologies in a single book.



Foundational Python For Data Science

Author: Kennedy Behrman
Publisher: Pearson
Pages:256
ISBN: 978-0136624356
Print: 0136624359
Kindle: B095Y6G2QV
Audience: Data scientists
Rating: 4.5
Reviewer: Kay Ewbank

This book sets out to be a simple introduction to Python, specifically how to use it to work with data.


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