Overview
- Straightforward, applicable guidance on using Python programming for a variety of data science applications
- Provides aspiring data scientists with a detailed introduction to the Python language and key modules for all phases of the data science development process
- Based on a course at UC San Diego for giving students hands-on skills for data analysis applications using key Python modules for data processing, analysis, and visualization.
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Table of contents (6 chapters)
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Front Matter
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Back Matter
Keywords
About this book
After developing the key Python language features, the book moves on to third-party modules that are foundational for effective data analysis, starting with Numpy. The book develops key Numpy concepts and discusses internal Numpy array data structures and memory usage. Then, the author moves onto Pandas and details its many features for data processing and alignment. Because strong visualizations are important for communicating data analysis, key modules such as Matplotlib are developed in detail, along with web-based options such as Bokeh, Holoviews, Altair, and Plotly.
The text is sprinkled with many tricks-of-the-trade that help avoid common pitfalls. The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis.To get the most out of this book, open a Python interpreter and type along with the many code samples.
Authors and Affiliations
About the author
Dr. José Unpingco completed his PhD from the University of California, San Diego (UCSD) in 1997 and has since worked in industry as an engineer, consultant, and instructor on a wide variety of advanced data science topics, with deep experience in machine learning. He was the onsite technical director for large-scale Signal and Image Processing for the Department of Defense (DoD) where he also spearheaded the DoD-wide adoption of scientific Python. Dr. Unpingco is currently the Senior Director for Data Science for the Gary and Mary West Health Institute, a non-profit Medical Research Organization in San Diego, California. He is also a Data Science lecturer at UCSD for undergraduate and graduate degree programs and the author of Python for Signal Processing, and Python for Probability, Statistics, and Machine Learning.
Bibliographic Information
Book Title: Python Programming for Data Analysis
Authors: José Unpingco
DOI: https://doi.org/10.1007/978-3-030-68952-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-68951-3Published: 05 May 2021
Softcover ISBN: 978-3-030-68954-4Published: 06 May 2022
eBook ISBN: 978-3-030-68952-0Published: 04 May 2021
Edition Number: 1
Number of Pages: XII, 263
Number of Illustrations: 11 b/w illustrations, 123 illustrations in colour
Topics: Communications Engineering, Networks, Probability and Statistics in Computer Science, Big Data/Analytics, Signal, Image and Speech Processing, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Data Mining and Knowledge Discovery