Python Programming for Data Analysis

版本说明：1

作     者：José Unpingco 

I S B N：(纸本) 9783030689513;9783030689544 

出 版 社：Springer Cham 

出 版 年：2021年

页      数：XII, 263页

主 题 词：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 

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

摘      要：This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of California, San Diego, which is a requirement for both graduate and undergraduate degrees in Machine Learning and Data Science. This book is ideal for readers with some Python programming experience. The book covers key language concepts that must be understood to program effectively, especially for data analysis applications. Certain low-level language features are discussed in detail, especially Python memory management and data structures. Using Python effectively means taking advantage of its vast ecosystem. The book discusses Python package management and how to use third-party modules as well as how to structure your own Python modules. The section on object-oriented programming explains features of the language that facilitate common programming patterns.;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.