Mastering Python Design Patterns

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This tutorial teaches everything you need to get started with Python programming for the fast-growing field of data analysis. Daniel Chen tightly links each new concept with easy-to-apply, relevant ex

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Mastering Arabic Vocabulary provides a structured vocabulary course for undergraduate and advanced students of Arabic.Arranged thematically, and by root, the course presents the key vocabulary that a

Python是由Guido van Rossum于20世紀80年代末和90年代初，在荷蘭國家數學和計算機科學研究所設計出來的。它是一種面向對象的、用途非常廣泛的編程語言，具有非常清晰的語法特點，適用于多種操作系統。目前Python在國際上非常流行，正在得到越來越多的應用。 Python可以完成許多任務，功能非常強大，其利用Pandas處理大數據的過程，由于Pandas庫的使用能夠很好地展現

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Introduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science, social science, and engineering that wish to learn the principles of computer mode

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本书具体内容包括：Python概述、Python语言基础、程序流程控制、常用内置数据类型、系列数据类型、输入和输出、错误和异常处理、函数、类和对象、模块和客户端、算法与数据结构基础、图形用户界面、图形绘制、数值日期和时间处理、字符串和文本处理、文件、数据库访问等。

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ALERT: Before you purchase, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. Several versions of Pearson's MyLab & Mastering products exist for eac

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Computer Coding Python for Kids has all you need to master Python - one of the world's most popular computer programming languages.Python is easier than other professional coding languages yet no less

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Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-pr

Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main conce

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Scientific Python is a significant public domain alternative to expensive proprietary software packages. This book teaches from scratch everything the working scientist needs to know using copious, downloadable, useful and adaptable code snippets. Readers will discover how easy it is to implement and test non-trivial mathematical algorithms and will be guided through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the language's capabilities. The author also shows how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. In this new edition, several chapters have been re-written to reflect the IPython notebook style. With an extended index, an entirely new chapter discussing SymPy and a substantial increase in the number of code snippets, researchers and research students will be able to quickly acquire all the skills needed for using Python e