Python数据科学手册 第2版(影印版)

Python是众多研究人员眼中的一流工具，主要 原因在于它所提供的可用于存储、操作、洞察数据 的各种库。数据科学堆栈的各个部分都存在多种资 源，但只有本书的新版将它们汇集于一处，包括 IPython、NumPy、pandas、Matplotlib、 Scikit-Learn以及其他相关工具。 熟悉阅读和编写Python代码的在职科技人员和 数据处理人员会发现这份全面的案头参考书的第二 版非常适合处理各种日常问题：数据的操作、转换 、清理；不同类型数据的可视化；使用数据建立统 计或机器学习模型。一句话，这是Python科学计算 的必备参考。

Jake VanderPlas是Python科学栈的深度用户和开发人员，目前是华盛顿大学eScience学院物理科学研究院院长，研究方向为天文学。同时，他还为很多领域的科学家提供建议和咨询。

Preface Part I. Jupyter: Beyond Normal Python 1. Getting Started in IPython and Jupyter Launching the IPython Shell Launching the Jupyter Notebook Help and Documentation in IPython Accessing Documentation with ? Accessing Source Code with ?? Exploring Modules with Tab Completion Keyboard Shortcuts in the IPython Shell Navigation Shortcuts Text Entry Shortcuts Command History Shortcuts Miscellaneous Shortcuts 2. Enhanced Interactive Features IPython Magic Commands Running External Code: %run Timing Code Execution: %timeit Help on Magic Functions: ?, %magic, and %lsmagic Input and Output History IPython's In and Out Objects Underscore Shortcuts and Previous Outputs Suppressing Output Related Magic Commands IPython and Shell Commands Quick Introduction to the Shell Shell Commands in IPython Passing Values to and from the Shell Shell-Related Magic Commands 3. Debugging and Profiling Errors and Debugging Controlling Exceptions: %xmode Debugging: When Reading Tracebacks Is Not Enough Profiling and Timing Code Timing Code Snippets: %timeit and %time Profiling Full Scripts: %prun Line-by-Line Profiling with %lprun Profiling Memory Use: %memit and %mprun More IPython Resources Web Resources Books Part II. Introduction to NumPy 4. Understanding Data Types in Python A Python Integer Is More Than Just an Integer A Python List Is More Than Just a List Fixed-Type Arrays in Python Creating Arrays from Python Lists Creating Arrays from Scratch NumPy Standard Data Types 5. The Basics of NumPy Arrays