作者：JakeVanderPlas
页数：563
出版社：东南大学出版社
出版日期：2023
ISBN：9787576606584
电子书格式：pdf/epub/txt
内容简介
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科学计算的推荐参考。
作者简介
杰克·万托布拉斯，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。
目录
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
NumPy Array Attributes
Array Indexing: Accessing Single Elements
Array Slicing: Accessing Subarrays
One-Dimensional Subarrays
Multidimensional Subarrays
Subarrays as No-Copy Views
Creating Copies of Arrays
Reshaping of Arrays
Array Concatenation and Splitting
Concatenation of Arrays
Splitting of Arrays
……
Part III. Data Manipulation with Pandas
Part IV. Visualization with Matplotlib
Part V. Machine Learning
Index
