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PYTHON数据科学手册(影印版 英文版)

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编程书籍推荐:PYTHON数据科学手册(影印版 英文版),由东南大学出版社2018-07-01月出版,本书发行作者信息: [美] Jake,VanderPlas 著此次为第1次发行, 国际标准书号为:9787564177324,品牌为南京东南大学出版社, 这本书采用平装开本为16开,附件信息:未知,纸张采为胶版纸,全书共有529页字数67万 1000字,值得推荐的Python Book。

此书内容摘要

对于很多研究者而言,Python成为一流工具的主要原因是它具有存储、处理数据并从中获取有价值信息的程序库。关于这堆数据科学知识已经有很多分散的独立篇章,但只有杰克·万托布拉斯著的《PYTHON数据科学手册(影印版 英文版)》可以把它们一网打尽——IPython、NumPy、Pandas、Matplotlib、Scikit-Learn,以及其它相关工具。熟悉读写Python代码的数据科学家和爱好者们,会发现这本全面的参考非常有助于处理每天工作:处理、转化和清洗数据,可视化不同类型的数据,以及利用数据构建统计或机器学习模型等。简言之,这是Python科学计算必备参考书。

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PYTHON数据科学手册(影印版 英文版)图书的目录

Preface
1. IPython: Beyond Normal Python
Shell or Notebook?
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
IPython Magic Commands
Pasting Code Blocks: %paste and %cpaste
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
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

2. Introduction to NumPy
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
The Basics of NumPy Arrays
NumPy Array Attributes
Array Indexing: Accessing Single Elements
Array Slicing: Accessing Subarrays
Reshaping of Arrays
Array Concatenation and Splitting
Computation on NumPy Arrays: Universal Functions
The Slowness of Loops
Introducing UFuncs
Exploring NumPy's UFuncs
Advanced Ufunc Features
Ufuncs: Learning More
Aggregations: Min, Max, and Everything in Between
Summing the Values in an Array
Minimum and Maximum
Example: What Is the Average Height of US Presidents?
Computation on Arrays: Broadcasting
Introducing Broadcasting
Rules of Broadcasting
Broadcasting in Practice
……
3.Data Manipulation with Pandas
4.Visualization with Matplotlib
5.Machine Learning
Index

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