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书名 | Python数据科学手册(影印版)(英文版) |
分类 | |
作者 | (美)杰克·万托布拉斯 |
出版社 | 东南大学出版社 |
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简介 | 内容推荐 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。 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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