March 2022
Intermediate to advanced
522 pages
13h 52m
Chinese
Content preview from Python语言及其应用（第2版）
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187
第 12章
数据处理
只要你把数据折磨得够狠，大自然都会招供。
——
Ronald Coase
迄今为止，本书主要讨论的是
Python
语言本身
，即它的数据类型、代码结构、语法，等
等。本书余下部分主要关注
Python
如何应用于现实问题。
本章将介绍很多数据处理的实践技术。有时候，数据处理也被称作
数据整理
（
data
munging
）
，或者是数据库世界中更商业化的
ETL
（
extract/transform/load
，提取
/
转换
/
加
载）。尽管编程类图书通常并不会专门介绍该主题，但程序员往往要花大量时间将数据整
理成符合要求的形式。
数据科学
专业在过去几年中已经变得颇为流行。《哈佛商业评论》（
Harvard Business
Review
）的一篇文章称数据科学家是“
21
世纪最性感的工作”
。如果这意味着需求旺盛、
报酬丰厚，那还算好，但苦差事同样也少不了。数据库的
ETL
无法满足
数据科学的需求，
其中往往要用到
机器学习
来挖掘出人眼无法看到的深刻见解。
本章会从基本的数据格式开始，一路讲解到对数据科学最有用的新工具。
数据格式粗略地分为两类：
文本
和
二进制
。
Python
字符串
用于文本数据，本章包括了前面
略过的字符串相关内容：
• Unicode
字符；
•
正则表达式模式匹配。
然后，本章会介绍二进制数据以及另外两种
Python
内建数据类型：
•
bytes
类型，用于不可变的
8
位值；
•
bytearray
类型，用于可变的
8
位值。
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and much more.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.