November 2023
Intermediate to advanced
512 pages
11h 53m
Chinese
Content preview from 利用 Python 进行数据分析：原书第 3 版
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441
附录 A
高阶 NumPy
在附录
A
中，我会深入讲解
NumPy
库的数组计算，包括关于
ndarray
类型以及更高级的
数组操作和算法的更多内部细节。
该部分包括多个主题，读者不必按顺序阅读。在附录
A
中，我使用 numpy.random 模块
中默认的随机数生成器为许多示例生成了随机数据，如下所示：
A.1 ndarray
对象的内部机理
NumPy
的
ndarray
提供了一种将同构类型数据块（可以是连续的或步进的）解释为多维
数组对象的方式。数据类型（
dtype
）决定了数据的解释方式，比如浮点数、整数、布尔
值等类型。
ndarray
如此强大，部分原因是所有数组对象都是数据块的步进视图。例如，你可能想知
道数组视图 arr[::2,::-1] 不复制任何数据的原因是什么。简单地说，
ndarray
不只是
一块内存和一个
dtype
，它还有步进信息，这使得数组能以各种步幅在内存中移动。更
准确地讲，
ndarray
内部由以下内容组成：
·
指向数据的指针，数据指内存或内存映射文件中的一块数据。
·
数据类型（dtype），用于描述数组中固定大小的值单元格。
·
表示数组形状的元组。
·
步进元组，其中的整数是指为了前进到当前维度的下一个元素，需要“步进”的字
节数。
图
A-1
简单模拟了
ndarray
的内部结构。
442
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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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.