July 2018
Intermediate to advanced
491 pages
9h 39m
Chinese
Content preview from 利用 Python 进行数据分析（原书第2版）
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准备工作
｜
11
相似的 R data.frame 对象进行命名的。与 Python 不同的是，数据框在 R 语言中是标
准库中的内容。因此，pandas 中的很多特征通常与 R 核心的实现或者 R 的附加库提供的
功能一致。
pandas 的名字的来源是
panel data
，这是计量经济学中针对多维结构化数据集的术语。
pandas 也是
Python data analysis
（Python 数据分析）自身的简写短语。
1.3.3 matplotlib
matplotlib（
http://matplotlib.org
）是最流行的用于制图及其他二维数据可视化的 Python
库。它由 John D. Hunter 创建，目前由一个大型开发者团队维护。matplotlib 被设计为适
合出版的制图工具。对于 Python 编程者来说也有其他可视化库，但 matplotlib 依然使用
最为广泛，并且与生态系统的其他库良好整合。我认为将它作为默认可视化工具是一个
安全的选择。
1.3.4 IPython 与 Jupyter
IPython 项目（
http://ipython.org
）开始于 2001 年，由 Fernando Pérez 发起，旨在开发一
个更具交互性的 Python 解释器。在过去的 16 年中，它成为 Python 数据技术栈中最重要
的工具之一。尽管它本身并不提供任何计算或数据分析工具，它的设计侧重于在交互计
算和软件开发两方面将生产力最大化。它使用了一种
执行
-
探索
工作流来替代其他语言
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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.