May 2026
Intermediate
418 pages
5h 50m
Chinese
Content preview from Python for Excel (Chinese Edition), 2nd Edition
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第 1 章. 为什么 要在 Excel 中使用 Python？
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许多 Excel 用户在遇到功能限制时，会开始重新考虑自己的电子表格工具。一个典型的例子是，当 Excel 工作簿包含大量数据和公式时，运行速度会变慢，甚至在最坏的情况下导致崩溃。千万不要让情况发展到这一步！如果您处理的是关键任务型工作簿（其中任何错误都可能导致财务损失或声誉受损），或者您需要花费数小时手动更新 Excel 工作簿，那么您应该将一种编程语言加入到您的工具箱中。 编程语言能帮你自动化易出错的复制粘贴流程，并将难以理解的 Excel 公式转化为易于维护的函数。它还能将电子表格与数据库等外部系统连接，从而精简工作簿并恢复其运行速度。本书选用 Python 作为 Excel 的编程语言，让我们先快速了解一下这两位“主角”的起源！
考虑到技术发展的迅猛速度，Excel和Python都已存在了相当长的时间：Excel由微软于1985年首次推出——这可能令人惊讶——当时仅支持Apple Macintosh系统。Windows用户不得不等到1987年Excel 2.0发布后才得以使用。 不过，微软并非电子表格市场的先行者：VisiCorp 早在 1979 年就推出了 VisiCalc（），随后 Lotus Software 于 1983 年推出了 Lotus 1-2-3（）。甚至微软当时还有另一款相关应用：在 Excel 问世的三年前，他们曾发布过一款面向 MS-DOS 的电子表格程序 Multiplan（ ）。
Python诞生于1991年，距Excel问世仅六年。虽然Excel早期便广受欢迎，但Python在作为脚本语言及Web开发工具获得认可之前，经历了一段更漫长的历程。2005年，随着用于数组计算和线性代数的包NumPy发布，Python开始成为科学计算领域 的有力替代方案。NumPy整合了两个前身包，从而将围绕科学计算的所有开发工作 集中到一个项目中。 如今，它构成了无数科学包的基础，包括 2008年问世的pandas，该包在很大程度上促成了Python在金融和数据科学领域的广泛应用。如今，得益于日益壮大的科学生态系统，Python已成为机器学习（ML）和人工智能（AI）领域最常用的语言之一。
在本章中，我将指出 Python 相较于 Excel 的传统编程语言 VBA（Visual Basic for Applications）所具备的优势。我将重点探讨 Python 的核心原则、科学计算能力及其现代语言特性。最后，我将介绍作为 Python 开发者可使用的几款工具。
Python 核心原则
与所有编程语言一样，Python也有一些核心原则，正是这些原则塑造了它今天的模样：
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通用语言：Python 适用于多种不同的用途。
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可读性很重要：Python 的语法易于阅读。
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功能齐全：Python 附带了一个全面的标准库。
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跨平台：Python 可在所有主流平台上运行。
让我们逐一探讨这些原则，并将其与 VBA 进行对比。
通用编程语言
Python（）是一种通用编程语言，这意味着它并非专为 Web 开发或数据分析等特定领域设计：Python 可用于多种不同用途，包括 Excel 自动化、机器学习以及大型 Web 应用程序。这也意味着，您可以将基于 Python 的 Excel 工具转变为功能齐全的 Web 应用程序，而无需重写包含业务逻辑的代码。 ...
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