Excel Data Analysis from Beginner to Mastery

Name: Excel Data Analysis from Beginner to Mastery
ISBN: 9787301364123

梁三十Peking University Press · ChinaMay 2026

3.0

Word count: 226K words
Chapters: 116
ISBN: 9787301364123

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Summary

The book has 24 chapters in 6 parts. Part 1 covers Excel basics. Part 2 covers data handling methods and techniques, including data normalization, filtering, sorting, and summarizing. Part 3 covers formulas and functions commonly used in data processing and analysis, including logical, statistical, lookup, text, and date functions. Part 4 covers common methods and techniques for pivot tables and pivot charts, including pivot table calculation, sorting, filtering, and grouped statistics, as well as slicers. Part 5 covers data visualization methods, including chart creation, editing, and formatting, and the use of combo charts. Part 6 ties together the methods and techniques presented in the book through three integrated cases—HR data analysis, inventory reports, and financial expense analysis—so readers can practice and apply what they have learned by analogy.

Editor's review

This is a clearly structured, hands-on tutorial on Excel data analysis, organized into six parts—basic operations, data handling, formulas and functions, pivot tables and pivot charts, data visualization, and integrated cases—across twenty-four chapters. Its value lies in organizing scattered Excel skills into a complete chain from data-entry standards to analysis and presentation, especially with Part 6 closing on three cases (HR data analysis, inventory reports, and financial expense analysis) that let readers connect what they have learned in concrete business scenarios. The book covers filtering and sorting, commonly used functions, slicers, and combo charts, making it suitable as a self-study handbook for improving office skills or as in-house training material. Readers are advised to open Excel and work along rather than reading straight through; they can jump to the chapters relevant to their work and then use the integrated cases to test their mastery. For those with scattered operational experience but no systematic method, this book helps organize the analysis workflow; complete beginners should set aside more time for hands-on practice.

Who it's for

A good fit for

New workplace professionals who need to systematically master Excel data processing and report creation
Administrative, HR, finance, and similar roles seeking to improve daily data analysis efficiency
In-house training or vocational courses looking for a structured Excel textbook
Those with scattered operational experience who want to fill gaps in functions and pivot tables

Not a good fit for

Readers seeking programming-based data analysis with Python, SQL, etc.
Analysts needing advanced statistical modeling or machine learning content
Readers who do not use spreadsheet software at all or have no conditions for hands-on practice

Reading tips

Open Excel and work along; after each chapter, immediately practice with the included data or your own work data.
Prioritize the chapters most relevant to your current work, then go back to fill in basics; do not feel obliged to read straight through in order.
After finishing the pivot table and chart chapters, run through the integrated cases in Part 6 as a complete workflow exercise.
Build your own quick-reference notes for functions, grouping common logical, statistical, and lookup functions by scenario.

About the publisher

Peking University Press China · Founded in 1979

Peking University Press is a comprehensive university press whose publishing areas cover classical literature, popular science, social culture, world history, Western philosophy, and culture. Its catalogue contains 6,031 titles, with representative books including A Dream of Red Mansions, Relativity: The Special and General Theory (15th Edition) (with Einstein's classic papers on unified field theory and other topics), Elements, Conics, The Aristocratic Families of the Eastern Jin, The Philosophy of Mythology (Volume I), The Philosophy of Mythology (Volume II), and The Origin of Continents and Oceans. Representative authors include Cao Xueqin, Zhou Ruchang, Albert Einstein, Euclid, Apollonius, Tian Yuqing, Schelling, and Xian Gang. The press has developed distinctive strengths in classical Chinese literature and in the translation of Western philosophical classics, while also covering scientific classics and social and cultural studies. As public information is limited, this description is based only on the books in the catalogue and offers no further extrapolation.

版权信息
内容提要
前言
第1篇 Excel入门
第1章绪论
1.1 在日常工作中，Excel能解决哪些问题
1.2 Excel数据分析的思维与方法
1.3 通过本书的学习，可以提升哪些能力
第2章 Excel数据处理与分析的必备基础操作
2.1 Excel的工作界面
2.2 Excel的工作簿和工作表操作
2.3 表格打印
2.4 保护表格
第2篇数据处理
第3章数据规范
3.1 6种常见的表格问题
3.2 表格布局的4个原则
3.3 单元格格式规范
3.4 数据验证
第4章数据筛选、排序与汇总
4.1 数据筛选
4.2 数据排序
4.3 数据分类汇总
第5章数据处理综合实例——制作某火锅店6月份销售业绩表
5.1 案例背景
5.2 案例分析
5.3 实现过程
第3篇公式与函数
第6章公式与函数应用常识
6.1 认识公式与函数
6.2 单元格的引用
6.3 6类常见的函数错误
6.4 嵌套函数的排错方法
第7章逻辑函数
7.1 认识逻辑函数
7.2 IF函数详解
7.3 多个条件的逻辑判断
7.4 多层条件判断
第8章统计函数
8.1 认识统计函数
8.2 基础统计函数
8.3 条件统计函数
8.4 多条件统计函数
第9章查询函数
9.1 认识VLOOKUP函数
9.2 关键词查询
9.3 文本模糊查询
9.4 区间查询
9.5 一对多查询
第10章文本函数
10.1 提取类文本函数
10.2 定位辅助类文本函数
10.3 TEXT函数
第11章日期函数
11.1 基础日期函数
11.2 日期计算函数
11.3 条件格式和函数组合
第12章公式与函数综合实例——制作2022年10月工资表
12.1 案例背景
12.2 案例解析
12.3 实现过程
第4篇数据透视表与数据透视图
第13章数据透视表基础知识
13.1 初识数据透视表
13.2 数据透视表的字段列表功能
13.3 数据透视表的分类汇总功能
13.4 数据透视表布局
13.5 美化数据透视表
13.6 更新数据透视表的数据源
第14章数据透视表的计算
14.1 值的汇总方式
14.2 值的显示方式
14.3 计算字段汇总数据
第15章数据透视表的排序、筛选与分组统计
15.1 数据透视表的排序
15.2 数据透视表的筛选
15.3 数据透视表的分组统计
第16章数据透视图和切片器
16.1 数据透视图
16.2 切片器
16.3 美化数据看板
第17章数据透视表综合实例——制作2023年抱枕销售明细表
17.1 案例背景
17.2 实现思路
17.3 实现过程
第5篇数据可视化
第18章数据条件格式与迷你图应用
18.1 数据可视化的含义
18.2 突出显示单元格
18.3 数据图形化表达方式
第19章图表的创建、编辑与美化
19.1 常见的图表类型
19.2 图表的创建与编辑
19.3 图表的美化
第20章复合图表的应用
20.1 初识复合图表
20.2 柱形图-折线图复合图表
20.3 柱形图-柱形图
20.4 折线图-折线图
第21章图表应用综合实例——制作销售业绩的动态图表
21.1 案例背景
21.2 实现思路
21.3 实现过程
第6篇 Excel数据分析综合案例
第22章制作公司人力数据分析看板
22.1 案例目标
22.2 实现思路
22.3 实现过程
第23章制作进销存报表
23.1 案例目标
23.2 实现思路
23.3 实现过程
第24章制作财务费用分析看板
24.1 案例目标
24.2 实现思路
24.3 实现过程

FAQ

Can complete beginners read this book directly?

Yes, but hands-on practice is required. Part 1 introduces basic Excel operations; beginners should start there and set aside time to become familiar with the interface and basic data entry. If you have never used spreadsheet software at all, it is advisable to complete a few simple spreadsheet tasks before moving on to the data handling part, so that later study of functions and pivot tables is not too difficult.

Do I need to download the case data separately?

The materials do not state how to obtain the companion files; please refer to the book's copyright page, preface, or the publisher's official channels. If case data downloads are provided with the book, it is recommended to use them chapter by chapter; if you need to prepare data yourself, you can construct practice tables with the same structure based on the case descriptions without affecting your learning of the methods.

Which version of Excel is this suitable for?

The materials do not specify a particular version. The basic operations, commonly used functions, pivot tables, and chart features introduced in the book are generally available in newer versions of Excel, but some menu names or feature locations may vary by version. Readers can look up the corresponding commands in their own version; the core analysis methods are unaffected.

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About the author

梁三十 Author

Liang Sanshi is a book author about whom little public information is available; the library currently holds only one work by this author, Excel Data Analysis from Beginner to Mastery. Judging from the title and the common category of software learning, the book is aimed at learners who wish to use Excel for data processing and analysis, and it belongs to the practical how-to genre. The author organizes the content around specific software functions and operating procedures, guiding readers step by step from the basics toward the fundamental methods of organizing, analyzing, and presenting data, in a clear and approachable instructional style. Because no reliable records of birth and death dates, nationality, or professional experience have been found, the author's personal background cannot be supplied, and readers may regard Liang Sanshi as a compiler focused on office software applications. In terms of the existing work, the writing serves the clear goal of introducing and improving software skills and is suitable for ordinary readers who need to study Excel data analysis systematically.