掌握最新LINQ思维与实践：功能编程到数据探索

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"《Thinking in LINQ 最新版》是一本专注于指导读者如何有效地运用LINQ的书籍，而非基础教程。作者和编者对本书的介绍强调了其核心在于提升读者在实际编程中的应用技巧，而不是单纯教授语法。书中内容涵盖了多个实用章节，包括： 1. **Chapter 1: Thinking Functionally** - 从函数式编程的角度引导读者理解LINQ，让读者掌握如何利用LINQ处理问题的抽象和逻辑。 2. **Chapter 2: Series Generation** - 学习如何通过LINQ创建和操作序列，这是理解和使用LINQ的关键，因为LINQ的核心就是对数据集的操作。 3. **Chapter 3: Text Processing** - 介绍了如何利用LINQ进行文本处理，如搜索、替换和分析文本数据。 4. **Chapter 4: Refactoring with LINQ** - 针对代码重构，展示如何通过LINQ优化现有的代码结构，提高代码质量和可读性。 5. **Chapter 5: Refactoring with MoreLINQ** - 进一步探讨了MoreLINQ扩展库的使用，提供更多高级操作的可能性。 6. **Chapter 6: Creating Domain-Specific Languages (DSL)** - 如何设计和实现领域特定的语言，利用LINQ来简化特定领域的任务处理。 7. **Chapter 7: Static Code Analysis** - 涉及静态代码分析，帮助读者通过LINQ进行代码质量检查和错误检测。 8. **Chapter 8: Exploratory Data Analysis** - 教授如何使用LINQ进行数据分析，特别是当数据量大或需要高效探索时。 9. **Chapter 9: Interacting with the File System** - 显示如何与文件系统集成，处理文件操作，利用LINQ简化文件读写和目录操作。 10. **Appendix A: Lean LINQ Tips** - 提供实用的LINQ技巧和最佳实践，帮助读者更好地利用LINQ的潜能。 11. **Appendix B: Taming Streaming Data with Rx.NET** - 探索如何使用Rx.NET（Reactive Extensions）与LINQ结合处理流数据，扩展了LINQ在实时数据处理中的应用。整本书的目的是让读者了解并掌握如何在合适的时候、用合适的方式使用LINQ，避免过度使用或不当使用工具导致效率下降。书中实例丰富，适合有基础的开发者深入学习和提升LINQ技能。"

Chapter 2 ■ SerieS Generation

How It Works

This example uses a lookup table to find out the percentile. The keys in the lookup table hold the number, and the

values are all those numbers that are smaller than that number. Later the code finds the percent of these values

against the total number of items. That yields the percentile for the particular number represented by the key.

2-5. Math and Statistics: Finding the Dominator in an Array

A dominator is an element in an array that repeats in more than 50 percent of the array positions.

Problem

Assume you have the following array: {3, 4, 3, 2, 3, -1, 3, 3}. There are eight elements, and 3 appears in five of those.

So in this case the dominator is 3. The problem is to use LINQ to find the dominator in an array.

Solution

The first algorithm that comes to mind to find a dominator has to loop through the array twice and thus has quadratic

time complexity, but you can improve the efficiency by using a lookup. Listing 2-6 shows the solution.

Listing 2-6. Finding the array dominator

int[] array = { 3, 4, 3, 2, 3, -1, 3, 3};

array.ToLookup (a => a).First (a => a.Count() >

array.Length/2).Key.Dump("Dominator");

Figure 2-7. Student rank derived from percentile

Chapter 2 ■ SerieS Generation

When you run this query in LINQPad, you will see the output shown in Figure 2-9. The Key column shows

the face value of various bills, while the Value column shows the number of those bills required to add up to the

target value.

How It Works

The algorithm to find the minimum number of currency bills required is recursive. It is a continuous division of the

value by the largest currency value that results in an integer greater than or equal to 1, repeated against the remainder

until the value of the amount diminishes to zero.

amount/c (amount divided by c) calculates the number of currency bills required with value c. The remaining

amount is the remainder, as calculated by amount % c.

The data is stored as a currency and currency count pair in the C# dictionary map. Each dictionary key is a

currency bill face value, and the value is the number of such currency bills required to total the given amount, using

the minimum number of currency bills. Thus, any nonzero value in the map is what you should look for. The LINQ

query map.Where (m => m.Value!=0) does just that. And that’s about it!

LINQPad has a cool feature that sums up the values in the Value column. In this case, that summation is 8.

That means it will require a minimum of eight currency bills to make 2,548.

The first call to OrderByDescending() makes sure that you start with the highest available currency value.

2-7. Math and Statistics: Finding Moving Averages

Finding a moving average is a problem that often arises in time series analysis, where it’s used to smooth out local

fluctuations. A moving average is just what it says—an average that “moves.” In other words, it is the average of all

elements that fall within a moving window of a predefined size. For example, suppose you have the numbers 1, 2, 3, 4,

and the window size is 2. In that case, there are three moving averages: the average of 1 and 2, the average of 2 and 3,

and the average of 3 and 4.

Problem

Create a program that finds the moving average of given window size.

Figure 2-9. Output of the minimum currency bill count query

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