grouped2=grouped.orderBy(desc(grouped.columns[0])).limit(3)代码解释

时间: 2024-05-24 19:14:17 浏览: 75

SAS.9.2.SQL.Procedure.Users.Guide

Chapter 1 Introduction to the SQL Procedure Chapter 2 Retrieving Data from a Single Table Chapter 3 Retrieving Data from Multiple Tables Chapter 4 Creating and Updating Tables and Views Chapter 5 Programming with the SQL Procedure Chapter 6 Practical Problem-Solving with PROC SQL ### SAS 9.2 SQL Procedure User’s Guide #### Chapter 1: Introduction to the SQL Procedure **What Is SQL?** Structured Query Language (SQL) is a standard language used for managing and manipulating relational databases. It allows users to perform various operations such as querying, inserting, updating, and deleting data. **What Is the SQL Procedure?** The SQL procedure in SAS (Statistical Analysis System) is a powerful tool that enables users to execute SQL statements within the SAS environment. This procedure provides an interface between SAS and SQL, allowing users to leverage the capabilities of both systems for data manipulation and analysis. **Terminology** The SQL procedure uses specific terminology that is important for understanding how it operates: - **Table**: A collection of related data stored in a structured format within a database. - **View**: A virtual table based on the result of a SELECT statement. It does not physically exist until it is referenced. - **Join**: Combines rows from two or more tables based on a related column between them. - **Aggregate Function**: Functions used to calculate summary statistics, such as SUM, AVG, COUNT, etc. **Comparing PROC SQL with the SAS DATA Step** PROC SQL and the SAS DATA step are two different methods for processing data in SAS, each with its own strengths and use cases: - **PROC SQL**: - **Strengths**: - Easier syntax for complex queries. - Direct support for common database operations like joins and aggregations. - Ability to interact with external databases directly. - **Use Cases**: - When working with large datasets or when complex data manipulations are required. - For ad-hoc reporting and data analysis. - **SAS DATA Step**: - **Strengths**: - Greater control over the data processing flow. - Flexibility in handling loops and conditional statements. - **Use Cases**: - When detailed record-level processing is necessary. - For complex programming logic. **Notes about the Example Tables** The example tables used throughout the guide are designed to demonstrate various aspects of using PROC SQL. These tables often include a mix of numeric and character fields and represent real-world scenarios to help users understand how to apply the concepts learned. #### Chapter 2: Retrieving Data from a Single Table **Overview of the SELECT Statement** The SELECT statement is the core of any SQL query and is used to retrieve data from one or more tables. The basic structure of a SELECT statement includes specifying the columns to be retrieved and the table from which to retrieve them. **Selecting Columns in a Table** To select specific columns from a table, you can list the column names after the SELECT keyword. For example: ```sql SELECT column1, column2 FROM table_name; ``` **Creating New Columns** You can create new columns on the fly by using expressions or functions in the SELECT statement. For example: ```sql SELECT column1, column1 * 10 AS new_column FROM table_name; ``` **Sorting Data** Sorting data is achieved using the ORDER BY clause. You can sort in ascending (ASC) or descending (DESC) order. For example: ```sql SELECT * FROM table_name ORDER BY column1 DESC; ``` **Retrieving Rows That Satisfy a Condition** You can filter rows based on conditions using the WHERE clause. For example: ```sql SELECT * FROM table_name WHERE column1 > 100; ``` **Summarizing Data** Aggregation functions are used to summarize data. Common functions include SUM, AVG, MAX, MIN, and COUNT. For example: ```sql SELECT SUM(column1), AVG(column2) FROM table_name; ``` **Grouping Data** Grouping data is done using the GROUP BY clause, which allows you to perform calculations on grouped data. For example: ```sql SELECT column1, COUNT(*) FROM table_name GROUP BY column1; ``` **Filtering Grouped Data** After grouping data, you can further filter the results using the HAVING clause, which filters the results of a GROUP BY operation. For example: ```sql SELECT column1, COUNT(*) FROM table_name GROUP BY column1 HAVING COUNT(*) > 5; ``` **Validating a Query** It is essential to validate the correctness of your query by comparing the results against expected outcomes or by performing additional checks. This ensures that the data being processed is accurate and reliable. In conclusion, the SAS 9.2 SQL Procedure User's Guide covers a comprehensive range of topics related to using PROC SQL effectively. From retrieving data from single tables to creating and updating tables and views, this guide is a valuable resource for SAS users looking to leverage SQL within the SAS environment.

这段代码使用Spark SQL对一个DataFrame进行分组、排序和限制操作。具体地说，首先对DataFrame进行groupby操作，然后根据分组后的列进行降序排序，并最终返回前三行。其中，"grouped"是分组后的结果DataFrame，"[0]"代表分组列的索引，"desc"表示降序排序，"limit"表示限制输出行数。

阅读全文

grouped2=grouped.orderBy(desc(grouped.columns[0])).limit(3)代码解释

相关推荐

【Python数学库终极指南】：解锁代码优化与数据分析的7大高级技巧

（2）新加一列命名为“时长”，计算订单时间距离2021年3月1日）已经过去多少天。 （3）用pivot_table制作透视表，以客户名称为分组，统计不同客户产品销量总和以及平均时长。python

spring 异步编程样例

带有 python 3 和 opencv 4.1 的 Docker 映像.zip

原生js鼠标滑过文字淡入淡出效果.zip

1-中国各省、市、区、县距离港口和海岸线的距离计算代码+计算结果-社科数据.zip

为 Spring Web 应用提供 OAuth1 (a) 和 OAuth2 功能支持.zip

信号处理和通信系统模型中的模拟电路效应simulink.rar

Python错误集合.doc

1-中国全球投资追踪相关数据（2005-2023年）-社科数据.zip

原生js广告代码制作可展开关闭的页面上固定的图片对联广告代码.rar

1-中国各地区普通小学毕业生数（1999-2020年）-社科数据.zip

用于模拟三角模糊隶属度的 Simulink 函数.rar

生产单元数字化改造24国赛仓库

成熟草莓检测 草莓照片 - 物体检测数据集

雷达信号分选仿真数据产生程序以及信号分选的PRI变换算法仿真程序 matlab代码.rar

最新推荐

spring 异步编程样例

火炬连体网络在MNIST的2D嵌入实现示例

管理建模和仿真的文件

L2正则化的终极指南：从入门到精通，揭秘机器学习中的性能优化技巧

如何构建一个符合GB/T19716和ISO/IEC13335标准的信息安全事件管理框架，并确保业务连续性规划的有效性？

Angular插件增强Application Insights JavaScript SDK功能

"互动学习：行动中的多样性与论文攻读经历"

L1正则化模型诊断指南：如何检查模型假设与识别异常值（诊断流程+案例研究）

如何构建一个符合GB/T19716和ISO/IEC13335标准的信息安全事件管理框架，并确保业务连续性规划的有效性？

实时三维重建：InfiniTAM的ros驱动应用

（2）新加一列命名为“时长”，计算订单时间距离2021年3月1日）已经过去多少天。（3）用pivot_table制作透视表，以客户名称为分组，统计不同客户产品销量总和以及平均时长。python

成熟草莓检测草莓照片 - 物体检测数据集