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Hands-On SAS for Data Analysis

You're reading from   Hands-On SAS for Data Analysis A practical guide to performing effective queries, data visualization, and reporting techniques

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Product type Paperback
Published in Sep 2019
Publisher Packt
ISBN-13 9781788839822
Length 346 pages
Edition 1st Edition
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Author (1):
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Harish Gulati Harish Gulati
Author Profile Icon Harish Gulati
Harish Gulati
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: SAS Basics
2. Introduction to SAS Programming FREE CHAPTER 3. Data Manipulation and Transformation 4. Section 2: Merging, Optimizing, and Descriptive Statistics
5. Combining, Indexing, Encryption, and Compression Techniques Simplified 6. Power of Statistics, Reporting, Transforming Procedures, and Functions 7. Section 3: Advanced Programming
8. Advanced Programming Techniques - SAS Macros 9. Powerful Functions, Options, and Automatic Variables Simplified 10. Section 4: SQL in SAS
11. Advanced Programming Techniques Using PROC SQL 12. Deep Dive into PROC SQL 13. Section 5: Data Visualization and Reporting
14. Data Visualization 15. Reporting and Output Delivery System 16. Other Books You May Enjoy

Altering the CALL SYMPUT example

In the previous chapter, while introducing CALL SYMPUT, we looked at an example where the objective was to output records from 2019 and 2013 of the youngest people in each year with the maximum height. We had to store the ClassIDs of the people we were looking at and then pass this information on to a Proc Print statement to get the desired output. By using Call Execute, we can shorten the process to get the output in at least two steps:

Proc Sort Data = Class Out = Sorted;
By Descending Year Age Descending Height;
Run;

Data First;
Set Sorted;
By Descending Year Age Descending Height;
If First.Year and First.Height Then Output First;
Call Execute ('Proc Print Data = _LAST_; Where Year = 2019; Run;');
Call Execute ('Proc Print Data = _LAST_; Where Year = 2013; Run;');
Run;

The output will be the same as it was in previous chapter.

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