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Hands-On SAS for Data Analysis
Hands-On SAS for Data Analysis

Hands-On SAS for Data Analysis: A practical guide to performing effective queries, data visualization, and reporting techniques

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Hands-On SAS for Data Analysis

Introduction to SAS Programming

In this chapter, we will learn and master basic SAS programming techniques. For the uninitiated of you, this chapter should be a stepping stone to SAS programming. For experienced SAS programmers, this chapter will help you revise some behind the scenes functionalities and tricks of SAS. In either case, this chapter will lay the foundation for how good an advanced SAS programmer you can be. As we progress through this chapter, we will cover the following topics:

  • SAS dataset fundamentals
  • SAS programming language—basic syntax
  • SAS LOG
  • Dataset options
  • SAS operators
  • Formats
  • Subsetting datasets

SAS dataset fundamentals

The SAS dataset contains values that are organized as rows and columns that can be processed (read/written) by SAS. The dataset can be a data file (table) or view. Either way, a dataset is typically rectangular in format. The dataset has a descriptor portion and data portion. While in the following table, we can only see the column/variable names, the descriptor portion holds further information such as the number of rows (more commonly referred to as observations) in the dataset, date and time of creation, and the operating environment in which it was created. This section is called the data portion, which holds all the data values:

The maximum number of observations that can be counted for a SAS dataset is determined by the long integer data type size for the operating environment. In operating environments with a 32-bit long integer, the maximum number...

SAS programming language – basic syntax

We used code in the first program to create an output dataset. The dataset was created by what is known as data steps. Data steps are a collection of statements that can help create, modify, and control the output. SAS also leverages Structured Query Language (SQL). Let's review the basic syntax for data steps and SQL within SAS. We will continue to explore more advanced versions of code throughout this book.

Data step

The following code represents one of the simplest forms of a data step:

DATA WORK.Air;
SET SASHELP.Air;
RUN;

Using the SET statement in this data step, we have specified the dataset that we want to refer to. There are no conditional statements in the program...

SAS LOG

The SAS LOG section of your coding environment is where all the actions performed that have been by the user in the current session are stored. These include instances of program submission and also messages about any programs that you might have terminated while they were executing. Apart from these, the SAS LOG also contains system-generated messages. These are of two types. The first instance is where the SAS version and a few other details about your system are written to the LOG. The second is when responses to the user code are generated and written to the LOG. The response could state that the program has run successfully, failed, or has some syntax issues that have been ignored. The responses are categorized in NOTE, INFO, WARNING, and ERROR categories. Program submission messages can be easily identified in the LOG as they have a line number associated with them...

Dataset options

There are many built-in SAS options that apply to the dataset. The broad purpose of these options is to help us do the following:

  • Rename variables
  • Select variables for subsetting
  • Retain select variables
  • Specify the password for a dataset, compress it, and encrypt it

Throughout this book, we will be looking at various dataset options. We will begin by exploring the compress, encrypt, and index options.

Compression

Compression reduces the number of bytes that are required to store each observation. The advantage of compression is that it requires less storage, owing to the fact that fewer bytes are required and fewer I/O operations are necessary to read or write to the data during processing.

The biggest disadvantage...

SAS operators

An SAS operator is a symbol that represents a comparison, arithmetic calculation, or logical operation. We will look into the various operator in the following sections.

Arithmetic operators

For performing arithmetic operations, the following can be used in SAS:

Symbol

Definition

+

Addition

/

Division

**

Exponentiation

*

Multiplication

-

Subtraction

Comparison operators

Comparison operators set up a comparison, operation, or calculation with two variables, constants, or expressions. If the comparison is true, the result...

Formats

There are usually three scenarios when formats are used in SAS:

  • To format the data available to make it more readable
  • To assign a specific format to make the data more meaningful
  • To alter the data type to make calculations, derivations, and so on

Formatting to make the data readable

SAS stores all dates as single unique numbers in a numeric format. All dates are stored as the number of dates from January 1, 1960. If you think of a number line, all dates prior to January 1, 1960 are negative and all dates after that are positive. It’s cumbersome to decode the numeric dates. An easier alternative is to get SAS to display a date using a date format. Let's look at our cost of living dataset with the addition...

Subsetting datasets

In many instances, we will need to select only a proportion of the overall dataset. This selection or subsetting of the dataset can be done in three ways:

  • Use of the WHERE and IF statements
  • Using the SAS dataset OPTIONS
  • Using the DROP and KEEP statements

WHERE and IF statements

Let's only select the data where the records have been updated in 2019:

DATA Updated_2019;
SET Cost_Living;
WHERE Year(Updated) = 2019;
RUN;

The following output will be generated:

In this instance, we could have also used the IF statement to generate similar output. We can also use WHERE and IF statements in the same data step:

DATA Updated_2019;
SET Cost_Living;
WHERE Year(Updated) = 2019;
IF Index >= 80;
RUN;

This further...

Dictionary tables

Some SAS software packages require minimal coding experience to get your work done. However, once you want to do anything advanced, it gets restrictive to use just the predefined options available in the package. At that moment, most users tend to write code. Chances are that if you want to go beyond what SAS already offers as predefined procedures and functionalities, you want to write advanced programs/macros. While we will delve into macros later on in this book, there is an aspect of SAS that is being leveraged less by some users. These are the dictionaries. But what are they and how can they be useful?

Some reasons for using dictionary tables are as follows:

  • They hold all the information about SAS libraries, datasets, macros, and external files that are being used in the SAS session.
  • It is a read-only view, so there are no chances of it being compromised...

Summary

In this chapter, we covered the basics of SAS dataset fundamentals and how to create a table, compile it, and then execute it. We also looked into the basic syntax of the SAS programming language. Then, we learned how to compress, encrypt, and index a dataset. Finally, we learned the various operators in SAS, and how to format and subset the dataset.

In the next chapter, we will learn how to manipulate, sanitize, and transform data.

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Key benefits

  • Build enterprise-class data solutions using SAS and become well-versed in SAS programming
  • Work with different data structures, and run SQL queries to manipulate your data
  • Explore essential concepts and techniques with practical examples to confidently pass the SAS certification exam

Description

SAS is one of the leading enterprise tools in the world today when it comes to data management and analysis. It enables the fast and easy processing of data and helps you gain valuable business insights for effective decision-making. This book will serve as a comprehensive guide that will prepare you for the SAS certification exam. After a quick overview of the SAS architecture and components, the book will take you through the different approaches to importing and reading data from different sources using SAS. You will then cover SAS Base and 4GL, understanding data management and analysis, along with exploring SAS functions for data manipulation and transformation. Next, you'll discover SQL procedures and get up to speed on creating and validating queries. In the concluding chapters, you'll learn all about data visualization, right from creating bar charts and sample geographic maps through to assigning patterns and formats. In addition to this, the book will focus on macro programming and its advanced aspects. By the end of this book, you will be well versed in SAS programming and have the skills you need to easily handle and manage your data-related problems in SAS.

Who is this book for?

Budding or experienced data professionals who want to get started with SAS will benefit from this book. Those looking to prepare for the SAS certification exam will also find this book to be a useful resource. Some understanding of basic data management concepts will help you get the most out of this book.

What you will learn

  • Explore a variety of SAS modules and packages for efficient data analysis
  • Use SAS 4GL functions to manipulate, merge, sort, and transform data
  • Gain useful insights into advanced PROC SQL options in SAS to interact with data
  • Get to grips with SAS Macro and define your own macros to share data
  • Discover the different graphical libraries to shape and visualize data with
  • Apply the SAS Output Delivery System to prepare detailed reports
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Table of Contents

16 Chapters
Section 1: SAS Basics Chevron down icon Chevron up icon
Introduction to SAS Programming Chevron down icon Chevron up icon
Data Manipulation and Transformation Chevron down icon Chevron up icon
Section 2: Merging, Optimizing, and Descriptive Statistics Chevron down icon Chevron up icon
Combining, Indexing, Encryption, and Compression Techniques Simplified Chevron down icon Chevron up icon
Power of Statistics, Reporting, Transforming Procedures, and Functions Chevron down icon Chevron up icon
Section 3: Advanced Programming Chevron down icon Chevron up icon
Advanced Programming Techniques - SAS Macros Chevron down icon Chevron up icon
Powerful Functions, Options, and Automatic Variables Simplified Chevron down icon Chevron up icon
Section 4: SQL in SAS Chevron down icon Chevron up icon
Advanced Programming Techniques Using PROC SQL Chevron down icon Chevron up icon
Deep Dive into PROC SQL Chevron down icon Chevron up icon
Section 5: Data Visualization and Reporting Chevron down icon Chevron up icon
Data Visualization Chevron down icon Chevron up icon
Reporting and Output Delivery System Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
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