Book Image

Hands-On SAS for Data Analysis

By : Harish Gulati
Book Image

Hands-On SAS for Data Analysis

By: Harish Gulati

Overview of this book

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.

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Table of Contents (17 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Section 1: SAS Basics
Section 1: SAS Basics
2
Introduction to SAS Programming
Introduction to SAS Programming
SAS dataset fundamentals
SAS programming language – basic syntax
SAS LOG
Dataset options
SAS operators
Formats
Subsetting datasets
Dictionary tables
Summary
3
Data Manipulation and Transformation
Data Manipulation and Transformation
Length of a variable
Case conversion and alignment
String identification
Dealing with blanks
Missing and multiple values
Interval calculations
Concatenation
Logic and control
Number manipulation
Summary
4
Section 2: Merging, Optimizing, and Descriptive Statistics
Section 2: Merging, Optimizing, and Descriptive Statistics
5
Combining, Indexing, Encryption, and Compression Techniques Simplified
Combining, Indexing, Encryption, and Compression Techniques Simplified
Introduction to combining
Concatenation
Interleaving
Merging
Indexing
Encryption
Summary
6
Power of Statistics, Reporting, Transforming Procedures, and Functions
Power of Statistics, Reporting, Transforming Procedures, and Functions
Proc Freq
Proc Univariate
Proc Means and Summary
Proc Corr
Proc REG
Proc Transpose
Summary
7
Section 3: Advanced Programming
Section 3: Advanced Programming
8
Advanced Programming Techniques - SAS Macros
Advanced Programming Techniques - SAS Macros
What are macros?
Macro variable processing
Macro resolution tracking
Macro definition processing
Comparing positional and keywords parameters
Data-driven programming
Leveraging automatic global macro variables
Macros that evaluate
Writing efficient macros
Summary
9
Powerful Functions, Options, and Automatic Variables Simplified
Powerful Functions, Options, and Automatic Variables Simplified
NOMPREPLACE and MREPLACE
NOMCOMPILE and NCOMPILE
MCOMPILENOTE
NOMEXECNOTE and MEXECNOTE
MAUTOCOMPLOC
MACRO and NOMACRO
Exchanging values between the DATA step and macro variables
CALL EXECUTE
Altering the CALL SYMPUT example
Resolving macro variables
Macro quoting
Summary
10
Section 4: SQL in SAS
Section 4: SQL in SAS
11
Advanced Programming Techniques Using PROC SQL
Advanced Programming Techniques Using PROC SQL
Comparing data steps and Proc SQL
Proc SQL joins
Proc SQL essentials
Dictionary tables
Summary
12
Deep Dive into PROC SQL
Deep Dive into PROC SQL
SAS views in Proc SQL
Making changes with Proc SQL
Identifying duplicates using Proc SQL
Creating an index in Proc SQL
Macros and Proc SQL
Summary
13
Section 5: Data Visualization and Reporting
Section 5: Data Visualization and Reporting
14
Data Visualization
Data Visualization
The role of data visualization in analytics
Histograms
Line plots
Vertical and horizontal bar charts
Scatter charts
Box plot
Summary
15
Reporting and Output Delivery System
Reporting and Output Delivery System
Proc Tabulate
Specifying the ODS destination
Formatting ODS files
ODS Excel charts
Summary
16
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Exchanging values between the DATA step and macro variables

In upcoming sections, we will explore the various options that we have for exchanging values between the DATA step and macro variables and compare them.

Choosing between CALL SYMGET and CALL SYMPUT

In previous chapters, we discussed CALL SYMPUT. As you may recall, CALL SYMPUT was used to transfer DATA step variable values to a macro variable. On many occasions, you will need to transfer values from macro variables to DATA steps. Always remember the following process flow when you're trying to remember if you need to use SYMPUT or SYMGET in coding:

Without the SYMGET function, you will struggle to use macro variables in the DATA step, which includes the DATALINES...

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