book

Learning SAS by Example

Name: Learning SAS by Example
Author: Ron Cody
ISBN: 9781635266566

by Ron Cody

July 2018

Beginner

536 pages

12h 32m

English

SAS Institute

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List of Programs
Preface
About This Book
About the Author
Acknowledgments
Part 1: Getting Started
Chapter 1: What Is SAS?
1.1 Introduction1.2 Getting Data into SAS1.3 A Sample SAS Program1.4 SAS Names1.5 SAS Data Sets and SAS Data Types1.6 The SAS Windowing Environment, SAS Enterprise Guide, and the SAS University Edition1.7 Problems
Chapter 2: Writing Your First SAS Program
2.1 A Simple Program to Read Raw Data and Produce a Report2.2 Enhancing the Program2.3 More on Comment Statements2.4 How SAS Works (a Look inside the “Black Box”)2.5 Problems
Part 2: DATA Step Processing
Chapter 3: Reading Raw Data from External Files
3.1 Introduction3.2 Reading Data Values Separated by Blanks3.3 Specifying Missing Values with List Input3.4 Reading Data Values Separated by Commas (CSV Files)3.5 Using an alternative Method to Specify an External File3.6 Reading Data Values Separated by Delimiters Other Than Blanks or Commas3.7 Placing Data Lines Directly in Your Program (the DATALINES Statement)3.8 Specifying INFILE Options with the DATALINES Statement3.9 Reading Raw Data from Fixed Columns—Method 1: Column Input3.10 Reading Raw Data from Fixed Columns—Method 2: Formatted Input3.11 Using a FORMAT Statement in a DATA Step versus in a Procedure3.12 Using Informats with List Input3.13 Supplying an INFORMAT Statement with List Input3.14 Using List Input with Embedded Delimiters3.15 Problems

Chapter 4: Creating Permanent SAS Data Sets
4.1 Introduction4.2 SAS Libraries—The LIBNAME Statement4.3 Why Create Permanent SAS Data Sets?4.4 Examining the Descriptor Portion of a SAS Data Set Using PROC CONTENTS4.5 Listing All the SAS Data Sets in a SAS Library Using PROC CONTENTS4.6 Viewing the Descriptor Portion of a SAS Data Set Using a Point-and-Click Approach4.7 Viewing the Data Portion of a SAS Data Set Using PROC PRINT4.8 Using a SAS Data Set as Input to a DATA Step4.9 DATA _NULL_: A Data Set That Isn’t4.10 Problems
Chapter 5: Creating Labels and Formats
5.1 Adding Labels to Your Variables5.2 Using Formats to Enhance Your Output5.3 Regrouping Values Using Formats5.4 More on Format Ranges5.5 Storing Your Formats in a Format Library5.6 Permanent Data Set Attributes5.7 Accessing a Permanent SAS Data Set with User-Defined Formats5.8 Displaying Your Format Definitions5.9 Problems
Chapter 6: Reading and Writing Data from an Excel Spreadsheet
6.1 Introduction6.2 Using the Import Wizard to Convert a Spreadsheet to a SAS Data Set6.3 Creating an Excel Spreadsheet from a SAS Data Set6.4 Using an Engine to Read an Excel Spreadsheet6.5 Using the SAS Output Delivery System to Convert a SAS Data Set to an Excel Spreadsheet6.6 A Quick Look at the Import Utility in SAS Studio6.7 Problems
Chapter 7: Performing Conditional Processing
7.1 Introduction7.2 The IF and ELSE IF Statements7.3 The Subsetting IF Statement7.4 The IN Operator7.5 Using a SELECT Statement for Logical Tests7.6 Using Boolean Logic (AND, OR, and NOT Operators)7.7 A Caution When Using Multiple OR Operators7.8 The WHERE Statement7.9 Some Useful WHERE Operators7.10 Problems
Chapter 8: Performing Iterative Processing: Looping
8.1 Introduction8.2 DO Groups8.3 The Sum Statement8.4 The Iterative DO Loop8.5 Other Forms of an Iterative DO Loop8.6 DO WHILE and DO UNTIL Statements8.7 A Caution When Using DO UNTIL Statements8.8 LEAVE and CONTINUE Statements8.9 Problems
Chapter 9: Working with Dates
9.1 Introduction9.2 How SAS Stores Dates9.3 Reading Date Values from Text Data9.4 Computing the Number of Years between Two Dates9.5 Demonstrating a Date Constant9.6 Computing the Current Date9.7 Extracting the Day of the Week, Day of the Month, Month, and Year from a SAS Date9.8 Creating a SAS Date from Month, Day, and Year Values9.9 Substituting the 15th of the Month when the Day Value Is Missing9.10 Using Date Interval Functions9.11 Problems
Chapter 10: Subsetting and Combining SAS Data Sets
10.1 Introduction10.2 Subsetting a SAS Data Set10.3 Creating More Than One Subset Data Set in One DATA Step10.4 Adding Observations to a SAS Data Set10.5 Interleaving Data Sets10.6 Combining Detail and Summary Data10.7 Merging Two Data Sets10.8 Omitting the BY Statement in a Merge10.9 Controlling Observations in a Merged Data Set10.10 More Uses for IN= Variables10.11 When Does a DATA Step End?10.12 Merging Two Data Sets with Different BY Variable Names10.13 Merging Two Data Sets with Different BY Variable Data Types10.14 One-to-One, One-to-Many, and Many-to-Many Merges10.15 Updating a Master File from a Transaction File10.16 Problems
Chapter 11: Working with Numeric Functions
11.1 Introduction11.2 Functions That Round and Truncate Numeric Values11.3 Functions That Work with Missing Values11.4 Setting Character and Numeric Values to Missing11.5 Descriptive Statistics Functions11.6 Computing Sums within an Observation11.7 Mathematical Functions11.8 Computing Some Useful Constants11.9 Generating Random Numbers11.10 Special Functions11.11 Functions That Return Values from Previous Observations11.12 Sorting Within an Observations—a Game Changer11.13 Problems
Chapter 12: Working with Character Functions
12.1 Introduction12.2 Determining the Length of a Character Value12.3 Changing the Case of Characters12.4 Removing Characters from Strings12.5 Joining Two or More Strings Together12.6 Removing Leading or Trailing Blanks12.7 Using the COMPRESS Function to Remove Characters from a String12.8 Searching for Characters12.9 Searching for Individual Characters12.10 Searching for Words in a String12.11 Searching for Character Classes12.12 Using the NOT Functions for Data Cleaning12.13 Extracting Part of a String12.14 Dividing Strings into Words12.15 Performing a Fuzzy Match12.16 Substituting Strings or Words12.17 Problems
Chapter 13: Working with Arrays
13.1 Introduction13.2 Setting Values of 999 to a SAS Missing Value for Several Numeric Variables13.3 Setting Values of NA and ? to a Missing Character Value13.4 Converting All Character Values to Propercase13.5 Using an Array to Create New Variables13.6 Changing the Array Bounds13.7 Temporary Arrays13.8 Loading the Initial Values of a Temporary Array from a Raw Data File13.9 Using a Multidimensional Array for Table Lookup13.10 Problems
Part 3: Presenting and Summarizing Your Data
Chapter 14: Displaying Your Data
14.1 Introduction14.2 The Basics14.3 Changing the Appearance of Your Listing14.4 Changing the Appearance of Values14.5 Controlling the Observations That Appear in Your Listing14.6 Adding Titles and Footnotes to Your Listing14.7 Changing the Order of Your Listing14.8 Sorting by More Than One Variable14.9 Labeling Your Column Headings14.10 Adding Subtotals and Totals to Your Listing14.11 Making Your Listing Easier to Read14.12 Adding the Number of Observations to Your Listing14.13 Listing the First n Observations of Your Data Set14.14 Problems
Chapter 15: Creating Customized Reports
15.1 Introduction15.2 Using PROC REPORT15.3 Selecting the Variables to Include in Your Report15.4 Comparing Detail and Summary Reports15.5 Producing a Summary Report15.6 Demonstrating the FLOW Option of PROC REPORT15.7 Using Two Grouping Variables15.8 Changing the Order of Variables in the COLUMN Statement15.9 Changing the Order of Rows in a Report15.10 Applying the ORDER Usage to Two Variables15.11 Creating a Multi-Column Report15.12 Producing Report Breaks15.13 Using a Nonprinting Variable to Order a Report15.14 Computing a New Variable with PROC REPORT15.15 Computing a Character Variable in a COMPUTE Block15.16 Creating an ACROSS Variable with PROC REPORT15.17 Using an ACROSS Usage to Display Statistics15.18 Problems
Chapter 16: Summarizing Your Data
16.1 Introduction16.2 PROC MEANS—Starting from the Beginning16.3 Adding a BY Statement to PROC MEANS16.4 Using a CLASS Statement with PROC MEANS16.5 Applying a Format to a CLASS Variable16.6 Deciding between a BY Statement and a CLASS Statement16.7 Creating Summary Data Sets Using PROC MEANS16.8 Outputting Other Descriptive Statistics with PROC MEANS16.9 Asking SAS to Name the Variables in the Output Data Set16.10 Outputting a Summary Data Set: Including a BY Statement16.11 Outputting a Summary Data Set: Using a CLASS Statement16.12 Using Two CLASS Variables with PROC MEANS16.13 Selecting Different Statistics for Each Variable16.14 Printing all Possible Combinations of Your Class Variables16.15 Problems
Chapter 17: Counting Frequencies
17.1 Introduction17.2 Counting Frequencies17.3 Selecting Variables for PROC FREQ17.4 Using Formats to Label the Output17.5 Using Formats to Group Values17.6 Problems Grouping Values with PROC FREQ17.7 Displaying Missing Values in the Frequency Table17.8 Changing the Order of Values in PROC FREQ17.9 Producing Two-Way Tables17.10 Requesting Multiple Two-Way Tables17.11 Producing Three-Way Tables17.12 Problems
Chapter 18: Creating Tabular Reports
18.1 Introduction18.2 A Simple PROC TABULATE Table18.3 Describing the Three PROC TABULATE Operators18.4 Using the Keyword ALL18.5 Producing Descriptive Statistics18.6 Combining CLASS and Analysis Variables in a Table18.7 Customizing Your Table18.8 Demonstrating a More Complex Table18.9 Computing Row and Column Percentages18.10 Displaying Percentages in a Two-Dimensional Table18.11 Computing Column Percentages18.12 Computing Percentages on Numeric Variables18.13 Understanding How Missing Values Affect PROC TABULATE Output18.14 Problems
Chapter 19: Introducing the Output Delivery System
19.1 Introduction19.2 Sending SAS Output to an HTML File19.3 Creating a Table of Contents19.4 Selecting a Different HTML Style19.5 Choosing Other ODS Destinations19.6 Selecting or Excluding Portions of SAS Output19.7 Sending Output to a SAS Data Set19.8 Problems
Chapter 20: Creating Charts and Graphs
20.1 Introduction20.2 Creating Bar Charts20.3 Displaying Statistics for a Response Variable20.4 Creating Scatter Plots20.5 Adding a Regression Line and Confidence Limits to the Plot20.6 Generating Time Series Plots20.7 Describing Two Methods of Generating Smooth Curves20.8 Generating Histograms20.9 Generating a Simple Box Plot20.10 Producing a Box Plot with a Grouping Variable20.11 Demonstrating Overlays and Transparency20.12 Problems
Part 4: Advanced Topics
Chapter 21: Using Advanced INPUT Techniques
21.1 Introduction21.2 Handling Missing Values at the End of a Line21.3 Reading Short Data Lines21.4 Reading External Files with Lines Longer Than 32,767 Characters21.5 Detecting the End of the File21.6 Reading a Portion of a Raw Data File21.7 Reading Data from Multiple Files21.8 Reading Data from Multiple Files Using a FILENAME Statement21.9 Reading External Filenames from a Data File21.10 Reading Multiple Lines of Data to Create One Observation21.11 Reading Data Conditionally (the Single Trailing @ Sign)21.12 More Examples of the Single Trailing @ Sign21.13 Creating Multiple Observations from One Line of Input21.14 Using Variable and Informat Lists21.15 Using Relative Column Pointers to Read a Complex Data Structure Efficiently21.16 Problems
Chapter 22: Using Advanced Features of User-Defined Formats and Informats
22.1 Introduction22.2 Using Formats to Recode Variables22.3 Using Formats with a PUT Function to Create New Variables22.4 Creating User-Defined Informats22.5 Reading Character and Numeric Data in One Step22.6 Using Formats (and Informats) to Perform Table Lookup22.7 Using a SAS Data Set to Create a Format22.8 Updating and Maintaining Your Formats22.9 Using Formats within Formats22.10 Multilabel Formats22.11 Using the INPUTN Function to Perform a More Complicated Table Lookup22.12 Problems
Chapter 23: Restructuring SAS Data Sets
23.1 Introduction23.2 Converting a Data Set with One Observation per Subject to a Data Set with Several Observations per Subject: Using a DATA Step23.3 Converting a Data Set with Several Observations per Subject to a Data Set with One Observation per Subject: Using a DATA Step23.4 Converting a Data Set with One Observation per Subject to a Data Set with Several Observations per Subject: Using PROC TRANSPOSE23.5 Converting a Data Set with Several Observations per Subject to a Data Set with One Observation per Subject: Using PROC TRANSPOSE23.6 Problems
Chapter 24: Working with Multiple Observations per Subject
24.1 Introduction24.2 Identifying the First or Last Observation in a Group24.3 Counting the Number of Visits Using PROC FREQ24.4 Computing Differences between Observations24.5 Computing Differences between the First and Last Observation in a BY Group Using the LAG Function24.6 Computing Differences between the First and Last Observation in a BY Group Using a RETAIN Statement24.7 Using a Retained Variable to “Remember” a Previous Value24.8 Problems
Chapter 25: Introducing the SAS Macro Language
25.1 Introduction25.2 Macro Variables: What Are They?25.3 Some Built-In Macro Variables25.4 Assigning Values to Macro Variables with a %LET Statement25.5 Demonstrating a Simple Macro25.6 Describing Positional and Keyword Macro Parameters25.7 A Word about Tokens25.8 Another Example of Using a Macro Variable as a Prefix25.9 Using a Macro Variable to Transfer a Value between DATA Steps25.10 Problems
Chapter 26: Introducing the Structured Query Language
26.1 Introduction26.2 Some Basics26.3 Joining Two Tables (Merge)26.4 Left, Right, and Full Joins26.5 Concatenating Data Sets26.6 Using Summary Functions26.7 Demonstrating the ORDER Clause26.8 An Example of Fuzzy Matching26.9 Problems
Chapter 27: Introducing Perl Regular Expressions
27.1 Introduction27.2 Describing the Syntax of Regular Expressions27.3 Testing That Social Security Numbers Are in Standard Form27.4 Checking for Valid ZIP Codes27.5 Verifying That Phone Numbers Are in a Standard Form27.6 Describing the PRXPARSE Function27.7 Problems
Solutions to Odd-Numbered Exercises
Index

Overview

Learn to program SAS by example!

Learning SAS by Example, A Programmer’s Guide, Second Edition, teaches SAS programming from very basic concepts to more advanced topics. Because most programmers prefer examples rather than reference-type syntax, this book uses short examples to explain each topic. The second edition has brought this classic book on SAS programming up to the latest SAS version, with new chapters that cover topics such as PROC SGPLOT and Perl regular expressions. This book belongs on the shelf (or e-book reader) of anyone who programs in SAS, from those with little programming experience who want to learn SAS to intermediate and even advanced SAS programmers who want to learn new techniques or identify new ways to accomplish existing tasks.

In an instructive and conversational tone, author Ron Cody clearly explains each programming technique and then illustrates it with one or more real-life examples, followed by a detailed description of how the program works. The text is divided into four major sections: Getting Started, DATA Step Processing, Presenting and Summarizing Your Data, and Advanced Topics. Subjects addressed include

Reading data from external sources
Learning details of DATA step programming
Subsetting and combining SAS data sets
Understanding SAS functions and working with arrays
Creating reports with PROC REPORT and PROC TABULATE
Getting started with the SAS macro language
Leveraging PROC SQL
Generating high-quality graphics
Using advanced features of user-defined formats and informats
Restructuring SAS data sets
Working with multiple observations per subject
Getting started with Perl regular expressions

You can test your knowledge and hone your skills by solving the problems at the end of each chapter.

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