- List of Programs
- Preface
- About This Book
- About the Author
- Acknowledgments
- Part 1: Getting Started
- Part 2: DATA Step Processing
- Chapter 3: Reading Raw Data from External Files
- 3.1 Introduction
- 3.2 Reading Data Values Separated by Blanks
- 3.3 Specifying Missing Values with List Input
- 3.4 Reading Data Values Separated by Commas (CSV Files)
- 3.5 Using an alternative Method to Specify an External File
- 3.6 Reading Data Values Separated by Delimiters Other Than Blanks or Commas
- 3.7 Placing Data Lines Directly in Your Program (the DATALINES Statement)
- 3.8 Specifying INFILE Options with the DATALINES Statement
- 3.9 Reading Raw Data from Fixed Columns—Method 1: Column Input
- 3.10 Reading Raw Data from Fixed Columns—Method 2: Formatted Input
- 3.11 Using a FORMAT Statement in a DATA Step versus in a Procedure
- 3.12 Using Informats with List Input
- 3.13 Supplying an INFORMAT Statement with List Input
- 3.14 Using List Input with Embedded Delimiters
- 3.15 Problems
- Chapter 4: Creating Permanent SAS Data Sets
- 4.1 Introduction
- 4.2 SAS Libraries—The LIBNAME Statement
- 4.3 Why Create Permanent SAS Data Sets?
- 4.4 Examining the Descriptor Portion of a SAS Data Set Using PROC CONTENTS
- 4.5 Listing All the SAS Data Sets in a SAS Library Using PROC CONTENTS
- 4.6 Viewing the Descriptor Portion of a SAS Data Set Using a Point-and-Click Approach
- 4.7 Viewing the Data Portion of a SAS Data Set Using PROC PRINT
- 4.8 Using a SAS Data Set as Input to a DATA Step
- 4.9 DATA _NULL_: A Data Set That Isn’t
- 4.10 Problems
- Chapter 5: Creating Labels and Formats
- 5.1 Adding Labels to Your Variables
- 5.2 Using Formats to Enhance Your Output
- 5.3 Regrouping Values Using Formats
- 5.4 More on Format Ranges
- 5.5 Storing Your Formats in a Format Library
- 5.6 Permanent Data Set Attributes
- 5.7 Accessing a Permanent SAS Data Set with User-Defined Formats
- 5.8 Displaying Your Format Definitions
- 5.9 Problems
- Chapter 6: Reading and Writing Data from an Excel Spreadsheet
- 6.1 Introduction
- 6.2 Using the Import Wizard to Convert a Spreadsheet to a SAS Data Set
- 6.3 Creating an Excel Spreadsheet from a SAS Data Set
- 6.4 Using an Engine to Read an Excel Spreadsheet
- 6.5 Using the SAS Output Delivery System to Convert a SAS Data Set to an Excel Spreadsheet
- 6.6 A Quick Look at the Import Utility in SAS Studio
- 6.7 Problems
- Chapter 7: Performing Conditional Processing
- 7.1 Introduction
- 7.2 The IF and ELSE IF Statements
- 7.3 The Subsetting IF Statement
- 7.4 The IN Operator
- 7.5 Using a SELECT Statement for Logical Tests
- 7.6 Using Boolean Logic (AND, OR, and NOT Operators)
- 7.7 A Caution When Using Multiple OR Operators
- 7.8 The WHERE Statement
- 7.9 Some Useful WHERE Operators
- 7.10 Problems
- Chapter 8: Performing Iterative Processing: Looping
- Chapter 9: Working with Dates
- 9.1 Introduction
- 9.2 How SAS Stores Dates
- 9.3 Reading Date Values from Text Data
- 9.4 Computing the Number of Years between Two Dates
- 9.5 Demonstrating a Date Constant
- 9.6 Computing the Current Date
- 9.7 Extracting the Day of the Week, Day of the Month, Month, and Year from a SAS Date
- 9.8 Creating a SAS Date from Month, Day, and Year Values
- 9.9 Substituting the 15th of the Month when the Day Value Is Missing
- 9.10 Using Date Interval Functions
- 9.11 Problems
- Chapter 10: Subsetting and Combining SAS Data Sets
- 10.1 Introduction
- 10.2 Subsetting a SAS Data Set
- 10.3 Creating More Than One Subset Data Set in One DATA Step
- 10.4 Adding Observations to a SAS Data Set
- 10.5 Interleaving Data Sets
- 10.6 Combining Detail and Summary Data
- 10.7 Merging Two Data Sets
- 10.8 Omitting the BY Statement in a Merge
- 10.9 Controlling Observations in a Merged Data Set
- 10.10 More Uses for IN= Variables
- 10.11 When Does a DATA Step End?
- 10.12 Merging Two Data Sets with Different BY Variable Names
- 10.13 Merging Two Data Sets with Different BY Variable Data Types
- 10.14 One-to-One, One-to-Many, and Many-to-Many Merges
- 10.15 Updating a Master File from a Transaction File
- 10.16 Problems
- Chapter 11: Working with Numeric Functions
- 11.1 Introduction
- 11.2 Functions That Round and Truncate Numeric Values
- 11.3 Functions That Work with Missing Values
- 11.4 Setting Character and Numeric Values to Missing
- 11.5 Descriptive Statistics Functions
- 11.6 Computing Sums within an Observation
- 11.7 Mathematical Functions
- 11.8 Computing Some Useful Constants
- 11.9 Generating Random Numbers
- 11.10 Special Functions
- 11.11 Functions That Return Values from Previous Observations
- 11.12 Sorting Within an Observations—a Game Changer
- 11.13 Problems
- Chapter 12: Working with Character Functions
- 12.1 Introduction
- 12.2 Determining the Length of a Character Value
- 12.3 Changing the Case of Characters
- 12.4 Removing Characters from Strings
- 12.5 Joining Two or More Strings Together
- 12.6 Removing Leading or Trailing Blanks
- 12.7 Using the COMPRESS Function to Remove Characters from a String
- 12.8 Searching for Characters
- 12.9 Searching for Individual Characters
- 12.10 Searching for Words in a String
- 12.11 Searching for Character Classes
- 12.12 Using the NOT Functions for Data Cleaning
- 12.13 Extracting Part of a String
- 12.14 Dividing Strings into Words
- 12.15 Performing a Fuzzy Match
- 12.16 Substituting Strings or Words
- 12.17 Problems
- Chapter 13: Working with Arrays
- 13.1 Introduction
- 13.2 Setting Values of 999 to a SAS Missing Value for Several Numeric Variables
- 13.3 Setting Values of NA and ? to a Missing Character Value
- 13.4 Converting All Character Values to Propercase
- 13.5 Using an Array to Create New Variables
- 13.6 Changing the Array Bounds
- 13.7 Temporary Arrays
- 13.8 Loading the Initial Values of a Temporary Array from a Raw Data File
- 13.9 Using a Multidimensional Array for Table Lookup
- 13.10 Problems
- Chapter 3: Reading Raw Data from External Files
- Part 3: Presenting and Summarizing Your Data
- Chapter 14: Displaying Your Data
- 14.1 Introduction
- 14.2 The Basics
- 14.3 Changing the Appearance of Your Listing
- 14.4 Changing the Appearance of Values
- 14.5 Controlling the Observations That Appear in Your Listing
- 14.6 Adding Titles and Footnotes to Your Listing
- 14.7 Changing the Order of Your Listing
- 14.8 Sorting by More Than One Variable
- 14.9 Labeling Your Column Headings
- 14.10 Adding Subtotals and Totals to Your Listing
- 14.11 Making Your Listing Easier to Read
- 14.12 Adding the Number of Observations to Your Listing
- 14.13 Listing the First n Observations of Your Data Set
- 14.14 Problems
- Chapter 15: Creating Customized Reports
- 15.1 Introduction
- 15.2 Using PROC REPORT
- 15.3 Selecting the Variables to Include in Your Report
- 15.4 Comparing Detail and Summary Reports
- 15.5 Producing a Summary Report
- 15.6 Demonstrating the FLOW Option of PROC REPORT
- 15.7 Using Two Grouping Variables
- 15.8 Changing the Order of Variables in the COLUMN Statement
- 15.9 Changing the Order of Rows in a Report
- 15.10 Applying the ORDER Usage to Two Variables
- 15.11 Creating a Multi-Column Report
- 15.12 Producing Report Breaks
- 15.13 Using a Nonprinting Variable to Order a Report
- 15.14 Computing a New Variable with PROC REPORT
- 15.15 Computing a Character Variable in a COMPUTE Block
- 15.16 Creating an ACROSS Variable with PROC REPORT
- 15.17 Using an ACROSS Usage to Display Statistics
- 15.18 Problems
- Chapter 16: Summarizing Your Data
- 16.1 Introduction
- 16.2 PROC MEANS—Starting from the Beginning
- 16.3 Adding a BY Statement to PROC MEANS
- 16.4 Using a CLASS Statement with PROC MEANS
- 16.5 Applying a Format to a CLASS Variable
- 16.6 Deciding between a BY Statement and a CLASS Statement
- 16.7 Creating Summary Data Sets Using PROC MEANS
- 16.8 Outputting Other Descriptive Statistics with PROC MEANS
- 16.9 Asking SAS to Name the Variables in the Output Data Set
- 16.10 Outputting a Summary Data Set: Including a BY Statement
- 16.11 Outputting a Summary Data Set: Using a CLASS Statement
- 16.12 Using Two CLASS Variables with PROC MEANS
- 16.13 Selecting Different Statistics for Each Variable
- 16.14 Printing all Possible Combinations of Your Class Variables
- 16.15 Problems
- Chapter 17: Counting Frequencies
- 17.1 Introduction
- 17.2 Counting Frequencies
- 17.3 Selecting Variables for PROC FREQ
- 17.4 Using Formats to Label the Output
- 17.5 Using Formats to Group Values
- 17.6 Problems Grouping Values with PROC FREQ
- 17.7 Displaying Missing Values in the Frequency Table
- 17.8 Changing the Order of Values in PROC FREQ
- 17.9 Producing Two-Way Tables
- 17.10 Requesting Multiple Two-Way Tables
- 17.11 Producing Three-Way Tables
- 17.12 Problems
- Chapter 18: Creating Tabular Reports
- 18.1 Introduction
- 18.2 A Simple PROC TABULATE Table
- 18.3 Describing the Three PROC TABULATE Operators
- 18.4 Using the Keyword ALL
- 18.5 Producing Descriptive Statistics
- 18.6 Combining CLASS and Analysis Variables in a Table
- 18.7 Customizing Your Table
- 18.8 Demonstrating a More Complex Table
- 18.9 Computing Row and Column Percentages
- 18.10 Displaying Percentages in a Two-Dimensional Table
- 18.11 Computing Column Percentages
- 18.12 Computing Percentages on Numeric Variables
- 18.13 Understanding How Missing Values Affect PROC TABULATE Output
- 18.14 Problems
- Chapter 19: Introducing the Output Delivery System
- Chapter 20: Creating Charts and Graphs
- 20.1 Introduction
- 20.2 Creating Bar Charts
- 20.3 Displaying Statistics for a Response Variable
- 20.4 Creating Scatter Plots
- 20.5 Adding a Regression Line and Confidence Limits to the Plot
- 20.6 Generating Time Series Plots
- 20.7 Describing Two Methods of Generating Smooth Curves
- 20.8 Generating Histograms
- 20.9 Generating a Simple Box Plot
- 20.10 Producing a Box Plot with a Grouping Variable
- 20.11 Demonstrating Overlays and Transparency
- 20.12 Problems
- Chapter 14: Displaying Your Data
- Part 4: Advanced Topics
- Chapter 21: Using Advanced INPUT Techniques
- 21.1 Introduction
- 21.2 Handling Missing Values at the End of a Line
- 21.3 Reading Short Data Lines
- 21.4 Reading External Files with Lines Longer Than 32,767 Characters
- 21.5 Detecting the End of the File
- 21.6 Reading a Portion of a Raw Data File
- 21.7 Reading Data from Multiple Files
- 21.8 Reading Data from Multiple Files Using a FILENAME Statement
- 21.9 Reading External Filenames from a Data File
- 21.10 Reading Multiple Lines of Data to Create One Observation
- 21.11 Reading Data Conditionally (the Single Trailing @ Sign)
- 21.12 More Examples of the Single Trailing @ Sign
- 21.13 Creating Multiple Observations from One Line of Input
- 21.14 Using Variable and Informat Lists
- 21.15 Using Relative Column Pointers to Read a Complex Data Structure Efficiently
- 21.16 Problems
- Chapter 22: Using Advanced Features of User-Defined Formats and Informats
- 22.1 Introduction
- 22.2 Using Formats to Recode Variables
- 22.3 Using Formats with a PUT Function to Create New Variables
- 22.4 Creating User-Defined Informats
- 22.5 Reading Character and Numeric Data in One Step
- 22.6 Using Formats (and Informats) to Perform Table Lookup
- 22.7 Using a SAS Data Set to Create a Format
- 22.8 Updating and Maintaining Your Formats
- 22.9 Using Formats within Formats
- 22.10 Multilabel Formats
- 22.11 Using the INPUTN Function to Perform a More Complicated Table Lookup
- 22.12 Problems
- Chapter 23: Restructuring SAS Data Sets
- 23.1 Introduction
- 23.2 Converting a Data Set with One Observation per Subject to a Data Set with Several Observations per Subject: Using a DATA Step
- 23.3 Converting a Data Set with Several Observations per Subject to a Data Set with One Observation per Subject: Using a DATA Step
- 23.4 Converting a Data Set with One Observation per Subject to a Data Set with Several Observations per Subject: Using PROC TRANSPOSE
- 23.5 Converting a Data Set with Several Observations per Subject to a Data Set with One Observation per Subject: Using PROC TRANSPOSE
- 23.6 Problems
- Chapter 24: Working with Multiple Observations per Subject
- 24.1 Introduction
- 24.2 Identifying the First or Last Observation in a Group
- 24.3 Counting the Number of Visits Using PROC FREQ
- 24.4 Computing Differences between Observations
- 24.5 Computing Differences between the First and Last Observation in a BY Group Using the LAG Function
- 24.6 Computing Differences between the First and Last Observation in a BY Group Using a RETAIN Statement
- 24.7 Using a Retained Variable to “Remember” a Previous Value
- 24.8 Problems
- Chapter 25: Introducing the SAS Macro Language
- 25.1 Introduction
- 25.2 Macro Variables: What Are They?
- 25.3 Some Built-In Macro Variables
- 25.4 Assigning Values to Macro Variables with a %LET Statement
- 25.5 Demonstrating a Simple Macro
- 25.6 Describing Positional and Keyword Macro Parameters
- 25.7 A Word about Tokens
- 25.8 Another Example of Using a Macro Variable as a Prefix
- 25.9 Using a Macro Variable to Transfer a Value between DATA Steps
- 25.10 Problems
- Chapter 26: Introducing the Structured Query Language
- Chapter 27: Introducing Perl Regular Expressions
- Chapter 21: Using Advanced INPUT Techniques
- Solutions to Odd-Numbered Exercises
- Index
Preface to the Second Edition
It’s been almost 11 years since the first edition of this book was published, and I felt that it was time to bring it up-to-date. One major change is that all the SAS output is now displayed as HTML images, using the default style HTMLBlue. Not only does it look nicer than the old monospaced listing output, but the book figures are now images that can be viewed and sized on e-devices.
While we are on the topic of major changes, I should mention that a new chapter on Perl regular expressions was added, and the previous SAS/GRAPH chapter was replaced by a chapter on PROC SGPLOT. This procedure is easier to use than SAS/GRAPH, and (drum roll please) it is included with Base SAS.
People have come up to me at SAS conferences and told me that they learned SAS programming from the first edition of this book. That is really nice to hear. I hope that this edition will do the same for a whole new generation of programmers.
Ron Cody
Summer, 2018
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