Combining and Modifying SAS Data Sets

Examples

Author: Michele M. Burlew

Publisher: SAS Institute

The annotated example SAS programs in this book can be used as code models for many of the most common tasks of combining and modifying data in the SAS environment. The book begins with a brief overview of issues and techniques in SAS data set I/O.

Editions

1 Paperback (1995)

2 Paperback (2009)

2 Paperback

Year: 2009

ISBN: 978-1-59047-920-9

Pages: 332

Publisher’s list price: 48.95

Contents

• 1. Introducing Data Relationships, Techniques for Data Manipulation, and Access Methods
• 2. Combining Data Sets Vertically: Concatenating, Interleaving, and Appending Data Sets
• 3. Combining Data Sets Horizontally: Match-Merging Data Sets by Value
• 4. Using Lookup Tables to Match Data
• 5. Combining Summary and Detail Data
• 6. Updating Data Sets by Match-Merging by Value
• 7. Modifying Data Sets in Place
• 8. Manipulating Data From a Single Source
• 9. Manipulating Data with Utilities and Functions
• Index

1 Paperback

Author: SAS (technical reference)

Publisher: SAS Publishing

Year: 1995

ISBN: 1-55544-220-X

Pages: 197

Publisher’s list price: 26.95

Contents

• 1. An Introduction to Data Relationships, Access Methods, and Techniques for Data Manipulation
• 2. Combining Single Observations With Single Observations
• 3. Combining a Single Observation With Multiple Observations
• 4. Combining Multiple Observations With Multiple Observations
• 5. Manipulating Data From a Single Source
• 6. Utilities and Functions
• Appendix. Error Checking When Using MODIFY or SET With KEY=
• Index

From the back cover

Combining and Modifying SAS Data Sets: Examples provides solutions for common tasks involving reshaping or combining SAS data sets. You can save programming hours by using these programs as a model for developing your own.

Discover efficient ways to

• concatenate SAS data sets
• interleave SAS data sets
• match-merge SAS data sets
• update SAS data sets
• remove, add, or update observations
• use error checking to protect data integrity when combining or modifying data sets
• use BY-group processing effectively
• retrieve information by performing table lookups.

In addition, examples demonstrate basic tasks such as converting a variable’s type, working with character strings, and working with SAS time and date values, among others.