- Copyright
- Acknowledgments
- About This Book
- Introducing Data Relationships, Techniques for Data Manipulation, and Access Methods
- Overview
- Determining Data Relationships
- Understanding the Methods for Combining SAS Data Sets
- Understanding Access Methods: Sequential versus Direct
- Understanding the Tools for Combining SAS Data Sets
- Understanding the Tools for Processing Information in Groups
- Choosing between the DATA Step and PROC SQL
- Choosing between MODIFY and UPDATE
- Combining Data Sets Vertically: Concatenating, Interleaving, and Appending Data Sets
- Example 2.1 Concatenating Data Sets
- Example 2.2 Interleaving Observations from Two or More Data Sets Based on a Common Variable
- Example 2.3 Appending One Data Set to the End of Another Data Set
- Example 2.4 Selecting Unique Rows When Concatenating Tables
- Example 2.5 Selecting Rows in Common When Concatenating Tables
- Example 2.6 Selecting Observations Unique to Each Data Set When Concatenating Data Sets
- Combining Data Sets Horizontally: Match-Merging Data Sets by Value
- Example 3.1 Merging Data Sets by a Common Variable
- Example 3.2 Merging Observations from Multiple Data Sets by a Common Variable
- Example 3.3 Combining Observations When Variable Values Do Not Match Exactly
- Example 3.4 Combining Observations by the Formatted Value of a Variable
- Example 3.5 Combining Multiple Tables When the Matching Column Has Different Attributes
- Example 3.6 Combining Rows When There Is No Common Column
- Example 3.7 Matching Observations Randomly
- Example 3.8 Combining Multiple Data Sets without a Variable Common to All the Data Sets
- Example 3.9 Generating Every Combination of Rows (Cartesian Product) between Tables
- Example 3.10 Generating Every Combination of Rows between Tables Based on a Common Column
- Example 3.11 Generating Every Combination of Observations between Data Sets Based on a Common Variable When an Index Is Available
- Example 3.12 Combining and Collapsing Observations Based on a Common Variable
- Example 3.13 Combining and Collapsing Observations Based on a Common Variable When the Transaction Data Set Is Indexed
- Example 4.1 Performing a Simple Table Lookup
- Example 4.2 Performing a Table Lookup in a Small Lookup Data Set
- Example 4.3 Performing a Table Lookup in a Large, Non-Indexed Lookup Data Set
- Example 4.4 Performing Multiple Lookups for Each Observation in a Data Set
- Example 4.5 Performing a Table Lookup When the Lookup Data Set Is Indexed
- Example 4.6 Performing a "Chained" Lookup
- Combining Summary and Detail Data
- Example 5.1 Adding Values to All Observations in a Data Set
- Example 5.2 Adding Values from the Last Observation in a Data Set to All Observations in a Data Set
- Example 5.3 Computing Summary Data and Combining Them with Detail Data
- Example 5.4 Subsetting a Table Based on the Calculated Average of a Group
- Example 5.5 Calculating Totals across a BY Group to Produce Cumulative and Grand Totals
- Example 5.6 Calculating Percentages and Statistics That One Row Contributes to a BY Group
- Updating Data Sets by Match-Merging by Value
- Example 6.1 Updating a Data Set and Controlling Whether Common Variables Are Overwritten with Missing Values
- Example 6.2 Updating a Data Set and Allowing Some Values to Be Updated with Missing Values
- Example 6.3 Merging Data Sets and Conditionally Overwriting Common Variables
- Example 6.4 Adding Observations and Variables to the Master Data Set When Duplicate Matching Variable Values Exist in the Transaction Data Set
- Example 6.5 Saving Observations from Only the Master Data Set When the Transaction Data Set Contains Duplicates
- Modifying Data Sets in Place
- Manipulating Data from a Single Source
- Example 8.1 Performing a Simple Subset
- Example 8.2 Separating Unique Observations from Duplicate Observations Based on BY Values
- Example 8.3 Separating Completely Duplicate Observations from Unique Observations
- Example 8.4 Separating the First Observation in a BY Group from the Other Observations in the BY Group
- Example 8.5 Accessing a Specific Number of Observations from the Beginning and End of a Data Set
- Example 8.6 Creating a Customized Sort Order without Adding a New Column to the Table
- Example 8.7 Adding New Observations to the End of a Data Set
- Example 8.8 Adding Observations to a Data Set Based on the Value of a Variable
- Example 8.9 Adding Observations to a SAS Data Set So the Values of a Variable Are Consecutive throughout the BY Group
- Example 8.10 Adding Rows to a Table So That All Possible Values of Specific Columns Are Present in Each BY Group
- Example 8.11 Expanding Single Observations into Multiple Observations
- Example 8.12 Collapsing Observations within a BY Group into a Single Observation
- Example 8.13 Obtaining the Previous Value of a Variable within a BY Group
- Example 8.14 Comparing the Value of a Variable to Its Value in the Next Observation
- Example 8.15 Applying the Same Operation to a Group of Variables
- Example 8.16 Obtaining Hierarchical Data from a Table and Matching Them to the Rows in the Same Table
- Example 8.17 Combining Generation Data Sets
- Manipulating Data with Utilities and Functions
- Example 9.1 Converting Variable Types from Character to Numeric and Vice Versa
- Example 9.2 Determining the Type of a Variable's Content
- Example 9.3 Determining Whether a Variable Is Character or Numeric
- Example 9.4 Specifying a Numeric or Character Format at Run Time
- Example 9.5 Creating Columns That Contain the Attributes of Other Columns
- Example 9.6 Sorting Variable Values within an Observation
- Example 9.7 Shifting Nonmissing Values Left in an Observation
- Example 9.8 Generating Random Numbers within a Range of Values
- Example 9.9 Selecting Observations at Random from a Data Set without Replacement
- Example 9.10 Selecting Equal-Sized Samples from Different Groups
- Example 9.11 Creating SAS Datetime Values and Computing the Difference between Two Datetime Values
- Example 9.12 Creating a SAS Time Value from a Character Value
- Example 9.13 Calculating a Person's Age
- Example 9.14 Incrementing a Date by an Interval
- Example 9.15 Determining the Number of U.S. Business Days between Two Dates
- Example 9.16 Counting the Occurrences of a String
- Example 9.17 Extracting a Character String without Breaking the Text in the Middle of a Word
- Example 9.18 Cleaning Character Data Values
- Example 9.19 Validating and Standardizing Complex Character Data
Purpose
Combining and Modifying SAS Data Sets: Examples, Second Edition is a book of examples that show you how to combine, modify, and reshape your SAS data sets. The chapters and examples are organized and titled by task. This structure makes it possible for you to find an example that solves a task similar to the one you need to solve and then adapt the code to your needs.
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