Tables

Click on a button corresponding to a SAS data set table utility . These utilities can be grouped into four major purposes: inspection, consolidation, reduction, and reversible reorganization. A multi-purpose DATA STEP utility is also available.

The

Column Contents process is an excellent way to quickly view all or part of a data set, and obtain a high-level summary along with detailed variable attributes. It can also be used in planning for, and verifying the outcome of, other utilities.

Consolidation operation	Process	Choose this process for...
Row wise	Append	Appending the rows of one SAS data set to the end of another SAS data set to generate one rowwise concatenated SAS data set.
Column wise	Merge	Joining two data sets, side by side, with matching row variables.
Merge and Transform	Joining two data sets, side by side, with matching row variables, while simultaneously transforming data.

Consolidation operation

Process

Choose this process for...

Row wise

Append

Appending the rows of one SAS data set to the end of another SAS data set to generate one rowwise concatenated SAS data set.

Column wise

Merge

Joining two data sets, side by side, with matching row variables.

Merge and Transform

Joining two data sets, side by side, with matching row variables, while simultaneously transforming data.

Using the

Subset utility, a data set can be subsetted based on observation filter criteria and variables to drop . Therefore, both rows and columns can be reduced in the output subset data set.

Processes for reversible stacking and transposition of tables are available. They are outlined below.

Reorganization criterion	Process	Choose this process for...
Stackedness	Stack	Converting a tall SAS data set and Experimental Design Data Set (EDDS) into a stacked SAS data set where all observations of interest are placed in a single column.
Unstack	Converting a stacked SAS data set into a tall SAS data set and corresponding EDDS.
Subset	Subset	Subsets an input data set based on the criteria specified by up to four different filters.
Tall or wide transposition (see Tall and Wide Data Sets ) with the use of an EDDS	Transpose Tall to Wide	Converting a tall SAS data set (samples as columns, molecular entity as rows) and EDDS into a wide SAS data set (samples as rows, molecular entity as columns).
Transpose Wide to Tall	Converting a wide SAS data set (samples as rows, molecular entity as columns) into a tall SAS data set (samples as columns, molecular entity as rows) and EDDS.
General transposition of columns and rows without the use of an EDDS	Transpose Rectangular	Transposing a general SAS data set (without regard to an EDDS). This reversible process is not tall - or wide -specific.

Reorganization criterion

Process

Choose this process for...

Stackedness

Stack

Converting a tall SAS data set and Experimental Design Data Set (EDDS) into a stacked SAS data set where all observations of interest are placed in a single column.

Unstack

Converting a stacked SAS data set into a tall SAS data set and corresponding EDDS.

Subset

Subsets an input data set based on the criteria specified by up to four different filters.

Tall or wide transposition (see Tall and Wide Data Sets ) with the use of an EDDS

Transpose Tall to Wide

Converting a tall SAS data set (samples as columns, molecular entity as rows) and EDDS into a wide SAS data set (samples as rows, molecular entity as columns).

Transpose Wide to Tall

Converting a wide SAS data set (samples as rows, molecular entity as columns) into a tall SAS data set (samples as columns, molecular entity as rows) and EDDS.

General transposition of columns and rows without the use of an EDDS

Transpose Rectangular

Transposing a general SAS data set (without regard to an EDDS).

This reversible process is not tall - or wide -specific.

A very general mechanism for performing ad hoc manipulations and modifications on a SAS data set is available in the

DATA Step process.

Caution : This process requires knowledge of SAS DATA Step and other commands. Please refer to Base SAS documentation ( http://support.sas.com/documentation/ ) for more information. You should not attempt to use this process unless you have some experience with SAS programming.