MODIFY

MODIFY

Replaces, deletes, and appends observations in an existing SAS data set in place; does not create an additional copy

Valid: in a DATA step

Category: File-handling

Type: Executable

Restriction: Cannot modify the descriptor portion of a SAS data set, such as adding a variable

Syntax
Arguments
Details
	Matching Access
	Duplicate BY Values
	Direct Access by Indexed Values
	Duplicate Index Values
	Direct (Random) Access by Observation Number
	Sequential Access
	Automatic Variable _IORC_ and the SYSRC Autocall Macro
	Writing Observations When MODIFY Is Used in a DATA Step
	Using MODIFY in a SAS/SHARE Environment
Comparisons
Input Data Set for Examples
Examples
	Example 1: Modifying All Observations
	Example 2: Modifying Observations Using a Transaction Data Set
	Example 3: Modifying Observations Located by Observation Number
	Example 4: Modifying Observations Located by an Index
	Example 5: Handling Duplicate Index Values
	Example 6: Controlling I/O
	Example 7: Replacing and Removing Observations and Writing Observations to Different SAS Data Sets
See Also

Syntax

MODIFY master-data-set <(data-set-option(s))> transaction-data-set <(data-set-option(s))>
<NOBS=variable> <END=variable> <UPDATEMODE=MISSINGCHECK|
NOMISSINGCHECK>;
BY by-variable;

MODIFY master-data-set <(data-set-option(s))> KEY=index </ UNIQUE> <NOBS=variable> <END=variable> ;

MODIFY master-data-set <(data-set-option(s))> <NOBS=variable> POINT=variable;

MODIFY master-data-set <(data-set-option(s))> <NOBS=variable> <END=variable>;

CAUTION:: Damage to the SAS data set can occur if the system terminates abnormally during a DATA step that contains the MODIFY statement.
Observations in native SAS data files may have incorrect data values, or the data file may become unreadable. DBMS tables that are referenced by views are not affected.

Note:

If you modify a password-protected data set, specify the password with the appropriate data set option (ALTER= or PW=) within the MODIFY statement, and not in the DATA statement. [cautionend]

Arguments

master-data-set

specifies the SAS data set that you want to modify.

Restriction:

This data set must also appear in the DATA statement.

Restriction:

For sequential and matching access, the master data set can be a SAS data file, a SAS/ACCESS view, an SQL view, or a DBMS engine for the LIBNAME statement. It cannot be a DATA step view or a passthrough view.

For random access using POINT=, the master data set must be a SAS data file or an SQL view that references a SAS data file.

For direct access using KEY=, the master data set can be a SAS data file or the DBMS engine for the LIBNAME statement. If it is a SAS file, it must be indexed and the index name must be specified on the KEY= option.

For a DBMS, the KEY= is set to the keyword DBKEY and the column names to use as an index must be specified on the DBKEY= data set option. These column names are used in constructing a WHERE expression that is passed to the DBMS.

transaction-data-set

specifies the SAS data set that provides the values for matching access. These values are the values that you want to use to update the master data set.

Restriction:

Specify this data set only when the DATA step contains a BY statement.

END=variable

creates and names a temporary variable that contains an end-of-file indicator.

Explanation:	The variable, which is initialized to zero, is set to 1 when the MODIFY statement reads the last observation of the data set being modified (for sequential access ) or the last observation of the transaction data set (for matching access ). It is also set to 1 when MODIFY cannot find a match for a KEY= value (random access ). This variable is not added to any data set.
Restriction:	Do not use this argument in the same MODIFY statement with the POINT= argument. POINT= indicates that MODIFY uses random access. The value of the END= variable is never set to 1 for random access.

KEY=index

names a simple or composite index of the SAS data file that is being modified. The KEY= argument retrieves observations from that SAS data file based on index values that are supplied by like-named variables in another source of information.

Default:	If the KEY= value is not found, the automatic variable _ERROR_ is set to 1, and the automatic variable _IORC_ receives the value corresponding to the SYSRC autocall macro's mnemonic _DSENOM. See Automatic Variable _IORC_ and the SYSRC Autocall Macro .
Restriction:	KEY= processing is different for SAS/ACCESS engines. See the SAS/ACCESS documentation for more information.
Tip:	Examples of sources for index values include a separate SAS data set named in a SET statement and an external file that is read by an INPUT statement.
Tip:	If duplicates exist in the master file, only the first occurrence is updated unless you use a DO-LOOP to execute a SET statement for the data set listed on the KEY=option for all duplicates in the master data set. If duplicates exist in the transaction data set, and they are consequtive, use the UNIQUE option to force the search for a match in the master data set to begin at the top of the index. Write an accumulation statement to add each duplicate transaction to the observation in master. Without the UNIQUE option, only the first duplicate transaction observation updates the master. If the duplicates in the transaction data set are not consecutive, the search begins at the beginning of the index each time, so that each duplicate is applied to the master. Write an accumulation statement to add each duplicate to the master.
See Also:	UNIQUE
Featured in:	Modifying Observations Located by an Index, Handling Duplicate Index Values, and Controlling I/O

NOBS=variable

creates and names a temporary variable whose value is usually the total number of observations in the input data set. For certain SAS views, SAS cannot determine the number of observations. In these cases, SAS sets the value of the NOBS= variable to the largest positive integer value available in the operating environment.

Explanation:	At compilation time, SAS reads the descriptor portion of the data set and assigns the value of the NOBS= variable automatically. Thus, you can refer to the NOBS= variable before the MODIFY statement. The variable is available in the DATA step but is not added to the new data set.
Tip:	The NOBS= and POINT= options are independent of each other.
Featured in:	Modifying Observations Located by Observation Number

POINT=variable

reads SAS data sets using random (direct) access by observation number. variable names a variable whose value is the number of the observation to read. The POINT= variable is available anywhere in the DATA step, but it is not added to any SAS data set.

Requirement:	When using the POINT= argument, include one or both of the following: a STOP statement programming logic that checks for an invalid value of the POINT= variable. Because POINT= reads only the specified observations, SAS cannot detect an end-of-file condition as it would if the file were being read sequentially. Because detecting an end-of-file condition terminates a DATA step automatically, failure to substitute another means of terminating the DATA step when you use POINT= can cause the DATA step to go into a continuous loop.
Restriction:	You cannot use the POINT= option with any of the following: BY statement WHERE statement WHERE= data set option transport format data sets sequential data sets (on tape or disk) a table from another vendor's relational database management system.
Restriction:	You can use POINT= with compressed data sets only if the data set was created with the POINTOBS= data set option set to YES, the default value.
Restriction:	You can use the random access method on compressed files only with SAS version 7 and beyond.
Tip:	If the POINT= value does not match an observation number, SAS sets the automatic variable _ERROR_ to 1.
Featured in:	Modifying Observations Located by Observation Number

UNIQUE

causes a KEY= search always to begin at the top of the index for the data file being modified.

Restriction:	UNIQUE can appear only with the KEY= option.
Tip:	Use UNIQUE when there are consecutive duplicate KEY= values in the transaction data set, so that the search for a match in the master data set begins at the top of the index file for each duplicate transaction. You must include an accumulation statement or the duplicate values overwrite each other causing only the last transaction value to be the result in the master observation.
Featured in:	Handling Duplicate Index Values

UPDATEMODE=MISSINGCHECK| UPDATEMODE=NOMISSINGCHECK

specifies whether missing variable values in a transaction data set are to be allowed to replace existing variable values in a master data set.

MISSINGCHECK: prevents missing variable values in a transaction data set from replacing values in a master data set. Special missing values, however, are the exception and replace values in the master data set even when MISSINGCHECK is in effect.
NOMISSINGCHECK: allows missing variable values in a transaction data set to replace values in a master data set by preventing the check from being performed.

Default:

MISSINGCHECK

Details

Matching Access

The matching access method uses the BY statement to match observations from the transaction data set with observations in the master data set. The BY statement specifies a variable that is in the transaction data set and the master data set.

When the MODIFY statement reads an observation from the transaction data set, it uses dynamic WHERE processing to locate the matching observation in the master data set. The observation in the master data set can be either

replaced in the master data set with the value from the transaction data set
deleted from the master data set
appended to the master data set.

Modifying Observations Using a Transaction Data Set shows the matching access method.

Duplicate BY Values

Duplicates in the master and transaction data sets affect processing.

If duplicates exist in the master data set, only the first occurrence is updated because the generated WHERE statement always finds the first occurrence in the master.
If duplicates exist in the transaction data set, the duplicates are applied one on top of another unless you write an accumulation statement to add all of them to the master observation. Without the accumulation statement, the values in the duplicates overwrite each other so that only the value in the last transaction is the result in the master observation.

Direct Access by Indexed Values

This method requires that you use the KEY= option in the MODIFY statement to name an indexed variable from the data set that is being modified. Use another data source (typically a SAS data set named in a SET statement or an external file read by an INPUT statement) to provide a like-named variable whose values are supplied to the index. MODIFY uses the index to locate observations in the data set that is being modified.

Modifying Observations Located by an Index shows the direct-access-by-indexed-values method.

Duplicate Index Values

If there are duplicate values of the indexed variable in the master data set, only the first occurrence is retrieved, modified, or replaced. Use a DO LOOP to execute a SET statement with the KEY= option multiple times to update all duplicates with the transaction value.
If there are duplicate, nonconsecutive values in the like-named variable in the data source, MODIFY applies each transaction cumulatively to the first observation in the master data set whose index value matches the values from the data source. Therefore, only the value in the last duplicate transaction is the result in the master observation unless you write an accumulation statement to accumulate each duplicate transaction value in the master observation.
If there are duplicate, consecutive values in the variable in the data source, the values from the first observation in the data source are applied to the master data set, but the DATA step terminates with an error when it tries to locate an observation in the master data set for the second duplicate from the data source. To avoid this error, use the UNIQUE option in the MODIFY statement. The UNIQUE option causes SAS to return to the top of the master data set before retrieving a match for the index value. You must write an accumulation statement to accumulate the values from all the duplicates. If you do not, only the last one applied is the result in the master observation.
Handling Duplicate Index Values shows how to handle duplicate index values.
If there are duplicate index values in both data sets, you can use SQL to apply the duplicates in the transaction data set to the duplicates in the master data set in a one-to-one correspondence.

Direct (Random) Access by Observation Number

You can use the POINT= option in the MODIFY statement to name a variable from another data source (not the master data set), whose value is the number of an observation that you want to modify in the master data set. MODIFY uses the values of the POINT= variable to retrieve observations in the data set that you are modifying. (You can use POINT= on a compressed data set only if the data set was created with the POINTOBS= data set option.)

It is good programming practice to validate the value of the POINT= variable and to check the status of the automatic variable _ERROR_.

Modifying Observations Located by Observation Number shows the direct (random) access by observation number method.

CAUTION:: POINT= can result in infinite looping. Be careful when you use POINT=, as failure to terminate the DATA step can cause the DATA step to go into a continuous loop. Use a STOP statement, programming logic that checks for an invalid value of the POINT= variable, or both.

Sequential Access

The sequential access method is the simplest form of the MODIFY statement, but it provides less control than the direct access methods. With the sequential access method, you may use the NOBS= and END= options to modify a data set; you do not use the POINT= or KEY= options.

Automatic Variable _IORC_ and the SYSRC Autocall Macro

The automatic variable _IORC_ contains the return code for each I/O operation that the MODIFY statement attempts to perform. The best way to test for values of _IORC_ is with the mnemonic codes that are provided by the SYSRC autocall macro. Each mnemonic code describes one condition. The mnemonics provide an easy method for testing problems in a DATA step program. These codes are useful:

_DSENMR: specifies that the transaction data set observation does not exist on the master data set (used only with MODIFY and BY statements). If consecutive observations with different BY values do not find a match in the master data set, both of them return _DSENMR.
_DSEMTR: specifies that multiple transaction data set observations with a given BY value do not exist on the master data set (used only with MODIFY and BY statements). If consecutive observations with the same BY values do not find a match in the master data set, the first observation returns _DSENMR and the subsequent observations return _DSEMTR.
_DSENOM: specifies that the data set being modified does not contain the observation that is requested by the KEY= option or the POINT= option.
_SENOCHN: specifies that SAS is attempting to execute an OUTPUT or REPLACE statement on an observation that contains a key value which duplicates one already existing on an indexed data set that requires unique key values.
_SOK: specifies that the observation was located.

Note: Beginning in Version 7, the IORCMSG function returns a formatted error message associated with the current value of _IORC_. [cautionend]

Controlling I/O shows how to use the automatic variable _IORC_ and the SYSRC autocall macro.

Writing Observations When MODIFY Is Used in a DATA Step

The way SAS writes observations to a SAS data set when the DATA step contains a MODIFY statement depends on whether certain other statements are present. The possibilities are

no explicit statement: writes the current observation to its original place in the SAS data set. The action occurs as the last action in the step (as though a REPLACE statement were the last statement in the step).
OUTPUT statement: if no data set is specified in the OUTPUT statement, writes the current observation to the end of all data sets that are specified in the DATA step. If a data set is specified, the statement writes the current observation to the end of the data set that is indicated. The action occurs at the point in the DATA step where the OUTPUT statement appears.
REPLACE <data-set-name> statement: rewrites the current observation in the specified data set(s), or, if no argument is specified, rewrites the current observation in each data set specified on the DATA statement. The action occurs at the point of the REPLACE statement.
REMOVE <data-set-name> statement: deletes the current observation in the specified data set(s), or, if no argument is specified, deletes the current observation in each data set specified on the DATA statement. The deletion may be a physical one or a logical one, depending on the characteristics of the engine that maintains the data set.

Keep in mind the following as you work with these statements:

When no OUTPUT, REPLACE, or REMOVE statement is specified, the default action is REPLACE.
The OUTPUT, REPLACE, and REMOVE statements are independent of each other. More than one statement can apply to the same observation, as long as the sequence is logical.
Using OUTPUT, REPLACE, or REMOVE in a DATA step overrides the default replacement of observations. If you use any one of these statements in a DATA step, you must explicitly program each action that you want to take.
If both an OUTPUT statement and a REPLACE or REMOVE statement execute on a given observation, perform the OUTPUT action last to keep the position of the observation pointer correct.

Replacing and Removing Observations and Writing Observations to Different SAS Data Sets shows how to use the OUTPUT, REMOVE, and REPLACE statements to write observations.

Using MODIFY in a SAS/SHARE Environment

In a SAS/SHARE environment, the MODIFY statement accesses an observation in update mode. That is, the observation is locked from the time MODIFY reads it until a REPLACE or REMOVE statement executes. At that point the observation is unlocked. It cannot be accessed until it is re-read with the MODIFY statement. The MODIFY statement opens the data set in update mode, but the control level is based on the statement used. For example, KEY= and POINT= are member-level locking. Refer to SAS/SHARE User's Guide for more information.

Comparisons

When you use a MERGE, SET, or UPDATE statement in a DATA step, SAS creates a new SAS data set. The data set descriptor of the new copy can be different from the old one (variables added or deleted, labels changed, and so on). When you use a MODIFY statement in a DATA step, however, SAS does not create a new copy of the data set. As a result, the data set descriptor cannot change.
For information on DBMS replacement rules, see the SAS/ACCESS documentation.
If you use a BY statement with a MODIFY statement, MODIFY works much like the UPDATE statement, except that
- neither the master data set nor the transaction data set needs to be sorted or indexed. (The BY statement that is used with MODIFY triggers dynamic WHERE processing.)
  Note: Dynamic WHERE processing can be costly if the MODIFY statement modifies a SAS data set that is not in sorted order or has not been indexed. Having the master data set in sorted order or indexed and having the transaction data set in sorted order reduces processing overhead, especially for large files.
- both the master data set and the transaction data set can have observations with duplicate values of the BY variables. MODIFY treats the duplicates as described in Duplicate BY Values.
- MODIFY cannot make any changes to the descriptor information of the data set as UPDATE can. Thus, it cannot add or delete variables, change variable labels, and so on.

Input Data Set for Examples

The examples modify the INVTY.STOCK data set. INVTY.STOCK contains these variables:

PARTNO: is a character variable with a unique value identifying each tool number.
DESC: is a character variable with the text description of each tool.
INSTOCK: is a numeric variable with a value describing how many units of each tool the company has in stock.
RECDATE: is a numeric variable containing the SAS date value that is the day for which INSTOCK values are current.
PRICE: is a numeric variable with a value that describes the unit price for each tool.

In addition, INVTY.STOCK contains a simple index on PARTNO. This DATA step creates INVTY.STOCK:

libname invty 'SAS-data-library';

options yearcutoff= 1920;

data invty.stock(index=(partno));
   input PARTNO $ DESC $ INSTOCK @17 
         RECDATE date7. @25 PRICE;
   format  recdate date7.;
   datalines;
K89R seal   34  27jul95 245.00
M4J7 sander 98  20jun95 45.88
LK43 filter 121 19may96 10.99
MN21 brace 43   10aug96 27.87
BC85 clamp 80   16aug96 9.55
NCF3 valve 198  20mar96 24.50
KJ66 cutter 6   18jun96 19.77
UYN7 rod  211   09sep96 11.55
JD03 switch 383 09jan97 13.99
BV1E timer 26   03jan97 34.50
;

Examples

Example 1: Modifying All Observations

This example replaces the date on all records in the data set INVTY.STOCK with the current date. This code replaces the value of the variable RECDATE with the current date for all observations in INVTY.STOCK:

data invty.stock;
   modify invty.stock;
   recdate=today();
run;

A printing of INVTY.STOCK shows that RECDATE has been modified:

INVTY.STOCK 1 PARTNO DESC INSTOCK RECDATE PRICE K89R seal 34 14MAR97 245.00 M4J7 sander 98 14MAR97 45.88 LK43 filter 121 14MAR97 10.99 MN21 brace 43 14MAR97 27.87 BC85 clamp 80 14MAR97 9.55 NCF3 valve 198 14MAR97 24.50 KJ66 cutter 6 14MAR97 19.77 UYN7 rod 211 14MAR97 11.55 JD03 switch 383 14MAR97 13.99 BV1E timer 26 14MAR97 34.50

The MODIFY statement opens INVTY.STOCK for update processing. SAS reads one observation of INVTY.STOCK for each iteration of the DATA step and performs any operations that the code specifies. In this case, the code replaces the value of RECDATE with the result of the TODAY function for every iteration of the DATA step. An implicit REPLACE statement at the end of the step writes each observation to its previous location in INVTY.STOCK.

Example 2: Modifying Observations Using a Transaction Data Set

This example adds the quantity of newly received stock to its data set INVTY.STOCK as well as updating the date on which stock was received. The transaction data set ADDINV in the WORK library contains the new data.

The ADDINV data set is the data set that contains the updated information. ADDINV contains these variables:

PARTNO: is a character variable that corresponds to the indexed variable PARTNO in INVTY.STOCK.
NWSTOCK: is a numeric variable that represents quantities of newly received stock for each tool.

ADDINV is the second data set in the MODIFY statement. SAS uses it as the transaction data set and reads each observation from ADDINV sequentially. Because the BY statement specifies the common variable PARTNO, MODIFY finds the first occurrence of the value of PARTNO in INVTY.STOCK that matches the value of PARTNO in ADDINV. For each observation with a matching value, the DATA step changes the value of RECDATE to today's date and replaces the value of INSTOCK with the sum of INSTOCK and NWSTOCK (from ADDINV). MODIFY does not add NWSTOCK to the INVTY.STOCK data set because that would modify the data set descriptor. Thus, it is not necessary to put NWSTOCK in a DROP statement.

This example specifies ADDINV as the transaction data set that contains information to modify INVTY.STOCK. A BY statement specifies the shared variable whose values locate the observations in INVTY.STOCK.

This DATA step creates ADDINV:

data addinv;
   input PARTNO $ NWSTOCK;
   datalines;
K89R 55
M4J7 21
LK43 43
MN21 73
BC85 57
NCF3 90
KJ66 2
UYN7 108
JD03 55
BV1E 27
;

This DATA step uses values from ADDINV to update INVTY.STOCK.

libname invty 'SAS-data-library';

data invty.stock;
   modify invty.stock addinv;
   by partno;
   RECDATE=today();
   INSTOCK=instock+nwstock;
   if _iorc_=0 then replace;
run;

A printing of INVTY.STOCK shows that INSTOCK and RECDATE have been modified:

INVTY.STOCK 1 PARTNO DESC INSTOCK RECDATE PRICE K89R seal 89 14MAR97 245.00 M4J7 sander 119 14MAR97 45.88 LK43 filter 164 14MAR97 10.99 MN21 brace 116 14MAR97 27.87 BC85 clamp 137 14MAR97 9.55 NCF3 valve 288 14MAR97 24.50 KJ66 cutter 8 14MAR97 19.77 UYN7 rod 319 14MAR97 11.55 JD03 switch 438 14MAR97 13.99 BV1E timer 53 14MAR97 34.50

Example 3: Modifying Observations Located by Observation Number

This example reads the data set NEWP, determines which observation number in INVTY.STOCK to update based on the value of TOOL_OBS, and performs the update. This example explicitly specifies the update activity by using an assignment statement to replace the value of PRICE with the value of NEWP.

The data set NEWP contains two variables:

TOOL_OBS: contains the observation number of each tool in the tool company's master data set, INVTY.STOCK.
NEWP: contains the new price for each tool.

This DATA step creates NEWP:

data newp;
   input TOOL_OBS NEWP;
   datalines;
 251.00
2 49.33
3 12.32
4 30.00
5 15.00
6 25.75
7 22.00
8 14.00
9 14.32
0 35.00
;

This DATA step updates INVTY.STOCK:

libname invty 'SAS-data-library';

data invty.stock;
   set newp;
   modify invty.stock point=tool_obs
          nobs=max_obs;
   if _error_=1 then
      do;
        put 'ERROR occurred for TOOL_OBS=' tool_obs /
        'during DATA step iteration' _n_ /
        'TOOL_OBS value may be out of range.';
        _error_=0;
        stop;
      end;
   PRICE=newp;
   RECDATE=today();
run;

A printing of INVTY.STOCK shows that RECDATE and PRICE have been modified:

INVTY.STOCK 1 PARTNO DESC INSTOCK RECDATE PRICE K89R seal 34 14MAR97 251.00 M4J7 sander 98 14MAR97 49.33 LK43 filter 121 14MAR97 12.32 MN21 brace 43 14MAR97 30.00 BC85 clamp 80 14MAR97 15.00 NCF3 valve 198 14MAR97 25.75 KJ66 cutter 6 14MAR97 22.00 UYN7 rod 211 14MAR97 14.00 JD03 switch 383 14MAR97 14.32 BV1E timer 26 14MAR97 35.00

Example 4: Modifying Observations Located by an Index

This example uses the KEY= option to identify observations to retrieve by matching the values of PARTNO from ADDINV with the indexed values of PARTNO in INVTY.STOCK. ADDINV is created in Modifying Observations Using a Transaction Data Set.

KEY= supplies index values that allow MODIFY to access directly the observations to update. No dynamic WHERE processing occurs. In this example, you specify that the value of INSTOCK in the master data set INVTY.STOCK increases by the value of the variable NWSTOCK from the transaction data set ADDINV.

libname invty 'SAS-data-library';

data invty.stock;
   set addinv;
   modify invty.stock key=partno;
   INSTOCK=instock+nwstock;
   RECDATE=today();
   if _iorc_=0 then replace;
run;

A printing of INVTY.STOCK shows that INSTOCK and RECDATE have been modified.

Example 5: Handling Duplicate Index Values

This example shows how MODIFY handles duplicate values of the variable in the SET data set that is supplying values to the index on the master data set.

The NEWINV data set is the data set that contains the updated information. NEWINV contains these variables:

PARTNO: is a character variable that corresponds to the indexed variable PARTNO in INVTY.STOCK. The NEWINV data set contains duplicate values for PARTNO; M4J7 appears twice.
NWSTOCK: is a numeric variable that represents quantities of newly received stock for each tool.

This DATA step creates NEWINV:

data newinv;
   input PARTNO $ NWSTOCK;
   datalines;
K89R 55
M4J7 21
M4J7 26
LK43 43
MN21 73
BC85 57
NCF3 90
KJ66 2
UYN7 108
JD03 55
BV1E 27
;

This DATA step terminates with an error when it tries to locate an observation in INVTY.STOCK to match with the second occurrence of M4J7 in NEWINV:

libname invty 'SAS-data-library';

/* This DATA step terminates with an error! */
data invty.stock;
   set newinv;
   modify invty.stock key=partno;
   INSTOCK=instock+nwstock;
   RECDATE=today();
run;

This message appears in the SAS log:

ERROR: No matching observation was found in MASTER data set. PARTNO=K89R NWSTOCK=55 DESC= INSTOCK=. RECDATE=14MAR97 PRICE=. _ERROR_=1 _IORC_=1230015 _N_=1 NOTE: Missing values were generated as a result of performing an operation on missing values. Each place is given by: (Number of times) at (Line):(Column). 1 at 689:19 NOTE: The SAS System stopped processing this step because of errors. NOTE: The data set INVTY.STOCK has been updated. There were 0 observations rewritten, 0 observations added and 0 observations deleted.

Adding the UNIQUE option to the MODIFY statement avoids the error in the previous DATA step. The UNIQUE option causes the DATA step to return to the top of the index each time it looks for a match for the value from the SET data set. Thus, it finds the M4J7 in the MASTER data set for each occurrence of M4J7 in the SET data set. The updated result for M4J7 in the output shows that both values of NWSTOCK from NEWINV for M4J7 are added to the value of INSTOCK for M4J7 in INVTY.STOCK. An accumulation statement sums the values; without it, only the value of the last instance of M4J7 would be the result in INVTY.STOCK.

data invty.stock;
   set newinv;
   modify invty.stock key=partno / unique;
   INSTOCK=instock+nwstock;
   RECDATE=today();
   if _iorc_=0 then replace;
run;

A printing of INVTY.STOCK shows that INSTOCK and RECDATE have been modified:

Results of Using the UNIQUE Option 1 PARTNO DESC INSTOCK RECDATE PRICE K89R seal 89 14MAR97 245.00 M4J7 sander 145 14MAR97 45.88 LK43 filter 164 14MAR97 10.99 MN21 brace 116 14MAR97 27.87 BC85 clamp 137 14MAR97 9.55 NCF3 valve 288 14MAR97 24.50 KJ66 cutter 8 14MAR97 19.77 UYN7 rod 319 14MAR97 11.55 JD03 switch 438 14MAR97 13.99 BV1E timer 53 14MAR97 34.50

Example 6: Controlling I/O

This example uses the SYSRC autocall macro and the _IORC_ automatic variable to control I/O condition. This technique helps to prevent unexpected results that could go undetected. This example uses the direct access method with an index to update INVTY.STOCK. The data in the NEWSHIP data set updates INVTY.STOCK.

This DATA step creates NEWSHIP:

options yearcutoff= 1920; 

data newship;
   input PARTNO $ DESC $ NWSTOCK @17 
         SHPDATE date7. @25 NWPRICE;
   datalines;
K89R seal 14    14nov96 245.00
M4J7 sander 24  23aug96 47.98
LK43 filter 11  29jan97 14.99
MN21 brace 9    09jan97 27.87
BC85 clamp 12   09dec96 10.00
ME34 cutter 8   14nov96 14.50
;

Each WHEN clause in the SELECT statement specifies actions for each input/output return code that is returned by the SYSRC autocall macro:

_SOK indicates that the MODIFY statement executed successfully.
_DSENOM indicates that no matching observation was found in INVTY.STOCK. The OUTPUT statement specifies that the observation be appended to INVTY.STOCK. See the last observation in the output.
If any other code is returned by SYSRC, the DATA step terminates and the PUT statement writes the message to the log.

libname invty 'SAS-data-library';

data invty.stock;
   set newship;
   modify invty.stock key=partno;
   select (_iorc_);
      when (%sysrc(_sok)) do;
         INSTOCK=instock+nwstock;
         RECDATE=shpdate;
         PRICE=nwprice;
         replace;
      end;
      when (%sysrc(_dsenom)) do;
         INSTOCK=nwstock;
         RECDATE=shpdate;
         PRICE=nwprice;
         output;
         _error_=0;
      end;
      otherwise do;
         put
         'An unexpected I/O error has occurred.'/
         'Check your data and your program';
         _error_=0;
         stop;
       end;
   end;
run;

INVTY.STOCK Data Set 1 PARTNO DESC INSTOCK RECDATE PRICE K89R seal 48 14NOV96 245.00 M4J7 sander 122 23AUG96 47.98 LK43 filter 132 29JAN97 14.99 MN21 brace 52 09JAN97 27.87 BC85 clamp 92 09DEC96 10.00 NCF3 valve 198 20MAR96 24.50 KJ66 cutter 6 18JUN96 19.77 UYN7 rod 211 09SEP96 11.55 JD03 switch 383 09JAN97 13.99 BV1E timer 26 03JAN97 34.50 ME34 cutter 8 14NOV96 14.50

Example 7: Replacing and Removing Observations and Writing Observations to Different SAS Data Sets

This example shows that you can replace and remove (delete) observations and write observations to different data sets. Further, this example shows that if an OUTPUT, REPLACE, or REMOVE statement is present, you must specify explicitly what action to take because no default statement is generated.

The parts that were received in 1997 are output to INVTY.STOCK97 and are removed from INVTY.STOCK. Likewise, the parts that were received in 1995 are output to INVTY.STOCK95 and are removed from INVTY.STOCK. Only the parts that were received in 1996 remain in INVTY.STOCK, and the PRICE is updated only in INVTY.STOCK.

libname invty 'SAS-data-library';

data invty.stock invty.stock95 invty.stock97;
   modify invty.stock;
   if recdate>'01jan97'd then do;
       output invty.stock97;
       remove invty.stock;
   end;
   else if recdate<'01jan96'd then do;
       output invty.stock95;
       remove invty.stock;
   end;
   else do; 
      price=price*1.1;
      replace invty.stock;
   end; 
run;

New Prices for Stock Rcvd in '96 1 PARTNO DESC INSTOCK RECDATE PRICE LK43 filter 121 19MAY96 12.089 MN21 brace 43 10AUG96 30.657 BC85 clamp 80 16AUG96 10.505 NCF3 valve 198 20MAR96 26.950 KJ66 cutter 6 18JUN96 21.747 UYN7 rod 211 09SEP96 12.705

See Also

Statements:

OUTPUT

REMOVE

REPLACE

UPDATE

"Reading, Combining, and Modifying SAS Data Sets" in SAS Language Reference: Concepts

"SQL Procedure" in the SAS Procedures Guide

Chapter Contents
Previous
Next
Top of Page

Valid:	in a DATA step
Category:	File-handling
Type:	Executable
Restriction:	Cannot modify the descriptor portion of a SAS data set, such as adding a variable