How to create a comma separated file (.csv) of a SAS dataset?

IN SAS programming, we often require outputting the dataset in different formats like EXCEL and CSV etc and here are the five different ways to export the SAS dataset into .csv file.

Example:

data new ;
infile datalines dsd dlm=' ' missover;
input a b c d;

datalines;
3 5 1 1
4 1 . .
5 8 3 2
6 0 4 4
;
run;

By putting MISSOVER in the infile statement we are telling SAS to do not look for the data in the next lane if it runs out of the data, instead keep missing values for any remaining variables.

DSD and DLM options should be included always in the infile statement, if we include the
dlm=’ ‘ in the infile statement then SAS will put one digit for each variable even though we haven’t assigned any length to variable.

DSD option will tell SAS to consider a missing value if 2 delimiters are present side by side in any observation.

When we ran the above program in SAS, we create a SAS dataset name ‘NEW’ in the work directory and if we want to create a .csv file of dataset ‘NEW’ here are the 5 different ways to do it:

1)Here is the simplest method and least known method to create the .CSV file of a dataset; Using the DEXPORT statement.

Here is the syntax:

dm "dexport new 'H:\abccompany\client\Programs\Analysis\project1\class.csv' ";

When we submit the above code, SAS will automatically create a .CSV file in specified location path.


2) .CSV file can also be created using the PROC EXPORT procedure:
Here is the syntax:

proc export data=new
outfile=" H:\abccompany\client\Programs\Analysis\project1\class.csv ";
run;

3) By using the ODS and the Proc print we will be able to create a .CSV file of SAS dataset.

Here is the way to do it;

ods csv file= ‘H:\abccompany\client\Programs\Analysis\project1\class.csv ';

proc print data = new noobs;
run;
ods trace on;
ods csv close;

By keeping ODS trace on; statement we are telling SAS no to print the results in the output window, because, we are only creating the .csv file.

NOOBS option is required here, because PROC PRINT by default will create a new variable called 'OBS' and since we don't require it, we should include the NOOBS option.

4) File statement can also be useful in creating the .csv file of a SAS dataset.
Here is the way to do it.

data _null_;
file " H:\abccompany\client\Programs\Analysis\project1\class.csv ";

set new;
put (_all_) (',');
run;

5)b) Another way using the file statement:

filename csv ‘H:\abccompany\client\Programs\Analysis\project1\class.csv';

data _null_;
set new ;
file csv dlm=',';
put ( _all_ ) (+0);
run;

If we don’t mention the PUT( _all_), SAS will not keep all the variables in the .CSV file and even if we include put (_all_) the log will say:

ERROR 79-322: Expecting a (.

ERROR 76-322: Syntax error, statement will be ignored.

Because SAS is expecting a second parentheses here to follow the first one immediately and if we just only put the closed parenthesis to get rid of the previous error,
put (_all_) ( ) ;

We will get another error, because SAS we haven’t set any specifications for the PUT statement in the 2nd parenthesis.

So we can use a do-nothing pointer control (+0) to be error free.

Import CSV files and create SAS data sets on the fly!

How to Import Excel files into SAS

Reading from Excel Spreadsheets:
Microsoft Excel spreadsheets can be read from SAS in several ways. Two of these will be demonstrated here. First, PROC IMPORT allows direct access to Excel files through SAS/Access to PC File Formats or access to Comma-Separated (CSV) files through Base SAS. The second method uses the Excel LIBNAME engine.

PROC IMPORT
The IMPORT procedure reads from external sources and creates a SAS data set. Two sources are Excel spreadsheets and CSV files. A particular SAS/Access product may be required for certain sources, however. In our example, SAS/Access to PC File Formats is required to read an Excel file, but a CSV file can be accessed with Base SAS.

General Syntax for PROC IMPORT:

PROC IMPORT DATAFILE="c:\sas\ego.csv" OUT=jeeshim.egov DBMS=CSV REPLACE;For Excel you use the DATAFILE=”filename” option to specify the Excel file to be read. (The TABLE=”tablename” option would be applicable if you were reading from a database such as Microsoft Access.)

GETNAMES=YES;
DATAROW=2;
RUN;


The OUT= option specifies the SAS data set to be created. The DBMS= option identifies the type of file to be read. In this case, you will use either EXCEL or CSV to read an Excel spreadsheet or CSV file, respectively. Finally, the REPLACE option determines whether to replace the data set that is created, if it already exists.


read more at Reading from Excel Spreadsheets

Learning SAS

THE SPECIAL “??” FORMAT MODIFIER

The following excerpt is from SAS OnlineDoc documentation:

? or ??

Direct link: http://www.nesug.org/Proceedings/nesug01/at/at1013.pdf

The optional question mark (?) and double question mark (??) format modifiers suppress the printing of both the error messages and the input lines when invalid data values are read. The ? modifier suppresses the invalid data message. The ?? modifier also suppresses the invalid data message and, in addition, prevents the automatic variable _ERROR_ from being set to 1 when invalid data are read.

Below is an example of using ?? to determine whether a variable contains non-numeric values or not:

data _null_;
x = “12345678”;
if (input(x, ?? 8.) eq .) then
put ‘non-numeric’;
else put ‘numeric’;
run;

Running SAS would return “Numeric” in the above example. If we used X=”123a5678”, SAS would return “Non-Numeric”. Note that the input format in the above example is “8.” So only the first 8 bytes of the character string are checked.

Thus, X=123456789a would return “Numeric” as it would only be checking the first 8 bytes of the string.

 

 

I found an  interesting tip about suppressing the invalid data note and/or error message when reading in formatted data while surfing on the net.... (Source : Queensland Users Exploring SAS Technology)

 

Tips & Techniques - #3

Q: Is there a way to suppress the invalid data note and/or error message when reading in formatted data?

A:

􀂄Use the Format Modifiers ? or ?? on the input statement (or input function)

􀂄? –suppresses printing the invalid data note when SAS encounters invalid data values.

􀂄??––suppresses printing the messages and the input lines when SAS encounters invalid data values. The automatic variable _ERROR_ is not set to 1 for the invalid observation.

􀂄For example:

input x ?? 10 10-12;


Is the same as:


input x ? 10 10-12;


_error_=0;

PROC SQL basics, tips and techniques and sample code programs

Proc SQL:


Power of SAS SQL:

• SQL looks at datasets differently from SAS
– SAS looks at a dataset one record at a time, using an implied loop that moves from the first record to the last
– SQL looks at all the records, as a single object
• Because of this difference SQL can easily do few things that are more difficult to do in SAS
• There are a number of built in functions in SQL that can be used in a select statement
• Because of how SQL handles a dataset, these functions work over the entire dataset
• Functions:

– Count: Counts Values
– Sum: Sums Values
– Max: Identifies the largest value
– Min: Identifies the smallest value
– Mean: Averages the values

Read more at www.cognigencorp.com/perspective/tipsNtricks.pub/1/PROC%20SQL%20Talk_12_.ppt –

SAS SQL

Introduction to Proc SQL

AN INTRODUCTION TO PROC SQL®

PROC SQL: When and How to Use It?

Proc SQL – A Primer for SAS Programmers

Understanding PROC SQL

Creating Macro Variables with Proc SQL

DATA Step vs. PROC SQL: What’s a neophyte to do?


Effective Use of SQL in SAS Programming

Variable List Short-Cuts in PROC SQL

Ten Best PROC SQL Tips and Techniques

Undocumented and Hard-to-Find PROC SQL C2 AE_Features

Variable List Short-Cuts in PROC SQL

Exploring the World of PROC SQL® Joins

Using PROC SQL to Create Ad Hoc Reports

CREATING MACRO VARIABLES VIA PROC SQL

PROC SQL for DATA Step Die-hards

Calculating Changes and Differences Using PROC SQL —With Clinical Data Examples

Validating Data Via PROC SQL

Length of Numeric variables GT 8 in SAS| StudySAS BLOG

Q&A: numeric variables length more than 8? We all know that the default length of the numeric variables in SAS is 8 and if suppose I want to store a number lets say (12345678910, which has a length 11 to numeric variable) to variable total, what should I do?


What if the numeric variable digits are more than 12 digits and i want to store them all without any E values?

ANS)

The default length of numeric variables in SAS is 8 and all the numbers that we see in the sas datasets are called as floating numbers(floating point binary) and not a regular sequence numbers form 1 to 10. When we are using SAS/Windows as our operating system and then the minimum length for any numeric variable should be 3(not 1 as we get confused all the time). So if a variable contas less than 3 digits means it is stored with less space.

The reason is, since a numeric variable will need a power and and the sign(+ or -), if SAS want to store a numberit defenitely needs a minimum of 3 bytes.

Depending upon the operating system we are using for SAS, the range for numeric variables can be 2 to 8 or 3 to 8.

Since the type of floating-point values is upto 16 decimal digits. we can store numbers upto 16(1234567891012234) total 16 digits for a numeric variable, but that can be possible if we use a format statement.

Ex:
data dsn;
a=1234567891012234;
format a best16.;run;

 If we open the output, we can see all the 16 digits were stored for the variable a exactly in the dataset dsn.

If the the value of numeric variable is upto 12 disgits we don't require to specify any formats, if it is more than 12 digits we have to mention specify the format statement. without it we will see error in the system log.

Options VALIDVARNAME=UPCASE

VALIDVARNAME= V7 UPCASE ANY

VALIDVARNAME= option is generally used in SAS whenever we want to control the SAS variable names in the dataset.

VALIDVARNAME= V7 UPCASE ANY

The default option will be VALIDVARNAME=V7 until we specify as UPPERCASE or ANY.

When we mention options VALIDVARNAME=V7, that means we are telling SAS to change the name of the Database column (etc EXCEL sheet column) to valid SAS name with certain rules keeping in mind.

Here are those rules that SAS needs to follow, when it changes the DBMS column name to valid SAS name.

Only 32 mixed case (lower or uppercase) characters are allowed in each variable.

Names should be starting with an underscore or an alphabet (either uppercase or lower case character).

Invalid characters in the DBMS column (ex. $) should be changed to underscores.

See the SAS Language Reference: Dictionary to get more details about the rules.

VALIDVARNAME=UPCASE
When we mention options VALIDVARNAME=UPPERCASE we are telling SAS to change the column name of the Database column to uppercase variables irrespective of type of variables in the DBMS column.


And whenever we want the same kind of characters in SAS dataset which are in the DBMS column (ex .(=) sign and the Asterisk(*) or the forward slash(\) we have to mention options

VALIDVARNAME=ANY
If we do, this will allows any characters which are in the DBMS column to be kept in the SAS dataset.

To understand the concept better here I am giving the example:

Example
The following example shows how the Pass-Through Facility works with
VALIDVARNAME=UPPERCASE.

options validvarname=uppercase;
proc sql;
connect to oracle as tables(user=USERID orapw=passward path=’INSTANCE’);
create table lab as
select lab_rslt, lab_test
from connection to oracle
(select "laboratory result$", "laboratory test$"
from DBMStable);
quit;

When we check the Output we observe that the variables in the DBMS column is changed to upper case as well as V7 (default option) converts those variables into UPPERCASE variables. Ex: " laboratory result$" becomes LAB_RSLT and " laboratory test$" becomes LAB_TEST.

How to merge data sets with a common variable?

Here is the simple way of merging the data sets with a common variable if the datasets has the same prefix name.

For example: col1-col10, dsn1-dsn 7 , or data1 to data10 with common variable of ID.

Considering we have 10 datsets and all of them having the same prefix data;

%macro mymerge (n);

data merged;
merge %do i = 1 % to &n;
data&i %end; ; /* this additional ';' is necessary, the first ';' is for the "%end", while the second ';' is for "Merge"*/;
by id;
run;
%mend;
%mymerge(10)