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/*
SAS workshop 1.sas, March 2007*/ /*
use of colons The
colon has several uses in SAS, all of them worth knowing about. 1 In a “name prefix list” of
variables In
contexts where a list of variables is required, the colon is a wildcard
character denoting any number
of characters up the end of the variable name e.g.*/ keep
w: ; drop
tmp: ; /*respectively
keep all variables whose names begin with “w”, and drop all variables who names
begin with “tmp”. 2 As an operator modifier The
colon behaves in a similar spirit when modifying operators used in comparing
character variables, for
example:*/ if
string =: 's' then put 'Begins
with "s"'; if
string in: ('r','s','t')
then put 'Begins with "r", "s" or
"t"' ; if
string >=: 's' then put 'Begins
with "s" or a later letter' ; /*
3 As an input format
modifier The
colon means “start reading at the next non-blank column” e.g.*/ data
_null_; infile
cards truncover; input
name :$20. value :2.; cards; rob 23 koon 54 sonja
9 ; run; /*4 As an output format modifier The
colon means “take as much space as you need and no more”. So for example: put name :$20 value 2.; strips
both leading and trailing blanks from NAME, and leaves a single space before
printing the numeric VALUE. It’s
a bit like using the CATX function. 5 For creating a macro variable in PROC SQL For
example, this code creates a macro variable WDSCOUNT containing a count of data
sets in the WORK library:*/ proc
sql; select
count(*) into :wdscount fromdictionary.tables where
libname='WORK' and
memtype='DATA'; quit; data
_null_; put
"Currently &wdscount datasets in WORK library."; run;
/************/ /* proc sql */ /************/ /*
comments - inline versus quoted you can comment a highlighted block with Ctrl
/ and uncomment it with Ctrl Shift / */ proc
sql; create
table temp; quit; /* to spit out
records which have a repeated key, here are two methods - */ proc
sql; create
table duplicates as select
blah from
datasets group by
key having count(key)
> 1; quit; /*
using where on output datasets */ proc
summary data=sasuser.houses; class
style street; var
_numeric_; output
sum= out=temp(where=(_type_
in (1,3))); run; /*You
can use SQL functions to summarize data. PROC SQL is more intuitive than PROC
MEANS or PROC SUMMARY, which result in an output table containing more rows and
columns than you need and you have to choose the right _TYPE_ value. The
PROC SQL below summarizes the total number of cases by age group for each year. */ proc
sql; SELECT
year, agegrp, SUM(count) AS cases FROM
stud08.ages GROUP
BY 1,2; quit; |
/*
SAS workshop 2.sas proc sql and proc datasets
*/ /****************************** Program title Author **************************/
set
deet07.dx2007; if
0 <= _N_ <= 1000
then output en1; else
if 1000
< _N_ <= 2000 then
output en2; else
if 2000
< _N_ <= 3000 then
output en3; run; /*
1. list contents of last dataset used, en3 */ proc
contents data=
_LAST_; run; /*
2. list contents of all datasets in the work library */ proc
contents data=work._ALL_; run; /*
3. list datasets in the work library */ proc
contents data=work._ALL_
nods; run; /*
4. proc datasets version of above - list
all datasets in the specified library */ proc
datasets library=work; quit;
run; /*
5. describe a single dataset */ proc
datasets library=work; contents
data=en1; quit;
run; /*
6. describe all work datasets */ proc
datasets; contents
data=_ALL_; quit;
run; /*
7. copy all datasets in work to stud07, excluding e3*/ proc
datasets; copy
in=work out=stud07; exclude
e3; quit;
run; /*
8. delete everything in work (deletes datasets and formats) */ proc
datasets library=work
kill; quit;
run; /*
9. delete just the datasets */ proc
datasets library=work
memtype=data kill; quit;
run; /*
10. move all datasets except en3 from stud07 to work */ proc
datasets; copy move
in=stud07 out=work; exclude
en3; quit;
run; /*
11. move just one dataset from stud07 to work */ proc
datasets; copy
move in=stud07 out=work; select
en3; quit;
run; /*
12. delete an individual dataset */ proc
datasets library=work; delete
en3; quit;
run; /*
13. change the name of a dataset */ proc
datasets library=work; change
en2=en4; quit;
run; /*
14. append datasets - note this is quicker than using a set command, as only
the appended dataset is read in */ proc
datasets library=work; append
out=en4 data=en1; quit;
run; /*
15. rename a variable */ proc
datasets library=work
NOlist; modify
en1; rename
student=personid course = course_cd; run;
quit; /*
PROC SQL */ proc
sql; select
* from
deet07.en2007 as en where
course like '10%'; quit; /*
an alternative to a proc summary */ proc
sql; create
table ensum as select
course, sex, sum(eftsu) as load from
deet07.en2007 group by
1,2; quit; /*
find units with between 1 and 5 enrolments */ proc
sql; create
table small_enrols as select
max(unit) as unit, count(student) as
enrols from
deet07.ld2007 group by
unit having count(student) < 6 order
by unit; quit; /*
an sql version of nodupkey */ proc
sql; select
distinct(course) from
deet07.en2007; quit; /*
joins */ /*
this is an inner join */ proc
sql; select
* from
deet07.en2007 en, deet07.ld2007 ld where
en.student = ld.student and
en.course = ld.course and
en.course like '1012%'; quit; /*
can more explicitly write it as .. */ proc
sql; create
table test as
select
* from
deet07.en2007 en left join deet07.ld2007 ld on
(en.student = ld.student and
en.course = ld.course) where
en.course like '1012%'; quit; /*
full join is where all records are included, including missing records from
left and right */ /*
left join includes all records from the left */ |
