This is a newbie SAS question. I have a dataset with numerical variables v1-v120, V and a categorical variable Z(with say three possible values). For each possible value of Z, I would like to get another set of variables w1-w120, where w{i}=sum(v{i}}/V, where the sum is a sum over a given value of Z. Thus I am looking for 3*120 matrix in this case. I can do this in data step, but would like to do it by Proc SQL or Proc MEANS, as the number of categorical variables in the actual dataset is moderately large. Thanks in advance.
Here's a solution using proc sql. You could probably also do something similar with proc means using an output dataset and a 'by' statement.
data t1;
input z v1 v2 v3;
datalines;
1 2 3 4
2 3 4 5
3 4 5 6
1 7 8 9
2 4 7 9
3 2 2 2
;
run;
%macro listForSQL(varstem1, varstem2, numvars);
%local numWithCommas;
%let numWithCommas = %eval(&numvars - 1);
%local i;
%do i = 1 %to &numWithCommas;
mean(&varstem1.&i) as &varstem2.&i,
%end;
mean(&varstem1.&numvars) as &varstem2.&numvars
%mend listForSQL;
proc sql;
create table t2 as
select
z,
%listForSQL(v, z, 3)
from t1
group by z
;
quit;
It's easy to do this with proc means. Using the t1 data set from Louisa Grey's answer:
proc means data=t1 nway noprint;
class z;
var v1-v3;
output out=t3 mean=w1-w3;
run;
This creates an table of results that match the SQL results.
Related
Assume I have table foo which contains a (dynamic) list of new rows which I want to add to another table have, so that it yields a table want looking e.g. like this:
x y p_14 p_15
1 2 2 99
2 4 7 24
Example data for foo:
id row_name
14 p_14
15 p_15
Example data for have:
x y p Z
1 2 14 2
1 2 15 99
1 2 16 59
2 4 14 7
2 4 15 24
2 4 16 58
What I have so far is the following which is not yet in macro shape:
proc sql;
create table want as
select old.*, t1.p_14, t2.p_15 /* choosing non-duplicate rows */
from (select x, y from have) old
left join (select x, y, z as p_14 from have where p=14) t1
on old.x=t1.x and old.y=t1.y
left join (select x, y, z as p_15 from have where p=15) t2
on old.x=t2.x and old.y=t2.y
;
quit;
Ideally, I am aiming for a macro where which takes foo as input and automatically creates all the joins from above. Also, the solution should not spit out any warnings in the console. My challenge is how to dynamically choose the correct (non-duplicate) rows.
PS: This is a follow-up question of Populate SAS macro-variable using a SQL statement within another SQL statement? The important bit is that it is not a full transpose, I guess.
You can go from HAVE to WANT with PROC TRANSPOSE.
proc transpose data=have out=want(drop=_name_) prefix=p_ ;
by x y ;
id p ;
var z;
run;
To limit it to the values of P that occur in FOO you could use a macro variable (as long as the number of observations in FOO is small enough).
proc sql noprint ;
select id into :idlist separated by ' ' from foo ;
quit;
proc transpose data=have out=want(drop=_name_) prefix=p_ ;
where p in (&idlist) ;
by x y ;
id p ;
var z;
run;
If the issue is you want variable P_17 to be in the result even if 17 does not appear in HAVE then add a little more complexity. For example add another data step that will force the creation of the empty variables. You can generate the list of variable names from the list of id's in FOO.
proc sql noprint ;
select id , cats('p_',id)
into :idlist separated by ' '
, :varlist separated by ' '
from foo
;
quit;
proc transpose data=have out=want(drop=_name_) prefix=p_ ;
where p in (&idlist) ;
by x y ;
id p ;
var z;
run;
data want ;
set want (keep=x y);
array all &varlist ;
set want ;
run;
Results:
Obs x y p_14 p_15 p_17
1 1 2 2 99 .
2 2 4 7 24 .
If the number of values is too large to store in a single macro variable (limit 64K bytes) you could generate the WHERE statement with a data step to a file and use %INCLUDE to add the WHERE statement into the code.
filename where temp;
data _null_;
set foo end=eof;
file where ;
if _n_=1 then put 'where p in (' #;
put id # ;
if eof then put ');' ;
run;
proc transpose ... ;
%include where / source2;
...
Use macro program:
data have;
input x y p Z;
cards;
1 2 14 2
1 2 15 99
1 2 16 59
2 4 14 7
2 4 15 24
2 4 16 58
;
data foo;
input id row_name $;
cards;
14 p_14
15 p_15
;
%macro test(dsn);
proc sql;
select count(*) into:n trimmed from &dsn;
select id into: value separated by ' ' from &dsn;
create table want as
select distinct a.x,a.y,
%do i=1 %to &n;
%let cur=%scan(&value,&i);
t&i..p_&cur
%if &i<&n %then ,;
%else ;
%end;
from have a
%do i=1 %to &n;
%let cur=%scan(&value,&i);
left join have (where=(p=&cur) rename=(z=p_&cur.)) t&i.
on a.x=t&i..x and a.y=t&i..y
%end;
;
quit;
%mend;
%test(foo);
I am matching files base on IDs numbers. I need to format a data set with the IDs to be matched, so that the same ID number is not repeated in column a (because column b's ID is the surviving ID after the match is completed). My list of IDs has over 1 million observations, and the same ID may be repeated multiple times in either/both columns.
Here is an example of what I've got/need:
Sample Data
ID1 ID2
1 2
3 4
2 5
6 1
1 7
5 8
The surviving IDs would be:
2
4
5
error - 1 no longer exists
error - 1 no longer exists
8
WHAT I NEED
ID1 ID2
1 2
3 4
2 5
6 5
5 7
7 8
I am, probably very obviously, a SAS novice, but here is what I have tried, re-running over and over again because I have some IDs that are repeated upward of 50 times or more.
Proc sort data=Have;
by ID1;
run;
This sort makes the repeated ID1 values consecutive, so the I could use LAG to replace the destroyed ID1s with the surviving ID2 from the line above.
Data Want;
set Have;
by ID1;
lagID1=LAG(ID1);
lagID2=LAG(ID2);
If NOT first. ID1 THEN DO;
If ID1=lagID1 THEN ID1=lagID2;
KEEP ID1 ID2;
IF ID1=ID2 then delete;
end;
run;
That sort of works, but I still end up with some that end up with duplicates that won't resolve no matter how many times I run (I would have looped it, but I don't know how), because they are just switching back and forth between IDs that have other duplicates (I can get down to about 2,000 of these).
I have figured out that instead of using LAG, I need replace all values after the current line with ID2 for each ID1 value, but I cannot figure out how to do that.
I want to read observation 1, find all later instances of the value of ID1, in both ID1 or ID2 columns, and replace that value with the current observation's ID2 value. Then I want to repeat that process with line 2 and so on.
For the example, I would want to look for any instances after line one of the value 1, and replace it with 2, since that is the surviving ID of that pair - 1 may appear further down multiple times in either of the columns, and I need all them to replaced. Line two would look for later values of 3 and replace them with 4, and so one. The end result should be that an ID number only appears once ever in the ID1 column (though it may appear multiple times in the ID2 column).
ID1 ID2
1 2
3 4
2 5
6 1
1 7
5 8
After first line has been read, data set would look as follows:
ID1 ID2
1 2
3 4
2 5
6 2
2 7
5 8
Reading observation two would make no changes since 3 does not appear again; after observation 3, the set would be:
ID1 ID2
1 2
3 4
2 5
6 5
5 7
5 8
Again, there would be not changes from observation four. but observation 5 would cause the final change:
ID1 ID2
1 2
3 4
2 5
6 5
5 7
7 8
I have tried using the following statement but I can't even tell if I am on the complete wrong track or if I just can't get the syntax figured out.
Data want;
Set have;
Do i=_n_;
ID=ID2;
Replace next var{EUID} where (EUID1=EUID1 AND EUID2=EUID1);
End;
Run;
Thanks for your help!
There is no need to work back and forth thru the data file. You just need to retain the replacement information so that you can process the file in a single pass.
One way to do that is to make a temporary array using the values of the ID variables as the index. That is easy to do for your simple example with small ID values.
So for example if all of the ID values are integers between 1 and 1000 then this step will do the job.
data want ;
set have ;
array xx (1000) _temporary_;
do while (not missing(xx(id1))); id1=xx(id1); end;
do while (not missing(xx(id2))); id2=xx(id2); end;
output;
xx(id1)=id2;
run;
You probably need to add a test to prevent cycles (1 -> 2 -> 1).
For a more general solution you should replace the array with a hash object instead. So something like this:
data want ;
if _n_=1 then do;
declare hash h();
h.definekey('old');
h.definedata('new');
h.definedone();
call missing(new,old);
end;
set have ;
do while (not h.find(key:id1)); id1=new; end;
do while (not h.find(key:id2)); id2=new; end;
output;
h.add(key: id1,data: id2);
drop old new;
run;
Here's an implementation of the algorithm you've suggested, using a modify statement to load and rewrite each row one at a time. It works with your trivial example but with messier data you might get duplicate values in ID1.
data have;
input ID1 ID2 ;
datalines;
1 2
3 4
2 5
6 1
1 7
5 8
;
run;
title "Before making replacements";
proc print data = have;
run;
/*Optional - should improve performance at cost of increased memory usage*/
sasfile have load;
data have;
do i = 1 to nobs;
do j = i to nobs;
modify have point = j nobs = nobs;
/* Make copies of target and replacement value for this pass */
if j = i then do;
id1_ = id1;
id2_ = id2;
end;
else do;
flag = 0; /* Keep track of whether we made a change */
if id1 = id1_ then do;
id1 = id2_;
flag = 1;
end;
if id2 = id1_ then do;
id2 = id2_;
flag = 1;
end;
if flag then replace; /* Only rewrite the row if we made a change */
end;
end;
end;
stop;
run;
sasfile have close;
title "After making replacements";
proc print data = have;
run;
Please bear in mind that as this modifies the dataset in place, interrupting the data step while it is running could result in data loss. Make sure you have a backup first in case you need to roll your changes back.
Seems like this should do the trick and is fairly straight forward. Let me know if it is what you are looking for:
data have;
input id1 id2;
datalines;
1 2
3 4
2 5
6 1
1 7
5 8
;
run;
%macro test();
proc sql noprint;
select count(*) into: cnt
from have;
quit;
%do i = 1 %to &cnt;
proc sql noprint;
select id1,id2 into: id1, :id2
from have
where monotonic() = &i;quit;
data have;
set have;
if (_n_ > input("&i",8.))then do;
if (id1 = input("&id1",8.))then id1 = input("&id2",8.);
if (id2 = input("&id1",8.))then id2 = input("&id2",8.);
end;
run;
%end;
%mend test;
%test();
this might be a little faster:
data have2;
input id1 id2;
datalines;
1 2
3 4
2 5
6 1
1 7
5 8
;
run;
%macro test2();
proc sql noprint;
select count(*) into: cnt
from have2;
quit;
%do i = 1 %to &cnt;
proc sql noprint;
select id1,id2 into: id1, :id2
from have2
where monotonic() = &i;
update have2 set id1 = &id2
where monotonic() > &i
and id1 = &id1;
quit;
proc sql noprint;
update have2 set id2 = &id2
where monotonic() > &i
and id2 = &id1;
quit;
%end;
%mend test2;
%test2();
I have a dataset with some variables named sx for x = 1 to n.
Is it possible to write a freq which gives the same result as:
proc freq data=prova;
table s1 * s2 * s3 * ... * sn /list missing;
run;
but without listing all the names of the variables?
I would like an output like this:
S1 S2 S3 S4 Frequency
A 10
A E 100
A E J F 300
B 10
B E 100
B E J F 300
but with an istruction like this (which, of course, is invented):
proc freq data=prova;
table s1:sn /list missing;
run;
Why not just use PROC SUMMARY instead?
Here is an example using two variables from SASHELP.CARS.
So this is PROC FREQ code.
proc freq data=sashelp.cars;
where make in: ('A','B');
tables make*type / list;
run;
Here is way to get counts using PROC SUMMARY
proc summary missing nway data=sashelp.cars ;
where make in: ('A','B');
class make type ;
output out=want;
run;
proc print data=want ;
run;
If you need to calculate the percentages you can instead use the WAYS statement to get both the overall and the individual cell counts. And then add a data step to calculate the percentages.
proc summary missing data=sashelp.cars ;
where make in: ('A','B');
class make type ;
ways 0 2 ;
output out=want;
run;
data want ;
set want ;
retain total;
if _type_=0 then total=_freq_;
percent=100*_freq_/total;
run;
So if you have 10 variables you would use
ways 0 10 ;
class s1-s10 ;
If you just want to build up the string "S1*S2*..." then you could use a DO loop or a macro %DO loop and put the result into a macro variable.
data _null_;
length namelist $200;
do i=1 to 10;
namelist=catx('*',namelist,cats('S',i));
end;
call symputx('namelist',namelist);
run;
But here is an easy way to make such a macro variable from ANY variable list not just those with numeric suffixes.
First get the variables names into a dataset. PROC TRANSPOSE is a good way if you use the OBS=0 dataset option so that you only get the _NAME_ column.
proc transpose data=have(obs=0) ;
var s1-s10 ;
run;
Then use PROC SQL to stuff the names into a macro variable.
proc sql noprint;
select _name_
into :namelist separated by '*'
from &syslast
;
quit;
Then you can use the macro variable in your TABLES statement.
proc freq data=have ;
tables &namelist / list missing ;
run;
Car':
In short, no. There is no shortcut syntax for specifying a variable list that crosses dimension.
In long, yes -- if you create a surrogate variable that is an equivalent crossing.
Discussion
Sample data generator:
%macro have(top=5);
%local index;
data have;
%do index = 1 %to ⊤
do s&index = 1 to 2+ceil(3*ranuni(123));
%end;
array V s:;
do _n_ = 1 to 5*ranuni(123);
x = ceil(100*ranuni(123));
if ranuni(123) < 0.1 then do;
ix = ceil(&top*ranuni(123));
h = V(ix);
V(ix) = .;
output;
V(ix) = h;
end;
else
output;
end;
%do index = 1 %to ⊤
end;
%end;
run;
%mend;
%have;
As you probably noticed table s: created one freq per s* variable.
For example:
title "One table per variable";
proc freq data=have;
tables s: / list missing ;
run;
There is no shortcut syntax for specifying a variable list that crosses dimension.
NOTE: If you specify out=, the column names in the output data set will be the last variable in the level. So for above, the out= table will have a column "s5", but contain counts corresponding to combinations for each s1 through s5.
At each dimensional level you can use a variable list, as in level1 * (sublev:) * leaf. The same caveat for out= data applies.
Now, reconsider the original request discretely (no-shortcut) crossing all the s* variables:
title "1 table - 5 columns of crossings";
proc freq data=have;
tables s1*s2*s3*s4*s5 / list missing out=outEach;
run;
And, compare to what happens when a data step view uses a variable list to compute a surrogate value corresponding to the discrete combinations reported above.
data haveV / view=haveV;
set have;
crossing = catx(' * ', of s:); * concatenation of all the s variables;
keep crossing;
run;
title "1 table - 1 column of concatenated crossings";
proc freq data=haveV;
tables crossing / list missing out=outCat;
run;
Reality check with COMPARE, I don't trust eyeballs. If zero rows with differences (per noequal) then the out= data sets have identical counts.
proc compare noprint base=outEach compare=outCat out=diffs outnoequal;
var count;
run;
----- Log -----
NOTE: There were 31 observations read from the data set WORK.OUTEACH.
NOTE: There were 31 observations read from the data set WORK.OUTCAT.
NOTE: The data set WORK.DIFFS has 0 observations and 3 variables.
NOTE: PROCEDURE COMPARE used (Total process time)
My initial Dataset has 14000 STID variable with 10^5 observation for each.
I would like to make some procedures BY each stid, output the modification into data by STID and then set all STID together under each other into one big dataset WITHOUT a need to output all temporary STID-datsets.
I start writing a MACRO:
data HAVE;
input stid $ NumVar1 NumVar2;
datalines;
a 5 45
b 6 2
c 5 3
r 2 5
f 4 4
j 7 3
t 89 2
e 6 1
c 3 8
kl 1 6
h 2 3
f 5 41
vc 58 4
j 5 9
ude 7 3
fc 9 11
h 6 3
kl 3 65
b 1 4
g 4 4
;
run;
/* to save all distinct values of THE VARIABLE stid into macro variables
where &N_VAR - total number of distinct variable values */
proc sql;
select count(distinct stid)
into :N_VAR
from HAVE;
select distinct stid
into :stid1 - :stid%left(&N_VAR)
from HAVE;
quit;
%macro expand_by_stid;
/*STEP 1: create datasets by STID*/
%do i=1 %to &N_VAR.;
data stid&i;
set HAVE;
if stid="&&stid&i";
run;
/*STEP 2: from here data modifications for each STID-data (with procs and data steps, e.g.)*/
data modified_stid&i;
set stid&i;
NumVar1_trans=NumVar1**2;
NumVar2_trans=NumVar1*NumVar2;
run;
%end;
/*STEP 3: from here should be some code lines that set together all created datsets under one another and delete them afterwards*/
data total;
set %do n=1 %to &N_VAR.;
modified_stid&n;
%end;
run;
proc datasets library=usclim;
delete <ALL DATA SETS by SPID>;
run;
%mend expand_by_stid;
%expand_by_stid;
But the last step does not work. How can I do it?
You're very close - all you need to do is remove the semicolon in the macro loop and put it after the %end in step 3, as below:
data total;
set
%do n=1 %to &N_VAR.;
modified_stid&n
%end;;
run;
This then produces the statement you were after:
set modified_stid1 modified_stid2 .... ;
instead of what your macro was originally generating:
set modified_stid1; modified_stid2; ...;
Finally, you can delete all the temporary datasets using stid: in the delete statement:
proc datasets library=usclim;
delete stid: ;
run;
I have a dataset that has columns like:
a|b|c|d|e
and rows like:
1|3|5|7|9
2|4|6|8|10
How to change it to:
Char|Num|
a|1
a|2
b|3
b|4
c|5
c|6
d|7
d|8
e|9
e|10
Thank you in advance!
You can use PROC TRANSPOSE. The only gotcha is to get what you want you need a BY variable. Easiest thing is to add a record number and use that as your BY.
data have;
input a b c d;
i = _n_;
datalines;
1 2 3 4
5 6 7 8
;
run;
proc transpose data=have out=want(drop=i);
by i;
var a b c d;
run;