I have two different datasets - in one dataset (1) the variable homes has data in the following format "C012" and I have another dataset (2) that has the variable home in the format "012". I need to merge these two datasets together. How do I either add the C into dataset 2 or remove the C from dataset 1?
This is how you add "C" in front of you home string variable
home = "C"||home;
so it would look like this
data have;
input home $ ;
cards;
012
;
run;
data want;
set have;
home = "C"||home;
run;
Related
Suppose I have the following dataset:
Name Option
---- ------
A X
A
B
C X
B
E X
C
I want to delete all lines in which in column "Name" there is a letter that in column Option as an X
In the previous example for instance I would like to delete all lines in which in Name there is A, C and E.
How could I do?
I am a beginner in Sas
Use delete.
data want;
set have;
if(option = 'X') then delete;
run;
An important note about delete: no other code will run after this statement. If you have code after this conditional then it will not execute. This is a unique feature of delete.
You can optionally use remove instead, in which case additional code will run after the statement.
Since you are a beginning let's explain some basic terminology. A DATESET consists of OBSERVATIONS (what you might call a row or a line) and VARIABLES (what you might call a column).
If you want to select observations that contain particular values then you probably want to use the IN operator.
data want;
set have;
where name not in ('A','B','C');
run;
If you want to select observations where the value of the variable NAME contains a particular letter then you probably want to use INDEXC() function.
data want;
set have;
where not indexc(name,'ABC');
run;
If you do not care about the case of the letters then you could convert the values to uppercase and test. Or switch to the FINDC() function instead, which has more options, including one to ignore the case when checking for letter matches.
data want;
set have;
where not findc(name,'ABC','i');
run;
Here is a SQL solution if you want to delete ALL rows corresponding to a name that has any row with OPTION='X'
data have;
infile datalines missover;
input name $ option $;
datalines;
A X
A
B
C X
B
E X
C
;
proc sql;
create table remove as
select distinct(name) from have
where option = 'X'
;
create table want as
select * from have
where name not in (select name from remove)
;
quit;
The following code is an old-school SAS technique of SORT and MERGE and produces the same result.
proc sort data=have;
by name;
data filter;
set have;
by name;
where option='X';
if first.name;
data want;
merge have filter(in=residue);
by name;
if not residue;
run;
I have 33 different datasets with one column and all share the same column name/variable name;
net_worth
I want to load the values into arrays and use them in a datastep. But the array that I use should depend on the the by groups in the datastep (country by city). There are total of 33 datasets and 33 groups (country by city). each dataset correspond to exactly one by group.
here is an example what the by groups look like in the dataset: customers
UK 105 (other fields)
UK 102 (other fields)
US 291 (other fields)
US 292 (other fields)
Could I get some advice on how to go about and enter the columns in arrays and then use them in a datastep. or do you suggest to do it in another way?
%let var1 = uk105
%let var2 = uk102
.....
&let var33 = jk12
data want;
set customers;
by country city;
if _n_ = 1 then do;
*set datasets and create and populate arrays*;
* use array values in calculations with fields from dataset customers, depending on which by group. if the by group is uk and city is 105 then i need to use the created array corresponding to that by group;
It is a little hard to understand what you want.
It sounds like you have one dataset name CUSTOMERS that has all of the main variables and a bunch of single variable datasets that the values of NET_WORTH for a lot of different things (Countries?).
Assuming that the observations in all of the datasets are in the same order then I think you are asking for how to generate a data step like this:
data want;
set customers;
set uk105 (rename=(net_worth=uk105));
set uk103 (rename=(net_worth=uk103));
....
run;
Which might just be easiest to do using a data step.
filename code temp;
data _null_;
input name $32. ;
file code ;
put ' set ' name '(rename=(net_worth=' name '));' ;
cards;
uk105
uk102
;;;;
data want;
set customers;
%include code / source2;
run;
When I export a dataset to Stata format using PROC EXPORT, SAS 9.4 automatically expands adds an extra (empty) byte to every observation of every string variable. For example, in this data set:
data test1;
input cust_id $ 1
month 3-8
category $ 10-12
status $ 14-14
;
datalines;
A 200003 ABC C
A 200004 DEF C
A 200006 XYZ 3
B 199910 ASD X
B 199912 ASD C
;
quit;
proc export data = test1
file = "test1.dta"
dbms = stata replace;
quit;
the variables cust_id, category, and status should be str1, str3, and str1 in the final Stata file, and thus take up 1 byte, 3 bytes, and 1 byte, respectively, for every observation. However, SAS automatically adds an extra empty byte to each observation, which expands their data types to str2, str4, and str2 data type in the outputted Stata file.
This is extremely problematic because that's an extra byte added to every observation of every string variable. For large datasets (I have some with ~530 million observations and numerous string variables), this can add several gigabytes to the exported file.
Once the file is loaded into Stata, the compress command in Stata can automatically remove these empty bytes and shrink the file, but for large datasets, PROC EXPORT adds so many extra bytes to the file that I don't always have enough memory to load the dataset into Stata in the first place.
Is there a way to stop SAS from padding the string variables in the first place? When I export a file with a one character string variable (for example), I want that variable stored as a one character string variable in the output file.
This is how you can do it using existing functions.
filename FT41F001 temp;
data _null_;
file FT41F001;
set test1;
put 256*' ' #;
__s=1;
do while(1);
length __name $32.;
call vnext(__name);
if missing(__name) or __name eq: '__' then leave;
substr(_FILE_,__s) = vvaluex(__name);
putlog _all_;
__s = sum(__s,vformatwx(__name));
end;
_file_ = trim(_file_);
put;
format month f6.;
run;
To avoid the use of _FILE_;
data _null_;
file FT41F001;
set test1;
__s=1;
do while(1);
length __name $32. __value $128 __w 8;
call vnext(__name);
if missing(__name) or __name eq: '__' then leave;
__value = vvaluex(__name);
__w = vformatwx(__name);
put __value $varying128. __w #;
end;
put;
format month f6.;
run;
If you are willing to accept a flat file answer, I've come up with a fairly simple way of generating one that I think has the properties you require:
data test1;
input cust_id $ 1
month 3-8
category $ 10-12
status $ 14-14
;
datalines;
A 200003 ABC C
A 200004 DEF C
A 200006 XYZ 3
B 199910 SD X
B 199912 D C
;
run;
data _null_;
file "/folders/myfolders/test.txt";
set test1;
put #;
_FILE_ = cat(of _all_);
put;
run;
/* Print contents of the file to the log (for debugging only)*/
data _null_;
infile "/folders/myfolders/test.txt";
input;
put _infile_;
run;
This should work as-is, provided that the total assigned length of all variables in your dataset is less than 32767 (the limit of the cat function in the data step environment- the lower 200 character limit doesn't apply, as that's only when you use cat to create a variable that hasn't been assigned a length). Beyond that you may start to run into truncation issues. A workaround when that happens is to only cat together a limited number of variables at a time - a manual process, but much less laborious than writing out put statements based on the lengths of all the variables, and depending on your data it may never actually come up.
Alternatively, you could go down a more complex macro route, getting variable lengths from either the vlength function or dictionary.columns and using those plus the variable names to construct the required put statement(s).
The variable upc is already defined in my cool dataset. How do I convert it to a macro variable? I am trying to combine both text and numbers. For example blah should equal upc=123;
data cool;
set cool;
blah = catx("","upc=&upc","ccc")
run;
If upc is a numeric variable and you just want to include its value into some character string then you don't need to do anything special. Concatenation function will convert it into character before concatenating automatically:
data cool;
blah = catx("","upc=",upc,"ccc");
run;
The result:
upc----blah
123 upc= 123ccc
BTW, if you want to concatenate strings without blanks between them, you can use function CATS(), which strips all leading and trailing spaces from each argument.
The following test code works for my SAS 9.3 x64 PC.
Please note that:
1.symputx() provide the connection between dataset and macro variables.
2.cats() will be more appropriate than catx() if delimiting characters are not needed.
3.If you did not attempt to create a new data set, data _NULL_ is fine.
You can check the log to see that the correct values are being assigned.
Bill
data a;
input ID $ x y ##;
datalines;
A 1 10 A 2 20 A 3 30
;
run;
options SymbolGen MPrint MLogic MExecNote MCompileNote=all;
data _NULL_;
set a;
call symputx(cats("blah",_N_),cats(ID,x),"G");
run;
%put blah1=&blah1;
%put blah2=&blah2;
%put blah3=&blah3;
I have two datasets in SAS that I would like to merge, but they have no common variables. One dataset has a "subject_id" variable, while the other has a "mom_subject_id" variable. Both of these variables are 9-digit codes that have just 3 digits in the middle of the code with common meaning, and that's what I need to match the two datasets on when I merge them.
What I'd like to do is create a new common variable in each dataset that is just the 3 digits from within the subject ID. Those 3 digits will always be in the same location within the 9-digit subject ID, so I'm wondering if there's a way to extract those 3 digits from the variable to make a new variable.
Thanks!
SQL(using sample data from Data Step code):
proc sql;
create table want2 as
select a.subject_id, a.other, b.mom_subject_id, b.misc
from have1 a JOIN have2 b
on(substr(a.subject_id,4,3)=substr(b.mom_subject_id,4,3));
quit;
Data Step:
data have1;
length subject_id $9;
input subject_id $ other $;
datalines;
abc001def other1
abc002def other2
abc003def other3
abc004def other4
abc005def other5
;
data have2;
length mom_subject_id $9;
input mom_subject_id $ misc $;
datalines;
ghi001jkl misc1
ghi003jkl misc3
ghi005jkl misc5
;
data have1;
length id $3;
set have1;
id=substr(subject_id,4,3);
run;
data have2;
length id $3;
set have2;
id=substr(mom_subject_id,4,3);
run;
Proc sort data=have1;
by id;
run;
Proc sort data=have2;
by id;
run;
data work.want;
merge have1(in=a) have2(in=b);
by id;
run;
an alternative would be to use
proc sql
and then use a join and the substr() just as explained above, if you are comfortable with sql
Assuming that your "subject_id" variable is a number then the substr function wont work as sas will try convert the number to a string. But by default it pads some paces on the left of the number.
You can use the modulus function mod(input, base) which returns the remainder when input is divided by base.
/*First get rid of the last 3 digits*/
temp_var = floor( subject_id / 1000);
/* then get the next three digits that we want*/
id = mod(temp_var ,1000);
Or in one line:
id = mod(floor(subject_id / 1000), 1000);
Then you can continue with sorting the new data sets by id and then merging.