SAS Proc SQL Trim not working? - sas

I have a problem that seems pretty simple (probably is...) but I can't get it to work.
The variable 'name' in the dataset 'list' has a length of 20. I wish to conditionally select values into a macro variable, but often the desired value is less than the assigned length. This leaves trailing blanks at the end, which I cannot have as they disrupt future calls of the macro variable.
I've tried trim, compress, btrim, left(trim, and other solutions but nothing seems to give me what I want (which is 'Joe' with no blanks). This seems like it should be easier than it is..... Help.
data list;
length id 8 name $20;
input id name $;
cards;
1 reallylongname
2 Joe
;
run;
proc sql;
select trim(name) into :nameselected
from list
where id=2;
run;
%put ....&nameselected....;

Actually, there is an option, TRIMMED, to do what you want.
proc sql noprint;
select name into :nameselected TRIMMED
from list
where id=2;
quit;
Also, end PROC SQL with QUIT;, not RUN;.

It works if you specify a separator:
proc sql;
select trim(name) into :nameselected separated by ''
from list
where id=2;
run;

Related

Could someone please explain what the following lines of this code do?

This is the code that I have with me:
%let data=sashelp.cars;
proc transpose data=&data(obs=0) out=names;
var _all_;
run;
proc sql;
select cats('_',_name_,'=missing(',_name_,');') into: stmts separated by ' ' from names;
run;
data missing;
set &data;
_BIGN = 1;
/*%m_expand_varlist(data=&data,expr=cats('_',_name_,'=missing(',_name_,');'));*/
&stmts;
keep _:;
run;
proc summary data=missing;
var _numeric_;
output out=smry sum=;
run;
proc transpose data=smry(drop=_type_ _freq_) out=smry_;
run;
The goal of this code is to output the number of missing values for both character and numeric variables in the data set. The code accomplishes that objective but I have difficulty in understanding the purpose of certain lines in the code.
May I know what the following part of the code does?
select cats('_',_name_,'=missing(',_name_,');') into: stmts separated by ' ' from names;
I understand that the into part just stores the value into the macro variable stmts but what does "separated by ' ' from names" in the above line mean?
data missing;
set &data;
_BIGN = 1;
&stmts;
keep _:;
run;
And in the above portion of the code, what is the purpose of "keep :"? What does the ":" do in that? And is the "_BIGN = 1" necessary?
And also in the final output table called smry_, I get underscores before the names of the variables. But I don't need these underscores. What can I do to remove them? When I removed the underscore after the "keep :", the underscores in the smry table went away but I was left with only 10 rows instead of 15. Help would be appreciated. Thank you.
Before answering your questions, let me disclaim that this is not the way to go if you simply want a count of missing values for each numeric variable in your data.
However, this seems to be more of a practice assignment than an actual problem.
The Separated By Clause simply inserts the specific string between the values in the macro variable if the data source has >1 items. In this case the names data set has 15 items, so all 15 values are listed with a few spaces between them.
The colon operator in the keep statement tells the data step to keep only variables prefixed with an underscore.
_BIGN is not strictly necessary. However, it seems that the author of the code wants a simple count of observations in the final data set. That is all it does.
The underscores are applied to each variable name in the creation of the macro variable in. It is probably done to avoid conflicts between variable names (though this is technically still possible). Obviously, you can simply remove the underscore in the final data set.
As you know the "into" clause stores the values in the macro variable. The "separated by" leads to a list of values stored in the variable with spaces as delimiter here. If you don't use this you have only the value of the first row in your macro variable.
The ":" is a wildcard that means you keep all the variables starting with an underscore:
keep _:;
I managed to remove the underscores in the final data set using the following code:
data _smry_(drop = _name_);
set smry_;
name=compress(_name_, , 'kas');
run;
You could just rename the underscore variables back to original.
%let data=sashelp.heart;
proc transpose data=&data(obs=0) out=names;
var _all_;
run;
proc sql;
select cats('Label _',_name_,'=',quote(_label_),';') into: lb_stmts separated by ' ' from names;
select cats('_',_name_,'=missing(',_name_,');') into: stmts separated by ' ' from names;
select cats('_',_name_,'=',_name_) into: rn_stmts separated by ' ' from names;
run;
options symbolgen=1;
data missingV / view=missingV;
set &data;
&stmts;
&lb_stmts;
rename &rn_stmts;
keep _:;
run;
options symbolgen=0;
ods output summary=summary;
proc means data=missingV Sum Mean N STACKODSOUTPUT;
var _numeric_;
run;
ods output close;
proc print width=minimum label;
label sum='#Missing' mean='%Missing';
format sum 8. mean percentn8.1;
run;

Proc SQL SAS Basic

I want an answer for this.
The input I have is:
ABC123
The output I want is:
123ABC
How to print the output in this format (i.e. backwards) using Proc SQL?
Based on the information given and assuming that all your data is in same format you can tweak substr function in proc sql
data have;
value='ABC123';
run;
proc sql;
create table want
as
select value,
substr(value,4,4)||substr(value,1,3) as new_value
from have;
quit;
proc print data=want; run;
The same function can be applied in data step as well.
You will probably want to use trim() to deal with the trailing spaces that SAS stores in character variables.
trim(substr(have,4))||substr(have,1,3)
If you want an algorithm that would work with similar strings of any length (any number of letters followed by any number of digits), I suggest using regular expressions to modify the input string.
outStr = prxChange("s/([A-z]+)([\d]+)/$2$1/", 1, inStr);
You can easily use it within proc sql.
data test1;
inStr = "ABCdef12345";
run;
proc sql;
create table test2 as
select prxChange("s/([A-z]+)([\d]+)/$2$1/", 1, inStr) as outStr
from test1;
quit;
Base SAS contains a function REVERSE that is dedicated to reversing a string, and that can be used both in proc sql and in a datastep. See example in SAS documentation or here:
proc sql;
select Name,
reverse(Name) as Name_reversed
from sashelp.class
;
quit;
output:
Name | Name_reversed
--------|--------------
Alfred | derflA
Alice | ecilA
Barbara | arabraB
etc.

SAS: How to calculate frequency for all character variables except some

I know I can have something like the following to calculate frequency for all Chars:
proc freq data=sashelp.class;
tables _char_;
run;
However, is there a way to exclude some variables? I want to do something like:
proc freq data=sashelp.class;
tables _char_ EXCEPT VAR1 VAR2;
run;
Thank you so much!
you can use drop = , as shown below.
proc freq data=sashelp.cars(drop=origin make);
tables _char_;
run;
The drop example is the simplest, certainly, and probably best if that's exactly the request.
However, if it's slightly different - such as, you want to include (or exclude) all character variables matching a particular pattern, you can use macro variables constructed from dictionary.columns (or proc contents output dataset).
proc sql;
select name
into :freqlist separated by ' '
from dictionary.columns
where memname='YOURTABLE' and libname='YOURLIB'
and type='char' and name like 'PATTERN%'
;
quit;
Obviously filling in the various uppercase things as appropriate. Usually MEMNAME, LIBNAME, and NAME are stored upper case, though not always, so consider adding UPCASE() to them.
Then you can put &freqlist.; on the tables statement to get the list of columns that match your query.

SAS sum variables using name after a proc transpose

I have a table with postings by category (a number) that I transposed. I got a table with each column name as _number for example _16, _881, _853 etc. (they aren't in order).
I need to do the sum of all of them in a proc sql, but I don't want to create the variable in a data step, and I don't want to write all of the columns names either . I tried this but doesn't work:
proc sql;
select sum(_815-_16) as nnl
from craw.xxxx;
quit;
I tried going to the first number to the last and also from the number corresponding to the first place to the one corresponding to the last place. Gives me a number that it's not correct.
Any ideas?
Thanks!
You can't use variable lists in SQL, so _: and var1-var6 and var1--var8 don't work.
The easiest way to do this is a data step view.
proc sort data=sashelp.class out=class;
by sex;
run;
*Make transposed dataset with similar looking names;
proc transpose data=class out=transposed;
by sex;
id height;
var height;
run;
*Make view;
data transpose_forsql/view=transpose_forsql;
set transposed;
sumvar = sum(of _:); *I confirmed this does not include _N_ for some reason - not sure why!;
run;
proc sql;
select sum(sumvar) from transpose_Forsql;
quit;
I have no documentation to support this but from my experience, I believe SAS will assume that any sum() statement in SQL is the sql-aggregate statement, unless it has reason to believe otherwise.
The only way I can see for SAS to differentiate between the two is by the way arguments are passed into it. In the below example you can see that the internal sum() function has 3 arguments being passed in so SAS will treat this as the SAS sum() function (as the sql-aggregate statement only allows for a single argument). The result of the SAS function is then passed in as the single parameter to the sql-aggregate sum function:
proc sql noprint;
create table test as
select sex,
sum(sum(height,weight,0)) as sum_height_and_weight
from sashelp.class
group by 1
;
quit;
Result:
proc print data=test;
run;
sum_height_
Obs Sex and_weight
1 F 1356.3
2 M 1728.6
Also note a trick I've used in the code by passing in 0 to the SAS function - this is an easy way to add an additional parameter without changing the intended result. Depending on your data, you may want to swap out the 0 for a null value (ie. .).
EDIT: To address the issue of unknown column names, you can create a macro variable that contains the list of column names you want to sum together:
proc sql noprint;
select name into :varlist separated by ','
from sashelp.vcolumn
where libname='SASHELP'
and memname='CLASS'
and upcase(name) like '%T' /* MATCHES HEIGHT AND WEIGHT */
;
quit;
%put &varlist;
Result:
Height,Weight
Note that you would need to change the above wildcard to match your scenario - ie. matching fields that begin with an underscore, instead of fields that end with the letter T. So your final SQL statement will look something like this:
proc sql noprint;
create table test as
select sex,
sum(sum(&varlist,0)) as sum_of_fields_ending_with_t
from sashelp.class
group by 1
;
quit;
This provides an alternate approach to Joe's answer - though I believe using the view as he suggests is a cleaner way to go.

SAS - Creating variables from macro variables

I have a SAS dataset which has 20 character variables, all of which are names (e.g. Adam, Bob, Cathy etc..)
I would like a dynamic code to create variables called Adam_ref, Bob_ref etc.. which will work even if there a different dataset with different names (i.e. don't want to manually define each variable).
So far my approach has been to use proc contents to get all variable names and then use a macro to create macro variables Adam_ref, Bob_ref etc..
How do I create actual variables within the dataset from here? Do I need a different approach?
proc contents data=work.names
out=contents noprint;
run;
proc sort data = contents; by varnum; run;
data contents1;
set contents;
Name_Ref = compress(Name||"_Ref");
call symput (NAME, NAME_Ref);
%put _user_;
run;
If you want to create an empty dataset that has variables named like some values you have in a macro variables you could do something like this.
Save the values into macro variables that are named by some pattern, like v1, v2 ...
proc sql;
select compress(Name||"_Ref") into :v1-:v20 from contents;
quit;
If you don't know how many values there are, you have to count them first, I assumed there are only 20 of them.
Then, if all your variables are character variables of length 100, you create a dataset like this:
%macro create_dataset;
data want;
length %do i=1 %to 20; &&v&i $100 %end;
;
stop;
run;
%mend;
%create_dataset; run;
This is how you can do it if you have the values in macro variable, there is probably a better way to do it in general.
If you don't want to create an empty dataset but only change the variable names, you can do it like this:
proc sql;
select name into :v1-:v20 from contents;
quit;
%macro rename_dataset;
data new_names;
set have(rename=(%do i=1 %to 20; &&v&i = &&v&i.._ref %end;));
run;
%mend;
%rename_dataset; run;
You can use PROC TRANSPOSE with an ID statement.
This step creates an example dataset:
data names;
harry="sally";
dick="gordon";
joe="schmoe";
run;
This step is essentially a copy of your step above that produces a dataset of column names. I will reuse the dataset namerefs throughout.
proc contents data=names out=namerefs noprint;
run;
This step adds the "_Refs" to the names defined before and drops everything else. The variable "name" comes from the column attributes of the dataset output by PROC CONTENTS.
data namerefs;
set namerefs (keep=name);
name=compress(name||"_Ref");
run;
This step produces an empty dataset with the desired columns. The variable "name" is again obtained by looking at column attributes. You might get a harmless warning in the GUI if you try to view the dataset, but you can otherwise use it as you wish and you can confirm that it has the desired output.
proc transpose out=namerefs(drop=_name_) data=namerefs;
id name;
run;
Here is another approach which requires less coding. It does not require running proc contents, does not require knowing the number of variables, nor creating a macro function. It also can be extended to do some additional things.
Step 1 is to use built-in dictionary views to get the desired variable names. The appropriate view for this is dictionary.columns, which has alias of sashelp.vcolumn. The dictionary libref can be used only in proc sql, while th sashelp alias can be used anywhere. I tend to use sashelp alias since I work in windows with DMS and can always interactively view the sashelp library.
proc sql;
select compress(Name||"_Ref") into :name_list
separated by ' '
from sashelp.vcolumn
where libname = 'WORK'
and memname = 'NAMES';
quit;
This produces a space delimited macro vaiable with the desired names.
Step 2 To build the empty data set then this code will work:
Data New ;
length &name_list ;
run ;
You can avoid assuming lengths or create populated dataset with new variable names by using a slightly more complicated select statement.
For example
select compress(Name)||"_Ref $")||compress(put(length,best.))
into :name_list
separated by ' '
will generate a macro variable which retains the previous length for each variable. This will work with no changes to step 2 above.
To create populated data set for use with rename dataset option, replace the select statement as follows:
select compress(Name)||"= "||compress(_Ref")
into :name_list
separated by ' '
Then replace the Step 2 code with the following:
Data New ;
set names (rename = ( &name_list)) ;
run ;