Create SAS data set conditionally on other data sets - sas

I have 6 identical SAS data sets. They only differ in terms of the values of the observations.
How can I create one output data, which finds the maximum value across all the 6 data sets for each cell?
The update statement seems a good candidate, but it cannot set a condition.
data1
v1 v2 v3
1 1 1
1 2 3
data2
v1 v2 v3
1 2 3
1 1 1
Result
v1 v2 v3
1 2 3
1 2 3

If need be the following could be automated by "PUT" statements or variable arrays.
***ASSUMES DATA SETS ARE SORTED BY ID;
Data test;
do until(last.id);
set a b c;
by id;
if v1 > updv1 then updv1 = v1;
if v2 > updv2 then updv2 = v2;
if v3 > updv3 then updv3 = v3;
end;
drop v1-v3;
rename updv1-updv3 = v1-v3;
run;
To provide a more complete solution to Rico's question(assuming 6 datasets e.g. d1-d6) one could do it this way:
Data test;
array v(*) v1-v3;
array updv(*) updv1-updv3;
do until(last.id);
set d1-d6;
by id;
do i = 1 to dim(v);
if v(i) > updv(i) then updv(i) = v(i);
end;
end;
drop v1-v3;
rename updv1-updv3 = v1-v3;
run;
proc print;
var id v1-v3;
run;

See below. For a SAS beginner might be too complex. I hope the comments do explain it a bit.
/* macro rename_cols_opt to generate cols_opt&n variables
- cols_opt&n contains generated code for dataset RENAME option for a given (&n) dataset
*/
%macro rename_cols_opt(n);
%global cols_opt&n max&n;
proc sql noprint;
select catt(name, '=', name, "&n") into: cols_opt&n separated by ' '
from dictionary.columns
where libname='WORK' and memname='DATA1'
and upcase(name) ne 'MY_ID_COLUMN'
;
quit;
%mend;
/* prepare macro variables = pre-generate the code */
%rename_cols_opt(1)
%rename_cols_opt(2)
%rename_cols_opt(3)
%rename_cols_opt(4)
%rename_cols_opt(5)
%rename_cols_opt(6)
/* create macro variable keep_list containing names of output variables to keep (based on DATA1 structure, the code expects those variables in other tables as well */
proc sql noprint;
select trim(name) into: keep_list separated by ' '
from dictionary.columns
where libname='WORK' and memname='DATA1'
;
quit;
%put &keep_list;
/* macro variable maxcode contains generated code for calculating all MAX values */
proc sql noprint;
select cat(trim(name), ' = max(of ', trim(name), ":)") into: maxcode separated by '; '
from dictionary.columns
where libname='WORK' and memname='DATA1'
and upcase(name) ne 'MY_ID_COLUMN'
;
quit;
%put "&maxcode";
data result1 / view =result1;
merge
data1 (in=a rename=(&cols_opt1))
data2 (in=b rename=(&cols_opt2))
data3 (in=b rename=(&cols_opt3))
data4 (in=b rename=(&cols_opt4))
data5 (in=b rename=(&cols_opt5))
data6 (in=b rename=(&cols_opt6))
;
by MY_ID_COLUMN;
&maxcode;
keep &keep_list;
run;
/* created a datastep view, now "describing" it to see the generated code */
data view=result1;
describe;
run;

Here's another attempt that is scalable against any number of datasets and variables. I've added in an ID variable this time as well. Like the answer from #vasja, there are some advanced techniques used here. The 2 solutions are in fact very similar, I've used 'call execute' instead of a macro to create the view. My solution also requires the dataset names to be stored in a dataset.
/* create dataset of required dataset names */
data datasets;
input ds_name $;
cards;
data1
data2
;
run;
/* dummy data */
data data1;
input id v1 v2 v3;
cards;
10 1 1 1
20 1 2 3
;
run;
data data2;
input id v1 v2 v3;
cards;
10 1 2 3
20 1 1 1
;
run;
/* create dataset, macro list and count of variables names */
proc sql noprint;
create table variables as
select name as v_name from dictionary.columns
where libname='WORK' and upcase(memname)='DATA1' and upcase(name) ne 'ID';
select name, count(*) into :keepvar separated by ' ',
:numvar
from dictionary.columns
where libname='WORK' and upcase(memname)='DATA1' and upcase(name) ne 'ID';
quit;
/* create view that joins all datasets, renames variables and calculates maximum value per id */
data _null_;
set datasets end=last;
if _n_=1 then call execute('data data_all / view=data_all; merge');
call execute (trim(ds_name)|| '(rename=(');
do i=1 to &numvar.;
set variables point=i;
call execute(trim(v_name)||'='||catx('_',v_name,_n_));
end;
call execute('))');
if last then do;
call execute('; by id;');
do i=1 to &numvar.;
set variables point=i;
call execute(trim(v_name)||'='||'max(of '||trim(v_name)||':);');
end;
call execute('run;');
end;
run;
/* create dataset of maximum values per id per variable */
data result (keep=id &keepvar.);
set data_all;
run;

Related

SAS Array Variable Name Based on Another Array

I have data in the following format:
data have;
input id rtl_apples rtl_oranges rtl_berries;
datalines;
1 50 60 10
2 10 30 80
3 40 8 1
;
I'm trying to create new variables that represent the percent of the sum of the RTL variables, PCT_APPLES, PCT_ORANGES, PCT_BERRIES. The problem is I'm doing this within a macro so the names and number of RTL variables with vary with each iteration so the new variable names need to be generated dynamically.
This data step essentially gets what I need, but the new variables are in the format PCT1, PCT2, PCTn format so it's difficult to know which RTL variable the PCT corresponds too.
data want;
set have;
array rtls[*] rtl_:;
total_sales = sum(of rtl_:);
call symput("dim",dim(rtls));
array pct[&dim.];
do i=1 to dim(rtls);
pct[i] = rtls[i] / total_sales;
end;
drop i;
run;
I also tried creating the new variable name by using a macro variable, but only the last variable in the array is created. In this case, PCT_BERRIES.
data want;
set have;
array rtls[*] rtl_:;
total_sales = sum(of rtl_:);
do i=1 to dim(rtls);
var_name = compress(tranwrd(upcase(vname(rtls[i])),'RTL','PCT'));
call symput("var_name",var_name);
&var_name. = rtls[i] / total_sales;
end;
drop i var_name;
run;
I have a feeling I'm over complicating this so any help would be appreciated.
If you have the list of names in data already then use the list to create the names you need for your arrays.
proc sql noprint;
select distinct cats('RTL_',name),cats('PCT_',name)
into :rtl_list separated by ' '
, :pct_list separated by ' '
from dataset_with_names
;
quit;
data want;
set have;
array rtls &rtl_list;
array pcts &pct_list;
total_sales = sum(of rtls[*]);
do index=1 to dim(rtls);
pcts[index] = rtls[index] / total_sales;
end;
drop index ;
run;
You can't create variables while a data step is executing. This program uses PROC TRANSPOSE to create a new data using the RTL_ variables "renamed" PCT_.
data have;
input id rtl_apples rtl_oranges rtl_berries;
datalines;
1 50 60 10
2 10 30 80
3 40 8 1
;;;;
run;
proc transpose data=have(obs=0) out=names;
var rtl_:;
run;
data pct;
set names;
_name_ = transtrn(_name_,'rtl_','PCT_');
y = .;
run;
proc transpose data=pct out=pct2;
id _name_;
var y;
run;
data want;
set have;
if 0 then set pct2(drop=_name_);
array _rtl[*] rtl_:;
array _pct[*] pct_:;
call missing(of _pct[*]);
total = sum(of _rtl[*]);
do i = 1 to dim(_rtl);
_pct[i] = _rtl[i]/total*1e2;
end;
drop i;
run;
proc print;
run;
You may want to just report the row percents
proc transpose data=&data out=&data.T;
by id;
var rtl_:;
run;
proc tabulate data=&data.T;
class id _name_;
var col1;
table
id=''
, _name_='Result'*col1=''*sum=''
_name_='Percent'*col1=''*rowpctsum=''
/ nocellmerge;
run;

Concatenating all variables in an observation in SAS

Is there a general purpose way of concatenating each variable in an observation into one larger variable whilst preserving the format of numeric/currency fields in terms of how it looks when you do a proc print on the dataset. (see sashelp.shoes for example)
Here is some code you can run, as you can see when looking at the log, using the catx function to produce a comma separated output removes both the $ currency sign as well as the period from the numeric variables
proc print data=sashelp.shoes (obs=10);
run;
proc sql;
select name into :varstr2 separated by ','
from dictionary.columns
where libname = "SASHELP" and
memname = "SHOES";
quit;
data stuff();
format all $5000.;
set sashelp.shoes ;
all = catx(',',&varstr2.) ;
put all;
run;
Any solution needs to be general purpose as it will run on disparate datasets with differently formatted variables.
You can manually loop over PDV variables of the data set, concatenating each formatted value retrieved with vvaluex. A hash can be used to track which variables of the data set to process. If you are comma separating values you will probably want to double quote formatted values that contain a comma.
data want;
set sashelp.cars indsname=_data;
if _n_ = 1 then do;
declare hash vars();
length _varnum 8 _varname $32;
vars.defineKey('_n_');
vars.defineData('_varname');
vars.defineDone();
_dsid = open(_data);
do _n_ = 1 to attrn(_dsid,'NVAR');
rc = vars.add(key:_n_,data:varname(_dsid,_n_));
end;
_dsid = close(_dsid);
call missing (of _:);
end;
format weight comma7.;
length allcat $32000 _vvx $32000;
do _n_ = 1 to vars.NUM_ITEMS;
vars.find();
_vvx = strip(vvaluex(_varname));
if index(_vvx,",") then _vvx = quote(strip(_vvx));
if _n_ = 1
then allcat = _vvx;
else allcat = cats(allcat,',',_vvx);
end;
drop _:;
run;
You can use import and export to csv file:
filename tem temp;
proc export data=sashelp.SHOES file=tem dbms=csv replace;
run;
data l;
length all $ 200;
infile tem truncover firstobs=2;
input all 1-200;
run;
P.S.
If you need concatenate only char, uou can create array of all CHARACTER columns in dataset, and just iterate thru:
data l;
length all $ 5000;
set sashelp.SHOES;
array ch [*] _CHARACTER_;
do i = 1 to dim(ch);
all=catx(',',all,ch[i]);
end;
run;
The PUT statement is the easiest way to do that. You don't need to know the variables names as you can use the _all_ variable list.
put (_all_) (+0);
It will honor the formats attached the variables and if you have used DSD option on the FILE statement then the result is a delimited list.
What is the ultimate goal of this exercise? If you want to create a file you can just write the file directly.
data _null_;
set sashelp.shoes(obs=3);
file 'myfile.csv' dsd ;
put (_all_) (+0);
run;
If you really do want to get that string into a dataset variable there is no need to invent some new function. Just take advantage of the PUT statements abilities by creating a file and then reading the lines from the file.
filename junk temp;
data _null_;
set sashelp.shoes(obs=3);
file junk dsd ;
put (_all_) (+0);
run;
data stuff ;
set sashelp.shoes(obs=3);
infile junk truncover ;
input all $5000.;
run;
You can even do it without creating the full text file. Instead just write one line at a time and save the line into a variable using the _FILE_ automatic variable.
filename junk temp;
data stuff;
set sashelp.shoes(obs=3);
file junk dsd lrecl=5000 ;
length all $5000;
put #1 (_all_) (+0) +(-2) ' ' #;
all = _file_;
output;
all=' ';
put #1 all $5000. #;
run;
Solution with vvalue and concat function (||):
It is similar with 'solution without catx' (the last one), but it is simplified by vvalue function instead put.
/*edit sashelp.shoes with missing values in Product as test-cases*/
proc sql noprint;
create table wocatx as
select * from SASHELP.SHOES;
update wocatx
set Product = '';
quit;
/*Macro variable for concat function (||)*/
proc sql;
select ('strip(vvalue('|| strip(name) ||'))') into :varstr4 separated by "|| ',' ||"
from dictionary.columns
where libname = "WORK" and
memname = "WOCATX";
quit;
/*Data step to concat all variables*/
data stuff2;
format all $5000.;
set work.wocatx ;
all = &varstr4. ;
put all;
run;
Solution with catx:
proc print data=SASHELP.SHOES;
run;
proc sql;
select ifc(strip(format) is missing,strip(name),ifc(type='num','put('|| strip(name) ||','|| strip(format) ||')','input('|| strip(name) ||','|| strip(format) ||')')) into :varstr2 separated by ','
from dictionary.columns
where libname = "SASHELP" and
memname = "SHOES";
quit;
data stuff();
format all $5000.;
set sashelp.shoes ;
all = catx(',',&varstr2.) ;
put all;
run;
If there isn't in dictionary.columns format, then in macro variable varstr2 will just name, if there is format, then when it would call in catx it will convert in format, that you need, for example,if variable is num type then put(Sales,DOLLAR12.), or if it char type then input function . You could add any conditions in select into if you need.
If there is no need of using of input function just change select:
ifc(strip(format) is missing,strip(name),'put('|| strip(name) ||','|| strip(format) ||')')
Solution without catx:
/*edit sashelp.shoes with missing values in Product as test-cases*/
proc sql noprint;
create table wocatx as
select * from SASHELP.SHOES;
update wocatx
set Product = '';
quit;
/*Macro variable for catx*/
proc sql;
select ifc(strip(format) is missing,strip(name),ifc(type='num','put('|| strip(name) ||','|| strip(format) ||')','input('|| strip(name) ||','|| strip(format) ||')')) into :varstr2 separated by ','
from dictionary.columns
where libname = "WORK" and
memname = "WOCATX";
quit;
/*data step with catx*/
data stuff;
format all $5000.;
set work.wocatx ;
all = catx(',',&varstr2.) ;
put all;
run;
/*Macro variable for concat function (||)*/
proc sql;
select ifc(strip(format) is missing,
'strip(' || strip(name) || ')',
'strip(put('|| strip(name) ||','|| strip(format) ||'))') into :varstr3 separated by "|| ',' ||"
from dictionary.columns
where libname = "WORK" and
memname = "WOCATX";
quit;
/*Data step without catx*/
data stuff1;
format all $5000.;
set work.wocatx ;
all = &varstr3. ;
put all;
run;
Result with catx and missing values:
Result without catx and with missing values:

In SAS, verify if a specified column exist in every table listed in a table

I use SAS 9.4.
I have a table of table names, having two columns: libname and memname, which is the name of library and name of table, as example blow:
libname | memname
lib1 | table1
lib2 | table2
For every record, I would like to verify if a column LIKE '%CLI%' with type string and contains only digits. Every table contains at most one column satisfying these conditions.
Finally, I would like to have add the name of the found column to the table of table name as a new column:
libname | memname | colname
lib1 | table1 | client
lib2 | table2 | cli_num
Thanks a lot for your help.
Checking existence and type can be done without actually opening the data sets. But we need to open them to check that the values are all digits. Here is a looping construct you could use, including relevant tests and example data.
/* CLI exists, contains only digits*/
data ex1;
input other $ CLI $;
datalines;
x 1234
x 5787
;
/* CLI exists, doesn't contains only digits*/
data ex2;
input other $ CLI $;
datalines;
x 123a
x 5787
;
/* CLI exists, isn't character*/
data ex3;
input other $ CLI;
datalines;
x 1234
x 5787
;
/* CLI doesn't exist*/
data ex4;
input other $ other2;
datalines;
x 1234
x 5787
;
/* Makes a table of the datasets*/
data tableoftables;
input libname $ memname $;
datalines;
work ex1
work ex2
work ex3
work ex4
;
%macro do_stuff(indata=);
/* A data set to collect test results and present them to user.*/
data out;
set &indata;
length exists $3 type $9. alldigits $3.;
run;
/* Put libname and data set names into macro variables*/
data _null_;
set &indata;
call symput(cat('libname', _n_), libname);
call symput(cat('memname', _n_), memname);
run;
/* Find the number of datasets to loop through*/
proc sql noprint;
select count(*)
into :rows
from &indata;
/* Loop over data sets*/
%do i=1 %to &rows;
/*If CLI was in a specific place, you could use varnum, like here: https://communities.sas.com/message/154973. To use like, it's easier to go through proc contents*/
/* Create data ser with variables*/
proc contents noprint data=&&libname&i...&&memname&i out=row&i;
run;
/* Test 1: Is variable in file*/
/* Infile is initiated as 0, but turns to 1 if there is at least one variable like '%CLI%'. Type and name are collected*/
%let infile=0;
data test&i;
set row&i;
where name like '%CLI%';
call symput('infile', 1);
call symput('type', type);
call symput('name', name);
run;
/* Test 2: Is variable character*/
%let typetext=-;
%if &infile=1 %then %do;
%if &type=2 %then %let typetext=Character;
%else %if &type=1 %then %let typetext=Numeric;
%end;
/* Test 3: Does variable only contain digits*/
%let alldigits=-;
data test3&i;
set &&libname&i...&&memname&i end=eof;
retain test;
if _n_=1 then test=0;
notdigit=notdigit(strip(&name));
test+notdigit;
if eof then do;
if test=0 then call symput('alldigits', "YES");
else call symput('alldigits', "NO");
end;
run;
data out;
set out;
if _n_=&i then do;
if &infile=1 then exists="YES";
else exists="NO";
type="&typetext";
alldigits="&alldigits";
end;
run;
%end;
proc print data=out;
run;
%mend;
%do_stuff(indata=tableoftables)

How to write a concise list of variables in table of a freq when the variables are differentiated only by a suffix?

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 &top;
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)

How to delete blank observations in a data set in SAS

I want to delete ALL blank observations from a data set.
I only know how to get rid of blanks from one variable:
data a;
set data(where=(var1 ne .)) ;
run;
Here I set a new data set without the blanks from var1.
But how to do it, when I want to get rid of ALL the blanks in the whole data set?
Thanks in advance for your answers.
If you are attempting to get rid of rows where ALL variables are missing, it's quite easy:
/* Create an example with some or all columns missing */
data have;
set sashelp.class;
if _N_ in (2,5,8,13) then do;
call missing(of _numeric_);
end;
if _N_ in (5,6,8,12) then do;
call missing(of _character_);
end;
run;
/* This is the answer */
data want;
set have;
if compress(cats(of _all_),'.')=' ' then delete;
run;
Instead of the compress you could also use OPTIONS MISSING=' '; beforehand.
If you want to remove ALL Rows with ANY missing values, then you can use NMISS/CMISS functions.
data want;
set have;
if nmiss(of _numeric_) > 0 then delete;
run;
or
data want;
set have;
if nmiss(of _numeric_) + cmiss(of _character_) > 0 then delete;
run;
for all char+numeric variables.
You can do something like this:
data myData;
set myData;
array a(*) _numeric_;
do i=1 to dim(a);
if a(i) = . then delete;
end;
drop i;
This will scan trough all the numeric variables and will delete the observation where it finds a missing value
Here you go. This will work irrespective of the variable being character or numeric.
data withBlanks;
input a$ x y z;
datalines;
a 1 2 3
b 1 . 3
c . . 3
. . .
d . 2 3
e 1 . 3
f 1 2 3
;
run;
%macro removeRowsWithMissingVals(inDsn, outDsn, Exclusion);
/*Inputs:
inDsn: Input dataset with some or all columns missing for some or all rows
outDsn: Output dataset with some or all columns NOT missing for some or all rows
Exclusion: Should be one of {AND, OR}. AND will only exclude rows if any columns have missing values, OR will exclude only rows where all columns have missing values
*/
/*get a list of variables in the input dataset along with their types (i.e., whether they are numericor character type)*/
PROC CONTENTS DATA = &inDsn OUT = CONTENTS(keep = name type varnum);
RUN;
/*put each variable with its own comparison string in a seperate macro variable*/
data _null_;
set CONTENTS nobs = num_of_vars end = lastObs;
/*use NE. for numeric cols (type=1) and NE '' for char types*/
if type = 1 then call symputx(compress("var"!!varnum), compbl(name!!" NE . "));
else call symputx(compress("var"!!varnum), compbl(name!!" NE '' "));
/*make a note of no. of variables to check in the dataset*/
if lastObs then call symputx("no_of_obs", _n_);
run;
DATA &outDsn;
set &inDsn;
where
%do i =1 %to &no_of_obs.;
&&var&i.
%if &i < &no_of_obs. %then &Exclusion;
%end;
;
run;
%mend removeRowsWithMissingVals;
%removeRowsWithMissingVals(withBlanks, withOutBlanksAND, AND);
%removeRowsWithMissingVals(withBlanks, withOutBlanksOR, OR);
Outout of withOutBlanksAND:
a x y z
a 1 2 3
f 1 2 3
Output of withOutBlanksOR:
a x y z
a 1 2 3
b 1 . 3
c . . 3
e 1 . 3
f 1 2 3
Really weird nobody provided this elegant answer:
if missing(cats(of _all_)) then delete;
Edit: indeed, I didn't realized the cats(of _all_) returns a dot '.' for missing numeric value.
As a fix, I suggest this, which seems to be more reliable:
*-- Building a sample dataset with test cases --*;
data test;
attrib a format=8.;
attrib b format=$8.;
a=.; b='a'; output;
a=1; b=''; output;
a=.; b=''; output; * should be deleted;
a=.a; b=''; output; * should be deleted;
a=.a; b='.'; output;
a=1; b='b'; output;
run;
*-- Apply the logic to delete blank records --*;
data test2;
set test;
*-- Build arrays of numeric and characters --*;
*-- Note: array can only contains variables of the same type, thus we must create 2 different arrays --*;
array nvars(*) _numeric_;
array cvars(*) _character_;
*-- Delete blank records --*;
*-- Blank record: # of missing num variables + # of missing char variables = # of numeric variables + # of char variables --*;
if nmiss(of _numeric_) + cmiss(of _character_) = dim(nvars) + dim(cvars) then delete;
run;
The main issue being if there is no numeric at all (or not char at all), the creation of an empty array will generate a WARNING and the call to nmiss/cmiss an ERROR.
So, I think so far there is not other option than building a SAS statement outside the data step to identify empty records:
*-- Building a sample dataset with test cases --*;
data test;
attrib a format=8.;
attrib b format=$8.;
a=.; b='a'; output;
a=1; b=''; output;
a=.; b=''; output; * should be deleted;
a=.a; b=''; output; * should be deleted;
a=.a; b='.'; output;
a=1; b='b'; output;
run;
*-- Create a SAS statement which test any missing variable, regardless of its type --*;
proc sql noprint;
select distinct 'missing(' || strip(name) || ')'
into :miss_stmt separated by ' and '
from dictionary.columns
where libname = 'WORK'
and memname = 'TEST'
;
quit;
/*
miss_stmt looks like missing(a) and missing(b)
*/
*-- Delete blank records --*;
data test2;
set test;
if &miss_stmt. then delete;
run;