if column 'all' contains the string which is in column 'sch', then this string will be replaced by the string in 'rep'. the column 'new_all' is what I expected.
data a0;
input sch $9. rep $14. ;
cards;
map_clm map_claim
xyz_ttt xyz
drug_clm drug_clm_test
fee_sch fee_sch_test
;
run;
data a1;
input all $26. new_all $30.;
cards;
from abc.xyz_ttt d2 left from abc.xyz d2 left
D1.Xwlk,abc.xyz_TTT left D1.xwlk,abc.xyz left
d1.x,abc.map_clms,d2.dos d1.x,abc.map_clms,d2.dos
ABC.XYZ_Ttt left join d1 ABC.xyz left join d1
,tt.drug_CLM, tt.Xyz_ttt ,tt.drug_clm_test, tt.xyz
d3.DOS,t2.fee_SCH,tt.day fd3.DOS,t2.fee_sch_test,tt.day
;
run;
I'm assuming that you want to transform column all into column new_all, using the values from the a0 data set to describe/control the transformation.
%macro do_it;
* Set up some macro variable arrays to hold the from/to pairs;
data _null_;
set a0 end=end;
call symput("sch" || _n_, sch);
call symput("rep" || _n_, rep);
if end then call symput("max", _n_);
run;
* Process the data;
data want;
length new_all_new $ 200;
set a1;
* Copy the incoming value to the output;
new_all_new = all;
* Apply each of the transformations in turn;
%do i = 1 %to &max;
new_all_new = tranwrd(new_all_new, "&&sch&i", "&&rep&i");
%end;
* Did we get the expected value?;
if new_all_new ne new_all then do;
put "ERROR: Did not get expected value: " all= new_all= new_all_new=;
end;
run;
%mend;
%do_it;
The above code should be pretty close, though I'm unable to test it at the moment. This code is case-sensitive; your expected data suggests that you want to apply the transformations case-insensitively, whilst also preserving the case of the rest of the string. That's a little trickier to implement; if it's really a requirement, a regex search and replace (prxparse("s/&&sch&i/&&rep&i/");) might be the best approach.
There's also the issue that you want to replace 'map_clm' but not 'map_clms', which also suggests regexes might be the cleanest solution.
In any case, this code gives a reasonable starting point for you to work from, I think. It's great that you have built-in expected values to test against.
Are you really modifying SQL code programatically?
case when t1.all CONTAINS t1.sch
then t1.rep
end
If you skip 'else' statement, you'll get missing values (null) for new column if the condition is not satisfied. if you want to keep t1.all values, you have to add else t1.all statement before end.
Related
So I have a vector of search terms, and my main data set. My goal is to create an indicator for each observation in my main data set where variable1 includes at least one of the search terms. Both the search terms and variable1 are character variables.
Currently, I am trying to use a macro to iterate through the search terms, and for each search term, indicate if it is in the variable1. I do not care which search term triggered the match, I just care that there was a match (hence I only need 1 indicator variable at the end).
I am a novice when it comes to using SAS macros and loops, but have tried searching and piecing together code from some online sites, unfortunately, when I run it, it does nothing, not even give me an error.
I have put the code I am trying to run below.
*for example, I am just testing on one of the SASHELP data sets;
*I take the first five team names to create a search list;
data terms; set sashelp.baseball (obs=5);
search_term = substr(team,1,3);
keep search_term;;
run;
*I will be searching through the baseball data set;
data test; set sashelp.baseball;
run;
%macro search;
%local i name_list next_name;
proc SQL;
select distinct search_term into : name_list separated by ' ' from work.terms;
quit;
%let i=1;
%do %while (%scan(&name_list, &i) ne );
%let next_name = %scan(&name_list, &i);
*I think one of my issues is here. I try to loop through the list, and use the find command to find the next_name and if it is in the variable, then I should get a non-zero value returned;
data test; set test;
indicator = index(team,&next_name);
run;
%let i = %eval(&i + 1);
%end;
%mend;
Thanks
Here's the temporary array solution which is fully data driven.
Store the number of terms in a macro variable to assign the length of arrays
Load terms to search into a temporary array
Loop through for each word and search the terms
Exit loop if you find the term to help speed up the process
/*1*/
proc sql noprint;
select count(*) into :num_search_terms from terms;
quit;
%put &num_search_terms.;
data flagged;
*declare array;
array _search(&num_search_terms.) $ _temporary_;
/*2*/
*load array into memory;
if _n_ = 1 then do j=1 to &num_search_terms.;
set terms;
_search(j) = search_term;
end;
set test;
*set flag to 0 for initial start;
flag = 0;
/*3*/
*loop through and craete flag;
do i=1 to &num_search_terms. while(flag=0); /*4*/
if find(team, _search(i), 'it')>0 then flag=1;
end;
drop i j search_term ;
run;
Not sure I totally understand what you are trying to do but if you want to add a new binary variable that indicates if any of the substrings are found just use code like:
data want;
set have;
indicator = index(term,'string1') or index(term,'string2')
... or index(term,'string27') ;
run;
Not sure what a "vector" would be but if you had the list of terms in a dataset you could easily generate that code from the data. And then use %include to add it to your program.
filename code temp;
data _null_;
set term_list end=eof;
file code ;
if _n_ =1 then put 'indicator=' # ;
else put ' or ' #;
put 'index(term,' string :$quote. ')' #;
if eof then put ';' ;
run;
data want;
set have;
%include code / source2;
run;
If you did want to think about creating a macro to generate code like that then the parameters to the macro might be the two input dataset names, the two input variable names and the output variable name.
Have a variable called var1 that has two kinds of values (both as character strings). One is "ND" the other is a number out of 0-100, as a string. I want to convert "ND" to 0 and the character string to a numeric value, for example 1(character) to 1(numeric).
Here's my code attempt:
data cleaned_up(drop = exam_1);
set dataset.df(rename=(exam1=exam_1));
select (exam1);
when ('ND') do;
exam1 = 0;
end;
when ;
exam1 = input(exam_1,2.);
end;
otherwise;
end;
Clearly not working. What am I doing wrong?
A couple of problems with your code. Putting the rename statement as a dataset option against the input dataset will perform the rename before the data is read in. Therefore exam1 won't exist as it is now called exam_1. This will still be defined as a character column, so the input function won't work.
You need to keep the existing column, create a new numeric column to do the conversion, then drop the old column and rename the new one. This can be done as a dataset option against the output dataset.
The tranwrd function will replace all occurrences of 'ND' to '0', then using input with the best12 informat will read in all the data as numbers. You don't have to specify the length when reading numbers (i.e. 2. for 2 digits, 3. for 3 digits etc).
data cleaned_up (drop=exam1 rename=(exam_1=exam1));
set df;
exam_1 = input(tranwrd(exam1,'ND','0'),best12.);
run;
You are using select(exam1) while it should be select(exam_1). You can use select for this purpose, but I think simple if condition can solve this much easier:
data test;
length source $32;
do source='99', '34.5', '105', 'ND';
output;
end;
run;
data result(drop = convertedValue);
set test;
if (source eq 'ND') then do;
result = 0;
end;
else do;
convertedValue = input(source,??best.);
if not missing(convertedValue) then do;
if (0 <= round(convertedValue, 1E-12) <= 100) then do;
result = convertedValue;
end;
end;
end;
run;
input(source,??best.) tries to convert source to number and if it fails (e.g. values contains some word), it does not print an error and simply continues execution.
round(convertedValue,1E-12) is used to avoid precision error during the comparison. If you want to do it absolutely safely you have to use something like
if (0 < round(convertedValue,1E-12) < 100
or abs(round(convertedValue,1E-12)) < 1E-10
or abs(round(convertedValue-100,1E-12)) < 1E-10
)
Try to use ifc function then convert to numeric variable.
data have;
input x $3.;
_x=input(ifc(x='ND','0',x),best12.);
cards;
3
10
ND
;
My data is more than 70,000. I have more than 50 variables. (Var1 to Var50). In each variable, there are about about 30 groups (I'll use a to z). I am trying to get a selection of data using if statements. I'd like to select every data with the same group. Eg data in var 1 to 30 with a, data with var 1 to 30 in b.
I seem to be writing
If (Var1="a" and Var2="a" and Var3="a" and Var4="a" and all the way to var50=
"a") or (Var1="b" and Var2="a" and Var3="b" and Var4="b" and all the way to var50=
"b")...
How do I consolidate? I tried using an array but it didnt work and i was not sure if arrays work in the IF and then statement.
IF (VAR2="A" or VAR2="B" or VAR2="C" or VAR2="D"
or VAR3="A" or VAR3="B" or VAR3="C" or VAR3="D"
or VAR4="A" or VAR4="B" or VAR4="C" or VAR4="D"
or VAR5="A" or VAR5="B" or VAR5="C" or VAR5="D"
or VAR6="A" or VAR6="B" or VAR6="C" or VAR6="D"
or VAR7="A" or VAR7="B" or VAR7="C" or VAR7="D"
or VAR8="A" or VAR8="B" or VAR8="C" or VAR8="C"
or VAR9="A" or VAR9="B" or VAR9="C" or VAR9="D"
or VAR10="A" or VAR10="B" or I10_D10="C" or VAR10="D"
or VAR12="A" or VAR12="B" or VAR12="C" or VAR12="D"
or VAR13="A" or VAR13="B" or VAR13="C" or VAR13="D"
or VAR14="A" or VAR14="B" or VAR14="C" or VAR14="D"
or VAR15="A" or VAR15="B" or VAR15="C" or VAR15="D"
or VAR6="A" or VAR16="B" or VAR16="C" or VAR16="D"
or VAR17="A" or VAR17="B" or VAR17="C" or VAR17="D"
or VAR18="A" or VAR18="B" or VAR18="C" or VAR18="C"
or VAR19="A" or VAR19="B" or VAR19="C" or I10_D19="D"
or VAR20="A" or VAR20="B" or I10_D20="C" or VAR20="D"
or VAR21="D" or VAR22="A" or VAR22="B" or VAR22="C" or VAR22="D"
or VAR23="A" or VAR23="B" or VAR23="C" or VAR23="D"
or VAR24="A" or VAR24="B" or VAR24="C" or VAR24="D"
or VAR25="A" or VAR25="B" or VAR25="C" or VAR25="D"
or VAR26="A" or VAR26="B" or VAR26="C" or VAR26="D"
or VAR27="A" or VAR27="B" or VAR27="C" or VAR27="D"
or VAR28="A" or VAR28="B" or VAR28="C" or VAR28="C"
or VAR29="A" or VAR29="B" or VAR29="C" or VAR29="D"
or VAR30="A" or VAR30="B" or I10_D30="C" or VAR30="D")
then Group=1; else Group=0;
You probably don't need a macro, however a macro might be faster.
%let value=a;
data want;
set have;
array var[50];
keepit=1;
do i=1 to 50;
keepit = keepit and (var[i]="&value");
if ^keepit then
leave;
end;
if keepit;
drop i keepit;
run;
I create a signal variable and update it's value, it will be false if any value in the var[] array is not the &value. I leave the loop early if we find 1 non-matching value, to make it more efficient.
It's not exactly clear what you want. If you want to avoid checking all variables you can use WHICHC to find if any in a list are A.
X = whichc('a', of var1-var30);
If you want to see what different groups you have across all the variables, I think a big proc freq is what you want:
proc freq data=have noprint;
table var1*var2*var3*var4....*var30*gender*age / list out=table_counts;
run;
And then check the table_counts data set to see if that has what you want.
If neither of these are what you want, you need to add more details to your question. A sample of data and expected output would be perfect.
When I need to search several variables for a particular value what I will do is - combine all variables into one string and then search that string. Like this:
*** CREATE TEST DATA ***;
data have;
infile cards;
input VAR1 $ VAR2 $ VAR3 $ VAR4 $ VAR5 $;
cards;
J J K A M
S U I O P
D D D D D
l m n o a
Q U J C S
;
run;
data want;
set have;
*** USE CATS FUNCTION TO CONCATENATE ALL VAR# INTO ONE VARIABLE ***;
allvar = cats(var1, var2, var3, var4, var5);
*** IF NEEDED, APPLY UPCASE TO CONCATENATED VARIABLE ***;
*allvar = upcase(allvar);
*** USE INDEXC FUNCTION TO SEARCH NEW VARIABLE ***;
if indexc(allvar, "ABCD") > 0 then group = 1;
else group = 0;
run;
I'm not sure if this is exactly what you need, but hopefully this is something you can modify for your particular task.
The code as posted is testing if ANY of a list of variables match ANY of a list of values.
Let's make a simple test dataset.
data have ;
input id (var1-var5) ($);
cards;
1 E F G H I
2 A B C D E
;;;;
Make one array of the values you want to find and one array of the variables you want to check. Loop over the list of variables until you either find one that contains one of the values or you run out of variables to test.
data want ;
set have;
array values (4) $8 _temporary_ ('A' 'B' 'C' 'D');
array vars var1-var5 ;
group=0;
do i=1 to dim(vars) until (group=1);
if vars(i) in values then group=1;
end;
drop i;
run;
You could avoid the array for the list of values if you want.
if vars(i) in ('A' 'B' 'C' 'D') then group=1;
But using the array will allow you to make the loop run over the list of values instead of the list of variables.
do i=1 to dim(values) until (group=1);
if values(i) in vars then group=1;
end;
Which might be important if you wanted to keep the variable i to indicate which value (or variable) was first matched.
Im a new SAS User and I have a small problem
I have one large empty table A with lets say 100 columns that I have created with a simple proc sql; create table
I have another table B with lets say 40 columns and table C with 55 columns.
I want to add these two tables into table A, basically I want a table with 100 columns containing the data from table B & C and I'm doing this with a Union command.
Since I dont have values for all 100 variables I have to set default values.
Lets say I have a column named nourishment in table A, food in table B and has no equivalent in table C. I have rules like "If the data comes from table B then value =xxx if its from table C then Value="DefaultValue"
I'd do this easily with R or python but Im struggling with sas.
I'm using SAS sql commands (a Union command)
How do you set default values ? (for all data types : character, numeric or dateI'm using SAS sql commands )
Dates in SAS are actually just numeric values. Often they have a date format applied to make them readable.
So you could just assign a missing value by default like so:
. as ColumnName
or any default date like so
'17NOV2017'd as ColumnName
. as MyColumnName
SAS can deal with missing values.
Using a specially coded value, such as 'NA', to represent a missing value condition can work but may lead to headaches and extra coding. Recommended read in SAS help: "Working with Missing Values"
The default SAS missing value for numerics (which also includes dates) is period.
. as MyColumnName
SAS also has 27 special missing values for numerics that are expressed as . < character >
.A as MyColumnName
...
.Z as MyColumnName
._ as MyColumnName
The missing value for character variables is a single space
' '
'' empty quote string also works
' ' as does a longer empty string
Rule of thumb: be consistent when coding your missing values.
You can use OPTIONS MISSING to specify what character is shown when a missing value is printed.
OPTIONS MISSING = '*'; * My special representation of missing for this report;
Proc PRINT data=myData;
run;
OPTIONS MISSING = '.'; * Restore to the default;
SAS custom formats can also be used to customize what is printed for missing values.
Proc FORMAT;
value MissingN
. = 'N/A'
.N = 'Special N/A different than regular N/A' /* for .N */
;
value $MissingC
' ' = 'N/A'
;
value SillyChristmasStocking
.C = 'Bad'
.O = 'children'
.A = 'get'
.L = 'No toys'
;
The token after the value keyword can be any new valid SAS name that you want to used for your format name.
Proc PRINT data=myData;
format myColumnName MissingN.;
format name $MissingC.;
format behaviour SillyChristmasStocking.;
run;
As for your character missing value conditions, I would continue to use " " or ' '
You mention UNION which is a SQL feature. In SQL, JOIN also occur, perhaps more often then UNION. When JOINing and values from two source columns collide, you will want to use either COALESCE() function or CASE
statements to select the non-missing value.
I would not recommend using UNION in PROC SQL at any point in your SAS usage. UNION is almost always inferior to a simple data step, or a data step view.
That's because the data step seamlessly handles issues like differing variables on different tables. SAS is quite comfortable with vertically combining datasets; SQL is always a bit trickier when they're not identical.
data c;
set a b;
run;
That runs whether or not a and b are identical, so long as a and b don't have conflicting variable names (that aren't intended to be in the same column); and if they do, just use the rename dataset option to resolve it.
If you do as the above, and don't use union, you'll get a missing value automatically for those dates.
NFN:
DATA Step
A DATA Step approach for stacking data is the simplest. Use SET to stack the data and array processing to apply your defaults. For example:
data stacked_data;
set
TARGET_TEMPLATE (obs = 0)
ONE
TWO
;
array allchar _character_;
array allnum _numeric_;
array dates d1-d5;
do over allchar; if missing(allchar) then allchar = '*UNKNOWN*'; end;
do over allnum; if missing(allnum) then allnum = -995; end;
do over dates; if missing(dates) then dates='01NOV1971'd; end;
run;
A subtle issue is that any missing values in ONE or TWO will be replaced with the default value.
Proc SQL
In Proc SQL you will want to create a single row table containing the default values for A. That table can be joined to the union of B and C. The join select will involve coalesce() in order to choose the predefined default value when a column is not from B or C.
For example, suppose you have an empty (zero rows), richly columned, target table (your A) acting as a template:
data TARGET_TEMPLATE;
length _n_ 8;
length a1-a5 $25 d1-d5 4 x1-x20 y1-y20 z1-z20 p1-p20 q1-q20 r1-r20 8;
call missing (of _all_);
format d1-d5 yymmdd10.;
stop;
run;
Because Proc SQL does not provide syntax for a default constraint you need to create a table of your own defaults. This is probably easiest with DATA Step:
data TARGET_DEFAULTS;
if 0 then set TARGET_TEMPLATE (obs=0); * prep pdv to match TARGET;
array allchar _character_ (1000 * '*UNKNOWN*');
array allnum _numeric_ (1000 * -995);
array d d1-d5 (5 * '01NOV1971'd); * override the allnum array initialization;
output;
stop;
run;
Here is some generated demo data, ONE and TWO, that correspond to your B and C:
data ONE;
if 0 then set TARGET_TEMPLATE (obs=0); * prep pdv of demo data to match TARGET;
do _n_ = 1 to 100;
array a a1 a3 a5;
array num x: y: z:;
array d d1 d2;
do over a; a = catx (' ', 'ONE', _n_, _i_); end;
do over num; num = 1000 + _n_ + _i_; end;
retain foodate '01jan1975'd;
do over d; d=foodate; foodate+1; end;
output;
end;
keep a1 a3 a5 x: y: z: d1 d2; * keep the disparate columns that were populated;
run;
data TWO;
if 0 then set TARGET_TEMPLATE (obs=0); * prep pdv of demo data to match TARGET;
do _n_ = 1 to 200;
array a a1 a2 a3;
array num x5 y5 z5 p: q: r:;
array d d1 d2;
do over a; a = catx (' ', 'TWO', _n_, _i_); end;
do over num; num = 20000 + _n_*10 + _i_; end;
retain foodate '01jan1985'd;
do over d; d=foodate; foodate+1; end;
output;
end;
keep a1 a2 a3 x5 y5 z5 p: q: r:; * keep the disparate columns that were populated;
run;
A stacking of A, B and C is simple SQL but does not introduce target specific default values:
proc sql noprint;
* generic UNION stack with SAS missing values (space and dot) for cells
* where ONE and TWO did not contribute any data;
create table stacked_data as
select * from have_data_TEMPLATE %*** empty template first ensures template column order and formats are honored in output data;
outer union corresponding %*** align by column name, do not remove duplicates;
select * from ONE
outer union corresponding
select * from TWO
;
When the stacking is put in a sub-query, it can be joined with the defaults. The choosing of the target default value for each column involves examining DICTIONARY.COLUMNS and generating the SQL source for selecting the coalescence of stack and default.
proc sql noprint;
* codegen select items ;
select cat('coalesce(STACK.',trim(name),',DEFAULT.',trim(name),') as ',trim(name))
into :coalesces separated by ','
from DICTIONARY.COLUMNS
where libname = 'WORK' and memname = 'HAVE_DATA_TEMPLATE' %* dictionary lib and mem name values are always uppercase;
order by npos
;
create table stacked_data_with_defaults as
select * from TARGET_TEMPLATE %*** output honors template;
outer union corresponding
select
source
, &coalesces %*** apply codegen;
from
(
select * from WORK.have_data_TEMPLATE %*** ensure fully columned sub-select that will align with coalesces;
outer union corresponding
select 'one' as source, * from ONE
outer union corresponding
select 'two' as source, * from TWO
) as STACK
join
TARGET_DEFAULTS as DEFAULT
on 1=1
;
quit;
Why would you create an empty dataset? What is it going to be used for? Perhaps you want to use it as a default structure definition? If so and you want to stack B and C and get them in the structure defined by A you could code this way.
data want ;
set a(obs=0) b c ;
run;
Not sure what the purpose would be to have default values. Couldn't you use formats if you want missing values to display in special ways?
Or you could create code to default values and perhaps just %include it or wrap the logic into a macro. So it you had a code file name 'defaults.sas' with lines like this.
startdate=coalesce(startdate,'01JAN2013'd);
gender=coalescec(gender,'UNKNOWN');
Then your little program to make a new dataset that looks like A and uses the data from B and C would look like this.
data want ;
set a(obs=0) b c ;
%include 'defaults.sas';
run;
If you really did want to aggregate the records into some large dataset then perhaps you want to use PROC APPEND to add the records once they are created in the right structure.
proc append data=want base=a ;
run;
Is it possible to repeat a data step a number of times (like you might in a %do-%while loop) where the number of repetitions depends on the result of the data step?
I have a data set with numeric variables A. I calculate a new variable result = min(1, A). I would like the average value of result to equal a target and I can get there by scaling variable A by a constant k. That is solve for k where target = average(min(1,A*k)) - where k and target are constants and A is a list.
Here is what I have so far:
filename f0 'C:\Data\numbers.csv';
filename f1 'C:\Data\target.csv';
data myDataSet;
infile f0 dsd dlm=',' missover firstobs=2;
input A;
init_A = A; /* store the initial value of A */
run;
/* read in the target value (1 observation) */
data targets;
infile f1 dsd dlm=',' missover firstobs=2;
input target;
K = 1; * initialise the constant K;
run;
%macro iteration; /* I need to repeat this macro a number of times */
data myDataSet;
retain key 1;
set myDataSet;
set targets point=key;
A = INIT_A * K; /* update the value of A /*
result = min(1, A);
run;
/* calculate average result */
proc sql;
create table estimate as
select avg(result) as estimate0
from myDataSet;
quit;
/* compare estimate0 to target and update K */
data targets;
set targets;
set estimate;
K = K * (target / estimate0);
run;
%mend iteration;
I can get the desired answer by running %iteration a few times, but Ideally I would like to run the iteration until (target - estimate0 < 0.01). Is such a thing possible?
Thanks!
I had a similar problem to this just the other day. The below approach is what I used, you will need to change the loop structure from a for loop to a do while loop (or whatever suits your purposes):
First perform an initial scan of the table to figure out your loop termination conditions and get the number of rows in the table:
data read_once;
set sashelp.class end=eof;
if eof then do;
call symput('number_of_obs', cats(_n_) );
call symput('number_of_times_to_loop', cats(3) );
end;
run;
Make sure results are as expected:
%put &=number_of_obs;
%put &=number_of_times_to_loop;
Loop over the source table again multiple times:
data final;
do loop=1 to &number_of_times_to_loop;
do row=1 to &number_of_obs;
set sashelp.class point=row;
output;
end;
end;
stop; * REQUIRED BECAUSE WE ARE USING POINT=;
run;
Two part answer.
First, it's certainly possible to do what you say. There are some examples of code that works like this available online, if you want a working, useful-code example of iterative macros; for example, David Izrael's seminal Rakinge macro, which performs a rimweighting procedure by iterating over a relatively simple process (proc freqs, basically). This is pretty similar to what you're doing. In the process it looks in the datastep at the various termination criteria, and outputs a macro variable that is the total number of criteria met (as each stratification variable separately needs to meet the termination criterion). It then checks %if that criterion is met, and terminates if so.
The core of this is two things. First, you should have a fixed maximum number of iterations, unless you like infinite loops. That number should be larger than the largest reasonable number you should ever need, often by around a factor of two. Second, you need convergence criteria such that you can terminate the loop if they're met.
For example:
data have;
x=5;
run;
%macro reduce(data=, var=, amount=, target=, iter=20);
data want;
set have;
run;
%let calc=.;
%let _i=0;
%do %until (&calc.=&target. or &_i.=&iter.);
%let _i = %eval(&_i.+1);
data want;
set want;
&var. = &var. - &amount.;
call symputx('calc',&var.);
run;
%end;
%if &calc.=&target. %then %do;
%put &var. reduced to &target. in &_i. iterations.;
%end;
%else %do;
%put &var. not reduced to &target. in &iter. iterations. Try a larger number.;
%end;
%mend reduce;
%reduce(data=have,var=x,amount=1,target=0);
That is a very simple example, but it has all of the same elements. I prefer to use do-until and increment on my own but you can do the opposite also (as %rakinge does). Sadly the macro language doesn't allow for do-by-until like the data step language does. Oh well.
Secondly, you can often do things like this inside a single data step. Even in older versions (9.2 etc.), you can do all of what you ask above in a single data step, though it might look a little clunky. In 9.3+, and particularly 9.4, there are ways to run that proc sql inside the data step and get the result back without waiting for another data step, using RUN_MACRO or DOSUBL and/or the FCMP language. Even something simple, like this:
data have;
initial_a=0.3;
a=0.3;
target=0.5;
output;
initial_a=0.6;
a=0.6;
output;
initial_a=0.8;
a=0.8;
output;
run;
data want;
k=1;
do iter=1 to 20 until (abs(target-estimate0) < 0.001);
do _n_ = 1 to nobs;
if _n_=1 then result_tot=0;
set have nobs=nobs point=_n_;
a=initial_a*k;
result=min(1,a);
result_tot+result;
end;
estimate0 = result_tot/nobs;
k = k * (target/estimate0);
end;
output;
stop;
run;
That does it all in one data step. I'm cheating a bit because I'm writing my own data step iterator, but that's fairly common in this sort of thing, and it is very fast. Macros iterating multiple data steps and proc sql steps will be much slower typically as there is some overhead from each one.