I am trying to convert a categorical variable (Product) in binary and then want to know how many products per customer.
data is in the following format:
ID Product
C1 A
C1 B
C2 A
C3 B
C4 A
The code I am using for converting category to binary
IF PRODUCT="A" THEN PROD_A =1 ; ELSE PROD_A=0;
IF PRODUCT="B" THEN PROD_B =1 ; ELSE PROD_B=0;
TOT_PROD = SUM(PROD_A, PROD_B);
But when I count no. of product it gives me '1' for all customer and I am expecting 1 or 2.
I have tried
TOT_PROD = PROD_A + PROD_B;
but I get the same results
This is all inside one datastep, correct? If so you're processing only one line at a time. For each individual line the only possible values for PROD_A and PROD_B are one or zero. You need an aggregate function. For example, if your dataset is named PRODUCTS:
DATA X;
SET PRODUCTS;
IF PRODUCT="A" THEN PROD_A = 1 ; ELSE PROD_A=0;
IF PRODUCT="B" THEN PROD_B = 1 ; ELSE PROD_B=0;
TOT_PROD = SUM(PROD_A, PROD_B);
RUN;
(TOT_PROD will always be equal to 1 in X, but never mind for now).
Now sum them up:
proc sql;
create table prod_totals as
select product, sum(tot_prod) as total_products
from x
group by product;
quit;
More simply just skip the data step:
proc sql;
create table prod_totals as
select product, count(*) as total_products
from products
group by product;
quit;
Or use PROC SUMMARIZE or PROC MEANS instead of PROC SQL.
I have assumed you only want 1 record output per id.
In the solutions below I have employed the DOW-Loop (DO-Whitlock).
If you wanted prod_a and prod_b just to help with the totals and if they're not required in the output, then you could use something like:
data want;
do until(last.id);
set have;
by id;
tot_prod=sum(tot_prod,product='A',product='B');
end;
run;
If you need prod_a and prod_b in the output, then you could use:
data want;
do until(last.id);
set have;
by id;
prod_a=(product='A');
prod_b=(product='B');
tot_prod=sum(tot_prod,prod_a,prod_b);
end;
run;
In both data steps the last product per id will be output along with the other variables and in the case of the 2nd data step example the last prod_a & prod_b per id will also be output.
To do this in the data step, you need retain. Make sure you've sorted the dataset by id first.
data prod_totals;
set products;
by ID;
retain prod_a prod_b;
if first.id then do; *initialize to zero for each new ID;
prod_a=0; prod_b=0;
end;
if product='A' then prod_a=1; *set to 1 for each one found;
else if product='B' then prod_b=1;
if last.id then do; *for last record in each ID, output and sum total;
total_products=sum(prod_a,prod_b);
output;
end;
keep id prod_a prod_b total_products;
run;
Related
I am trying to collapse my multiple rows of binary variables into a single row per patient id as depicted in my illustration. Could someone please help me with the SAS code to do this? Thanks
If the rule is that to set it to 1 if it is ever 1 then take the MAX. If the rule is to set it to one only if all of them are one then take the MIN.
proc summary data=have nway ;
by id;
output out=want max= ;
run;
Update trick
data want;
update have(obs=0) have;
by id;
run;
Or
proc sql;
create table want as
select ID, max('2018'n) as Y2018, max('2019'n) as Y2019, max('2020'n) as Y2020
from have
group by ID
order by ID;
quit;
Untested because you provided data as images, please post as text, preferably as a data step.
Here is a data step-based solution. Certainly more complex than the above answers, but it does show ways you can use arrays, first. and last. processing, and the retain statement.
Use a retained temporary array to hold the values of 2018-2020 until the last observation of each id group. On the last value of each id, check if each held value is 1 and set each value of the year to a 1 or 0.
data want;
set have;
by id;
array year[3] '2018'n--'2020'n;
array hold[3] _TEMPORARY_;
retain hold;
if(first.id) then call missing(of hold[*]);
do i = 1 to dim(year);
if(year[i] = 1) then hold[i] = 1;
end;
if(last.id) then do;
do i = 1 to dim(year);
year[i] = (hold[i] = 1);
end;
output;
end;
drop i;
run;
I have a work table in SAS and I want to move the last row of the table to 2nd last row. Is it possible doing this programmatically? If so, how?
Thanks in advance
Use the SET option POINT= to read from specific rows based on a serial position.
data have;
do row = 1 to 10;
output;
end;
run;
data want;
do row_index = 1 to row_count-2, row_count, row_count-1;
set have nobs=row_count point=row_index;
output;
end;
STOP;
run;
I think this is what you want
data class;
set sashelp.class nobs=n;
if _N_ = n-1 then delete;
run;
If you don't have an id variable in your dataset, you may create one first. In the following case your dataset is called have:
data temp;
set have;
id + 1;
run;
Then, you may just subtract one from the id variable when it is equal to the max(id) and add one when it is equal to the max(id) minus one. Finally, you order your new dataset by id. This will switch the positions of the two last rows.
proc sql;
create table want as
select
case when id=max(id) then id-1
when id=max(id)-1 then id+1
else id end as id,
*
from temp
order by id;
quit;
If your original dataset already has a variable called id, just replace all id in the code above for the name of a new variable, and it will do what you want.
One more using MODIFY.
data class;
_obs_+1;
set sashelp.class;
run;
data class;
do point=nobs-2;
modify class point=point nobs=nobs;
remove;
output;
end;
stop;
run;
proc print;
run;
Here is a simple example I came up with. There are 3 players here (id is 1,2,3) and each player gets 3 attempts at the game (attempt is 1,2,3).
data have;
infile datalines delimiter=",";
input id attempt score;
datalines;
1,1,100
1,2,200
2,1,150
3,1,60
;
run;
I would like to add in rows where the score is missing if they did not play attempt 2 or attempt 3.
data want;
set have;
by id attempt;
* ??? ;
run;
proc print data=have;
run;
The output would look something like this.
1 1 100
1 2 200
1 3 .
2 1 150
2 2 .
2 3 .
3 1 60
3 2 .
3 3 .
How do I go about doing this?
You could solve this by first creating a table where you have the structure you want to see: for each ID three attempts. This structure can then be joined with a 'left join' to your 'have' table to get the actual scores if they exist and missing variable if they don't.
/* Create table with all ids for which the structure needs to be created */
proc sql;
create table ids as
select distinct id from have;
quit;
/* Create table structure with 3 attempts per ID */
data ids (drop = i);
set ids;
do i = 1 to 3;
attempt = i;
output;
end;
run;
/* Join the table structure to the actual scores in the have table */
proc sql;
create table want as
select a.*,
b.score
from ids a left join have b on a.id = b.id and a.attempt = b.attempt;
quit;
A table of possible attempts cross joined with the distinct ids left joined to the data will produce the desired result set.
Example:
data have;
infile datalines delimiter=",";
input id attempt score;
datalines;
1,1,100
1,2,200
2,1,150
3,1,60
;
data attempts;
do attempt = 1 to 3; output; end;
run;
proc sql;
create table want as
select
each_id.id,
each_attempt.attempt,
have.score
from
(select distinct id from have) each_id
cross join
attempts each_attempt
left join
have
on
each_id.id = have.id
& each_attempt.attempt = have.attempt
order by
id, attempt
;
Update: I figured it out.
proc sort data=have;
by id attempt;
data want;
set have (rename=(attempt=orig_attempt score=orig_score));
by id;
** Previous attempt number **;
retain prev;
if first.id then prev = 0;
** If there is a gap between previous attempt and current attempt, output a blank record for each intervening attempt **;
if orig_attempt > prev + 1 then do attempt = prev + 1 to orig_attempt - 1;
score = .;
output;
end;
** Output current attempt **;
attempt = orig_attempt;
score = orig_score;
output;
** If this is the last record and there are more attempts that should be included, output dummy records for them **;
** (Assumes that you know the maximum number of attempts) **;
if last.id & attempt < 3 then do attempt = attempt + 1 to 3;
score = .;
output;
end;
** Update last attempt used in this iteration **;
prev = attempt;
run;
Here is a alternative DATA step, a DOW way:
data want;
do until (last.id);
set have;
by id;
output;
end;
call missing(score);
do attempt = attempt+1 to 3;
output;
end;
run;
If the absent observations are only at the end then you can just use a couple of OUTPUT statements and a DO loop. So write each observation as it is read and if the last one is NOT attempt 3 then add more observations until you get to attempt 3.
data want1;
set have ;
by id;
output;
score=.;
if last.id then do attempt=attempt+1 to 3;
output;
end;
run;
If the absent attempts can appear any where then you need to "look ahead" to see whether the next observations skips any attempts.
data want2;
set have end=eof;
by id ;
if not eof then set have (firstobs=2 keep=attempt rename=(attempt=next));
if last.id then next=3+1;
output;
score=.;
do attempt=attempt+1 to next-1;
output;
end;
drop next;
run;
Suppose I have these data read into SAS:
I would like to list each unique name and the number of months it appeared in the data above to give a data set like this:
I have looked into PROC FREQ, but I think I need to do this in a DATA step, because I would like to be able to create other variables within the new data set and otherwise be able to manipulate the new data.
Data step:
proc sort data=have;
by name month;
run;
data want;
set have;
by name month;
m=month(lag(month));
if first.id then months=1;
else if month(date)^=m then months+1;
if last.id then output;
keep name months;
run;
Pro Sql:
proc sql;
select distinct name,count(distinct(month(month))) as months from have group by name;
quit;
While it's possible to do this in a data step, you wouldn't; you'd use proc freq or similar. Almost every PROC can give you an output dataset (rather than just print to the screen).
PROC FREQ data=sashelp.class;
tables age/out=age_counts noprint;
run;
Then you can use this output dataset (age_counts) as a SET input to another data step to perform your further calculations.
You can also use proc sql to group the variable and count how many are in that group. It might be faster than proc freq depending on how large your data is.
proc sql noprint;
create table counts as
select AGE, count(*) as AGE_CT from sashelp.class
group by AGE;
quit;
If you want to do it in a data step, you can use a Hash Object to hold the counted values:
data have;
do i=1 to 100;
do V = 'a', 'b', 'c';
output;
end;
end;
run;
data _null_;
set have end=last;
if _n_ = 1 then do;
declare hash cnt();
rc = cnt.definekey('v');
rc = cnt.definedata('v','v_cnt');
rc = cnt.definedone();
call missing(v_cnt);
end;
rc = cnt.find();
if rc then do;
v_cnt = 1;
cnt.add();
end;
else do;
v_cnt = v_cnt + 1;
cnt.replace();
end;
if last then
rc = cnt.output(dataset: "want");
run;
This is very efficient as it is a single loop over the data. The WANT data set contains the key and count values.
I'm not very familiar with Do Loops in SAS and was hoping to get some help. I have data that looks like this:
Product A: 1
Product A: 2
Product A: 4
I'd like to transpose (easy) and flag that Product A: 3 is missing, but I need to do this iteratively to the i-th degree since the number of products is large.
If I run the transpose part in SAS, my first column will be 1, second column will be 2, and third column will be 4 - but I'd really like the third column to be missing and the fourth column to be 4.
Any thoughts? Thanks.
Get some sample data:
proc sort data=sashelp.iris out=sorted;
by species;
run;
Determine the largest column we will need to transpose to. Depending on your situation you may just want to hardcode this value using a %let max=somevalue; statement:
proc sql noprint;
select cats(max(sepallength)) into :max from sorted;
quit;
%put &=max;
Transpose the data using a data step:
data want;
set sorted;
by species;
retain _1-_&max;
array a[1:&max] _1-_&max;
if first.species then do;
do cnt = lbound(a) to hbound(a);
a[cnt] = .;
end;
end;
a[sepallength] = sepallength;
if last.species then do;
output;
end;
keep species _1-_&max;
run;
Notice we are defining an array of columns: _1,_2,_3,..._max. This happens in our array statement.
We then use by-group processing to populate these newly created columns for a single species at a time. For each species, on the first record, we clear the array. For each record of the species, we populate the appropriate element of the array. On the final record for the species output the array contents.
You need a way to tell SAS that you have 4 products and the values are 1-4. In this example I create dummy ID with the needed information then transpose using ID statement to name new variables using the value of product.
data product;
input id product ##;
cards;
1 1 1 2 1 4
2 2 2 3
;;;;
run;
proc print;
run;
data productspace;
if 0 then set product;
do product = 1 to 4;
output;
end;
stop;
run;
data productV / view=productV;
set productspace product;
run;
proc transpose data=productV out=wide(where=(not missing(id))) prefix=P;
by id;
var product;
id product;
run;
proc print;
run;