I have a question regarding recursive/cumulative addition of a particular column for example: Click on example
How do I write this in SAS code which generates cumalitive addition with respect to column. Please help me with this.
Thank you in Advance
Example
use sum statement
data have;
input val;
datalines;
1
2
3
;
data want;
set have;
newval+val;
run;
Using Retain functionality.
You can reuse the code below as basis for any iterative/cumulative calculations.
data have;
input A;
datalines;
1
2
3
;
run;
data want;
set have;
Retain B;
/* If condition to initialize B only once, _N_ is the current row number */
if _N_= 1 then B=0;
B=B+A;
/* put statement will print the table in the log */
put _all_;
run;
Output:
A=1 B=1 _N_=1
A=2 B=3 _N_=2
A=3 B=6 _N_=3
Related
I need some help in trying to execute a comparison of rows within different ID variable groups, all in a single dataset.
That is, if there is any duplicate observation within two or more ID groups, then I'd like to delete the observation entirely.
I want to identify any duplicates between rows of different groups and delete the observation entirely.
For example:
ID Value
1 A
1 B
1 C
1 D
1 D
2 A
2 C
3 A
3 Z
3 B
The output I desire is:
ID Value
1 D
3 Z
I have looked online extensively, and tried a few things. I thought I could mark the duplicates with a flag and then delete based off that flag.
The flagging code is:
data have;
set want;
flag = first.ID ne last.ID;
run;
This worked for some cases, but I also got duplicates within the same value group flagged.
Therefore the first observation got deleted:
ID Value
3 Z
I also tried:
data have;
set want;
flag = first.ID ne last.ID and first.value ne last.value;
run;
but that didn't mark any duplicates at all.
I would appreciate any help.
Please let me know if any other information is required.
Thanks.
Here's a fairly simple way to do it: sort and deduplicate by value + ID, then keep only rows with values that occur only for a single ID.
data have;
input ID Value $;
cards;
1 A
1 B
1 C
1 D
1 D
2 A
2 C
3 A
3 Z
3 B
;
run;
proc sort data = have nodupkey;
by value ID;
run;
data want;
set have;
by value;
if first.value and last.value;
run;
proc sql version:
proc sql;
create table want as
select distinct ID, value from have
group by value
having count(distinct id) =1
order by id
;
quit;
This is my interpretation of the requirements.
Find levels of value that occur in only 1 ID.
data have;
input ID Value:$1.;
cards;
1 A
1 B
1 C
1 D
1 D
2 A
2 C
3 A
3 Z
3 B
;;;;
proc print;
proc summary nway; /*Dedup*/
class id value;
output out=dedup(drop=_type_ rename=(_freq_=occr));
run;
proc print;
run;
proc summary nway;
class value;
output out=want(drop=_type_) idgroup(out[1](id)=) sum(occr)=;
run;
proc print;
where _freq_ eq 1;
run;
proc print;
run;
A slightly different approach can use a hash object to track the unique values belonging to a single group.
data have; input
ID Value:& $1.; datalines;
1 A
1 B
1 C
1 D
1 D
2 A
2 C
3 A
3 Z
3 B
run;
proc delete data=want;
proc ds2;
data _null_;
declare package hash values();
declare package hash discards();
declare double idhave;
method init();
values.keys([value]);
values.data([value ID]);
values.defineDone();
discards.keys([value]);
discards.defineDone();
end;
method run();
set have;
if discards.find() ne 0 then do;
idhave = id;
if values.find() eq 0 and id ne idhave then do;
values.remove();
discards.add();
end;
else
values.add();
end;
end;
method term();
values.output('want');
end;
enddata;
run;
quit;
%let syslast = want;
I think what you should do is:
data want;
set have;
by ID value;
if not first.value then flag = 1;
else flag = 0;
run;
This basically flags all occurrences of a value except the first for a given ID.
Also I changed want and have assuming you create what you want from what you have. Also I assume have is sorted by ID value order.
Also this will only flag 1 D above. Not 3 Z
Additional Inputs
Can't you just do a sort to get rid of the duplicates:
proc sort data = have out = want nodupkey dupout = not_wanted;
by ID value;
run;
So if you process the observations by VALUE levels (instead of by ID levels) then you just need keep track of whether any ID is ever different than the first one.
data want ;
do until (last.value);
set have ;
by value ;
if first.value then first_id=id;
else if id ne first_id then remapped=1;
end;
if not remapped;
keep value id;
run;
Essentially I need to reorder my data set.
The data consists of 4 columns, one for each treatment group. I'm trying to run a simple 1-way anova in SAS but I don't know how to reorder the data so that there are two columns, one with the responses and one with the treatments.
Here is some example code to create example data sets.
data have;
input A B C D;
cards;
26.72 37.42 11.23 44.33
28.58 56.46 29.63 76.86
29.71 51.91 . .
;
run;
data want;
input Response Treatment $;
cards;
26.72 A
28.58 A
29.71 A
37.42 B
56.46 B
51.91 B
11.23 C
29.63 C
44.33 D
76.86 D
;
run;
I'm sure this is a very simple solution but I didn't see the same thing asked elsewhere on the site. I'm typically an R user but have to use SAS for this analysis so I could be looking for the wrong keywords.
I have used proc transpose for this, see below
/*1. create row numbers for each obs*/
data have1;
set have;
if _n_=1 then row=1;
else row+1;
run;
proc sort data=have1; by row; run;
/*Transpose the dataset by row number*/
proc transpose data=have1 out=want0;
by row;
run;
/*Final dataset by removing missing values*/
data want;
set want0;
drop row;
if COL1=. then delete;
rename _NAME_=Response
COL1=Treatment;
run;
proc sort data=want; by Response; run;
proc print data=want; run;
If that is your data for which you must use SAS just read so that you get the structure required for ANOVA.
data have;
do rep=1 to 3;
do trt='A','B','C','D';
input y #;
output;
end;
end;
cards;
26.72 37.42 11.23 44.33
28.58 56.46 29.63 76.86
29.71 51.91 . .
;;;;
run;
proc print;
run;
My dataset(named A) has columns : A B C. I want to add new observations (new row) at the end of it with the values: 1 2 3. There must be an easy way to do that?
Just use a proc sql and insert statement.
proc sql;
insert into table_name (A,B,C) values (1,2,3);
quit;
Here are 5 more ways of doing this:
/*Some dummy data*/
data have;
input A B C;
cards;
4 5 6
;
run;
data new_rows;
input A B C;
cards;
1 2 3
6 7 8
;
run;
/* Modifying in place - more efficient, increased risk of data loss */
proc sql;
insert into have
select * from new_rows;
quit;
proc append base = have data = new_rows;
run;
data have;
modify have;
set new_rows;
output;
run;
/* Overwriting - less efficient, no harm if interrupted. */
data have;
set have new_rows;
run;
data have;
update have new_rows;
/*N.B. assumes that A B C form a set of unique keys and that the datasets are sorted*/
by A B C;
run;
Just curious is this code:
data Bla.SomeGreatNewDataset;
set WORK.InputTempDataset;
by SomeColumnName;
if first.SomeColumnName then output;
else delete;
run;
the same as:
data Bla.SomeGreatNewDataset;
set WORK.InputTempDataset;
by SomeColumnName;
if not missing(first.SomeColumnName) then output;
else delete;
run;
in other words does:
if first.SomeColumnName
just check if SomeColumnName does not contain a missing value?
Short answer, no.
BY Group processing with first.var and last.var operates on the distinct values of the variable. A missing value is a valid missing value.
first.var and last.var are Boolean values, either 1 or 0. You code outputs just the first record for each unique value of SomeColumnName.
Note, the data needs to either be sorted by SomeColumnName or have an index on that column.
Here is an example:
data have;
input x;
datalines;
1
2
2
.
3
3
3
;
run;
proc sort data=have;
by x;
run;
data want;
set have;
by x;
if first.x;
run;
proc print data=want;
run;
Produces:
Obs x
1 .
2 1
3 2
4 3
I would like to turn the following long dataset:
data test;
input Id Injury $;
datalines;
1 Ankle
1 Shoulder
2 Ankle
2 Head
3 Head
3 Shoulder
;
run;
Into a wide dataset that looks like this:
ID Ankle Shoulder Head
1 1 1 0
2 1 0 1
3 0 1 1'
This answer seemed the most relevant but was falling over at the proc freq stage (my real dataset is around 1 million records, and has around 30 injury types):
Creating dummy variables from multiple strings in the same row
Additional help: https://communities.sas.com/t5/SAS-Statistical-Procedures/Possible-to-create-dummy-variables-with-proc-transpose/td-p/235140
Thanks for the help!
Here's a basic method that should work easily, even with several million records.
First you sort the data, then add in a count to create the 1 variable. Next you use PROC TRANSPOSE to flip the data from long to wide. Then fill in the missing values with a 0. This is a fully dynamic method, it doesn't matter how many different Injury types you have or how many records per person. There are other methods that are probably shorter code, but I think this is simple and easy to understand and modify if required.
data test;
input Id Injury $;
datalines;
1 Ankle
1 Shoulder
2 Ankle
2 Head
3 Head
3 Shoulder
;
run;
proc sort data=test;
by id injury;
run;
data test2;
set test;
count=1;
run;
proc transpose data=test2 out=want prefix=Injury_;
by id;
var count;
id injury;
idlabel injury;
run;
data want;
set want;
array inj(*) injury_:;
do i=1 to dim(inj);
if inj(i)=. then inj(i) = 0;
end;
drop _name_ i;
run;
Here's a solution involving only two steps... Just make sure your data is sorted by id first (the injury column doesn't need to be sorted).
First, create a macro variable containing the list of injuries
proc sql noprint;
select distinct injury
into :injuries separated by " "
from have
order by injury;
quit;
Then, let RETAIN do the magic -- no transposition needed!
data want(drop=i injury);
set have;
by id;
format &injuries 1.;
retain &injuries;
array injuries(*) &injuries;
if first.id then do i = 1 to dim(injuries);
injuries(i) = 0;
end;
do i = 1 to dim(injuries);
if injury = scan("&injuries",i) then injuries(i) = 1;
end;
if last.id then output;
run;
EDIT
Following OP's question in the comments, here's how we could use codes and labels for injuries. It could be done directly in the last data step with a label statement, but to minimize hard-coding, I'll assume the labels are entered into a sas dataset.
1 - Define Labels:
data myLabels;
infile datalines dlm="|" truncover;
informat injury $12. labl $24.;
input injury labl;
datalines;
S460|Acute meniscal tear, medial
S520|Head trauma
;
2 - Add a new query to the existing proc sql step to prepare the label assignment.
proc sql noprint;
/* Existing query */
select distinct injury
into :injuries separated by " "
from have
order by injury;
/* New query */
select catx("=",injury,quote(trim(labl)))
into :labls separated by " "
from myLabels;
quit;
3 - Then, at the end of the data want step, just add a label statement.
data want(drop=i injury);
set have;
by id;
/* ...same as before... */
* Add labels;
label &labls;
run;
And that should do it!