I'd like to replicate and modify specific rows in the table.
before:
xyz_id | letter | Col_1 | ...|
1 | Z | V1 | ... |
2 | Z | V2 | ... |
3 | Z | V3 | ... |
after:
xyz_id | letter | Col_1 | ...|
1 | A | V1.1 | ... |
1 | B | V1.2 | ... |
1 | C | V1.3 | ... |
2 | A | V2.1 | ... |
2 | B | V2.2 | ... |
2 | C | V2.3 | ... |
3 | A | V3.1 | ... |
3 | B | V3.2 | ... |
3 | C | V3.3 | ... |
I've prepared the following code:
data test2;
set test;
array letters {3} $3 _temporary_ ('A', 'B', 'C');
array weights {3} _temporary_ (1,2,3);
/* if xyz_id = '1' */
/* then array weights {3} _temporary_ (1,2,3);*/
/* else if xyz_id = '2'*/
/* then array weights {3} _temporary_ (8,7,6);*/
/* else array weights {3} _temporary_ (1,1,1)*/
do i = 1 to 8;
letter = letters(i);
Col_A = Col_A * weights(i);
output;
end;
drop i;
run;
Now, I'm trying to make weights depend of the letter column (commented code) - but without any success. I also tried:
array weights_1 {3} _temporary_ (1,2,3);
if xyz_id = '1'
then weights = weights_1;
but it didn't work as well.
Any suggestions?
How about
data have;
input xyz_id letter $ Col_1 $;
datalines;
1 Z V1
2 Z V2
3 Z V3
;
data want;
set have;
array letters {3} $3 _temporary_ ('A', 'B', 'C');
array weights {3} _temporary_ (1,2,3);
c = Col_1;
do i = 1 to 3;
letter = letters[i];
Col_1 = catx('.', c, weights[i]);
output;
end;
drop i c;
run;
Need to add an 3D array.
array weights{3,3}
c1_w1-c1_w8
c2_w1-c2_w8
c3_w1-c3_w8
(
0.1 0.1 /*letter 1*/
1 22 23 /*letter 2*/
1 32 33 /*letter 3*/
);
so the final codes is:
data test2;
set test;
array letters {3} $3 _temporary_ ('A', 'B', 'C');
array weights {3} _temporary_ (1,2,3);
if xyz_id = '1'
then weights_dim=1;
else if xyz_id = '2'
then weights_dim=2;
else if xyz_id = '3'
then weights_dim=3;
weight = weights{weights_dim, i};
do i = 1 to 8;
letter = letters(i);
Col_A = Col_A * weight;
output;
end;
drop i;
run;
Related
I'd like to replicate and modify specific rows in the table.
before:
xyz_id | letter | Col_1 | Col_2|
1 | Z | V1 | W1 |
2 | Z | V2 | W2 |
3 | Z | V3 | W3 |
after:
xyz_id | letter | Col_1 | Col_2|
1 | A | V1.1 | W1.1 |
1 | B | V1.1 | W1.1 |
1 | C | V1.1 | W1.1 |
2 | A | V2.1 | W2.1 |
2 | B | V2.1 | W2.1 |
2 | C | V2.1 | W2.1 |
3 | A | V3.1 | W3.1 |
3 | B | V3.1 | W3.1 |
3 | C | V3.1 | W3.1 |
I've prepared the following code:
data test2;
set test;
array letters {8} $8 _temporary_ ('A', 'B', 'C');
array weights {8} _temporary_ (1,2,3);
array nvars {2} Col_1 Col_2;
do i = 1 to 8;
letter = letters(i);
do j=1 to 2;
nvar{j} = nvar{j} * weights(i);
end;
output;
end;
drop i;
run;
but it doesn't work. Any suggestions?
You reference the nvar array in the j loop, but the array is called nvars.
Col_1 and Col_2 are characters (e.g. 'V1'), so you cannot multiply these by a number and expect a valid result.
Your letters and weights arrays do not have enough values defined for the number of elements (3 vs 8).
I have the following table
+-------+--------+---------+
| group | item | value |
+-------+--------+---------+
| 1 | a | 10 |
| 1 | b | 20 |
| 2 | b | 30 |
| 2 | c | 40 |
+-------+--------+---------+
I would like to group the table by group, insert the grouped sum into value, and then ungroup:
+-------+--------+
| item | value |
+-------+--------+
| 1 | 30 |
| a | 10 |
| b | 20 |
| 2 | 70 |
| b | 30 |
| c | 40 |
+-------+--------+
The purpose of the result is to interpret the first column as items a and b belonging to group 1 with sum 30 and items b and c belonging to group 2 with sum 70.
Such a data transformation can be indicative of a reporting requirement more than a useful data structure for downstream processing. Proc REPORT can create output in the form desired.
data have;
infile datalines;
input group $ item $ value ##; datalines;
1 a 10 1 b 20 2 b 30 2 c 40
;
proc report data=have;
column group item value;
define group / order order=data noprint;
break before group / summarize;
compute item;
if missing(item) then item=group;
endcomp;
run;
I assume that both group and item are character variables
data have;
infile datalines firstobs=4 dlm='|';
input group $ item $ value;
datalines;
+-------+--------+---------+
| group | item | value |
+-------+--------+---------+
| 1 | a | 10 |
| 1 | b | 20 |
| 2 | b | 30 |
| 2 | c | 40 |
+-------+--------+---------+
;
data want (keep=group value);
do _N_=1 by 1 until (last.group);
set have;
by group;
v + value;
end;
value = v;output;v=0;
do _N_=1 to _N_;
set have;
group = item;
output;
end;
run;
Asked on SAS communitiesas well , havent gotten a correct response.
https://communities.sas.com/t5/SAS-Programming/Identifying-overlap-medication-use/m-p/628115#M185541
I have a problem similar to the problem in -
https://communities.sas.com/t5/SAS-Programming/Concomitant-drug-medication-use/m-p/339879#M77587
However I have an issue , I have overlapping of same drug as well -
Eg:
+----+------+-----------+-----------+-----------+
| ID | DRUG | START_DT | DAYS_SUPP | END_DT |
+----+------+-----------+-----------+-----------+
| 1 | A | 2/17/2010 | 30 | 3/19/2010 |
| 1 | A | 3/17/2010 | 30 | 4/16/2010 |
| 1 | A | 4/12/2010 | 30 | 5/12/2010 |
| 1 | A | 8/20/2010 | 30 | 9/19/2010 |
| 1 | B | 5/6/2009 | 30 | 6/5/2009 |
+----+------+-----------+-----------+-----------+
Here the three A prescriptions are over lapping .
So using the code in the link gives me combinations like A-A-B
whereas I don't want that.
However I want to account for the overlapping days for drug A. So I want to shift the second row prescription to 3/20/2010 to 4/19/2010. Similarly for 3rd A prescription.
the code I have tried -
data have2;
set have_sorted1;
format NEW_START_DT NEW_END_DT _lagEND_DT date9.;
_lagID = lag(patient_ID);
_lagDRUG = lag(drg_cls);
_lagEND_DT = lag(rx_ed_dt);
if patient_ID = _lagID and drg_cls= _lagDRUG and rx_st_dt <= _lagEND_DT then flag=1;
else flag = 0;
retain NEW_START_DT NEW_END_DT;
if flag=0 then do;
NEW_START_DT = rx_st_dt;
NEW_END_DT = rx_ed_dt;
end;
else do;
New_start_dt = NEW_End_DT + 1;
NEW_END_DT = new_start_dt + DAY_SUPP ;
end;
/* drop flag _:;*/
run;
But even then I get incorrect result -
id Drug drug_start day_supp drug_end New_start New_end
15 A 6-Sep-15 30 5-Oct-15 6-Sep-15 5-Oct-15
15 A 24-Sep-15 90 22-Dec-15 6-Oct-15 4-Jan-16
15 A 6-Dec-15 90 4-Mar-16 5-Jan-16 4-Apr-16
15 A 26-Feb-16 90 25-May-16 5-Apr-16 4-Jul-16
15 A 29-May-16 90 26-Aug-16 29-May-16 26-Aug-16
15 A 7-Dec-16 90 6-Mar-17 7-Dec-16 6-Mar-17
15 A 17-Feb-17 90 17-May-17 7-Mar-17 5-Jun-17
It might be easier to track the 'flag' state implicitly in a shift variable that tracks how many days to shift forward.
Example:
Shift is always applied, but will be zero when no overlap occurs. The prior end, after computation, is tracked in a retained variable. The code does not need to rely on LAG.
data have;
infile cards firstobs=3 dlm='|';
input ID DRUG: $ START_DT: mmddyy10. DAYS_SUPP END_DT: mmddyy10.;
format start_dt end_dt mmddyy10.;
datalines;
| ID | DRUG | START_DT | DAYS_SUPP | END_DT |
+----+------+-----------+-----------+-----------+
| 1 | A | 2/17/2010 | 30 | 3/19/2010 |
| 1 | A | 3/17/2010 | 30 | 4/16/2010 |
| 1 | A | 4/12/2010 | 30 | 5/12/2010 |
| 1 | A | 8/20/2010 | 30 | 9/19/2010 |
| 1 | B | 5/6/2009 | 30 | 6/5/2009 |
;
data want;
set have;
by id drug;
retain shift prior_shifted_end;
select;
when (first.drug) shift = 0;
when (prior_shifted_end > start_dt) shift = prior_shifted_end - start_dt + 1;
otherwise shift = 0;
end;
original_start_dt = start_dt;
original_end_dt = end_dt;
start_dt + shift;
end_dt + shift;
prior_shifted_end = end_dt;
format prior: original: mmddyy10.;
run;
My table has some leading and trailing observations that I am trying to remove. I want to remove the rows that come before every 'begin' event and after every 'end' event for every single group. The table resembles the below:
| Time | Group | Event | Value |
| 1 | 1 | NA | 0 |
| 2 | 1 | NA | 0 |
| 3 | 1 | Begin | 1.1 |
| 4 | 1 | NA | 1.2 |
| 5 | 1 | NA | 1.3 |
| 6 | 1 | End | 1.4 |
| 7 | 1 | NA | 0 |
| 1 | 2 | NA | 0 |
| 2 | 2 | Begin | 1.1 |
| 3 | 2 | NA | 1.2 |
| 4 | 2 | End | 1.3 |
| 5 | 2 | NA | 1.4 |
On the presumption that the incoming data is already sorted and that there are zero or more serially bounded ranges of Begin to End within each group:
data want;
do until (last.group);
set have;
by group time;
if event = 'Begin' then _keeprow = 1;
if _keeprow then output;
if event = 'End' then _keeprow = 0;
end;
drop _keeprow;
end;
I have came out an easy way but will be limited by the actual data size.
data have;
input Time Group Event $ Value ;
datalines;
1 1 NA 0
2 1 NA 0
3 1 Begin 1.1
4 1 NA 1.2
5 1 NA 1.3
6 1 End 1.4
7 1 NA 0
1 2 NA 0
2 2 Begin 1.1
3 2 NA 1.2
4 2 End 1.3
5 2 NA 1.4
;
run;
proc sort data = have;
by group time;
run;
data have1;
set have;
count + 1;
by group;
if first.group then count = -100;
if event = 'Begin' then count = 0;
if event = 'End' then count = 100;
if count < 0 or count >100 then delete;
run;
The current code could be applied to the small size data if you have less than 100 observations between 'Begin' and 'End' and less than 100 observations before 'Begin'. You can adjust the initial count value according to the true data size.
one way to do is
data have;
input Time Group Event $ Value ;
datalines;
1 1 NA 0
2 1 NA 0
3 1 Begin 1.1
4 1 NA 1.2
5 1 NA 1.3
6 1 End 1.4
7 1 NA 0
1 2 NA 0
2 2 Begin 1.1
3 2 NA 1.2
4 2 End 1.3
5 2 NA 1.4
;
data have2(keep= Group min_var max_var);
set have;
by group;
retain min_var max_var;
if trim(Event)= "Begin" then min_var =_n_ ;
if trim(Event)= "End" then max_var =_n_;
if last.group;
run;
data want;
merge have have2;
by group;
if _n_ ge min_var and _n_ le max_var ;
drop min_var max_var;
run;
I have a set of multiple choice responses from a survey with 45 questions, and I've placed the correct responses as my first observation in the dataset.
In my DATA step I would like to set values to 0 or 1depending on whether the variable in each observation matches the same variable in the first observation, I want to replace the response letter (A-D) with the 0 or 1 in the dataset, how do I go about doing that comparison?
I'm not doing any grouping, so I believe I can access the first row using First.x, but I'm not sure how to compare that across each variable(answer1-answer45).
| Id | answer1 | answer2 | ...through answer 45
|:-------------|---------:|
| KEY | A | B |
| 2 | A | C |
| 3 | C | D |
| 4 | A | B |
| 5 | D | C |
| 6 | B | B |
Should become:
| Id | answer1 | answer2 | ...through answer 45
|:-------------|---------:|
| KEY | A | B |
| 2 | 1 | 0 |
| 3 | 0 | 0 |
| 4 | 1 | 1 |
| 5 | 0 | 0 |
| 6 | 0 | 1 |
Current code for reading in the data:
DATA TEST(drop=name fill answer0);
INFILE SCORES DSD firstobs=2;
length id $4;
length answer1-answer150 $1;
INPUT name $ fill id $ (answer0-answer150) ($);
RUN;
Thanks in advance!
Here's how I might do it. Create a data set to PROC COMPARE the KEY to the observed. Then you have X for not matching key and missing for matched. You can then use PROC TRANSREG to score the 'X.' to 01. PROC TRANSREG also creates macro variables which contain the names of the new variables and the number.
From log NOTE: _TRGINDN=2 _TRGIND=answer1D answer2D
data questions;
input id:$3. (answer1-answer2)(:$1.);
cards;
KEY A B
2 A C
3 C D
4 A B
5 D C
6 B B
;;;;
run;
data key;
if _n_ eq 1 then set questions(obs=1);
set questions(keep=id firstobs=2);
run;
proc compare base=key compare=questions(firstobs=2) out=comp outdiff noprint;
id id;
run;
options validvarname=v7;
proc transreg design data=comp(drop=_type_ type=data);
id id;
model class(answer:) / noint;
output out=scored(drop=intercept _:);
run;
%put NOTE: &=_TRGINDN &=_TRGIND;
I don't have my SAS license here at home, so I can't actually test this code. I'll give it me best shot, though ...
First, I'd keep my correct answers in a separate table, and then merge it with the answers from the respondents. That also makes the solution scalable, should you have more multiple choice solutions and answers in the same table, since you'd be joining on the assignment ID as well.
Now, import all your correct answers to a table answers_correct with column names answer_correct1-answer_correct45.
Then, merge the two tables and determine the outcome for each question.
DATA outcome;
MERGE answers answers_correct;
* We will not be using any BY.;
* If you later add more questionnaires, merge BY the questionnaire ID;
ARRAY answer(*) answer1-answer45;
ARRAY answer_correct(*) answer_correct1-answer_correct45;
LENGTH result1-result45 $1;
ARRAY result(*) result1-result45;
DROP i;
FOR i = 1 TO DIM(answer);
IF answer(i) = answer_correct(i) THEN result(i) = '1';
ELSE result(i) = '0';
END;
RUN;