Assume I have a data-set D1 as follows:
ID ATR1 ATR2 ATR3
1 A R W
2 B T X
1 A S Y
2 C T E
3 D U I
1 T R W
2 C X X
I want to create a data-set D2 from this as follows
ID ATR1 ATR2 ATR3
1 A R W
2 C T X
3 D U I
In other words, Data-set D2 consists of unique IDs from D1. For each ID in D2, the values of ATR1-ATR3 are selected as the most frequent (of the respective variable) among the records in D1 with the same ID. For example ID = 1 in D2 has ATR1 = A (most frequent).
I have one solution which is very clumsy. I simply sort copies of the data set `D1' three times (by ID and ATR1 e.g) and remove duplicates. I later merge the three data-sets to get what I want. However, I think there might be an elegant way to do this. I have about 20 such variables in the original data-set.
Thanks
/*
read and restructure so we end up with:
id attr_id value
1 1 A
1 2 R
1 3 W
etc.
*/
data a(keep=id attr_id value);
length value $1;
array attrs_{*} $ 1 attr_1 - attr_3;
infile cards;
input id attr_1 - attr_3;
do attr_id=1 to dim(attrs_);
value = attrs_{attr_id};
output;
end;
cards;
1 A R W
2 B T X
1 A S Y
2 C T E
3 D U I
1 T R W
2 C X X
;
run;
/* calculate frequencies of values per id and attr_id */
proc freq data=a noprint;
tables id*attr_id*value / out=freqs(keep=id attr_id value count);
run;
/* sort so the most frequent value per id and attr_id ends up at the bottom of the group.
if there are ties then it's a matter of luck which value we get */
proc sort data = freqs;
by id attr_id count;
run;
/* read and recreate the original structure. */
data b(keep=id attr_1 - attr_3);
retain attr_1 - attr_3;
array attrs_{*} $ 1 attr_1 - attr_3;
set freqs;
by id attr_id;
if first.id then do;
do i=1 to dim(attrs_);
attrs_{i} = ' ';
end;
end;
if last.attr_id then do;
attrs_{attr_id} = value;
end;
if last.id then do;
output;
end;
run;
Related
In the Data Step of SAS, you get value of a Column by directly using its name, for example, like this,
name = col1;
But for some reason, I want to get value of a column where column is represented by a string. For example, like this,
name = get_value_of_column(cats("col", i))
Is this possible? And if so, how?
The DATA Step functions VVALUE and VVALUEX will return the formatted value of a variable.
VVALUE(<variable-name>) static, a step compilation time interaction
VVALUEX(<expression>) dynamic, a runtime expression resolving to a variable name
The actual value of the variable can be dynamically obtained via a _type_ array scan
Array Scan
data have;
input name $ x y z (s t u) ($) date: yymmdd10.;
format s t u $upcase. date yymmdd10.;
datalines;
x 1 2 3 a b c 2020-10-01
y 2 3 4 b c d 2020-10-02
z 3 4 5 c d e 2020-10-03
s 4 5 6 hi ho silver 2020-10-04
t 5 6 7 aa bb cc 2020-10-05
u 6 7 8 -- ** !! 2020-10-06
date 7 8 9 ppp qqq rrr 2020-10-07
;
data want;
set have;
length u_vvalue name_vvaluex $20.;
u_vvalue = vvalue(u);
name_vvaluex = vvaluex(name);
array nums _numeric_;
array chars _character_;
/* NOTE:
* variable based arrays cause automatic variable _i_ to be in the PDV
* and _i_ will be automatically dropped from output data sets
*/
do _i_ = 1 to dim(nums);
if upcase(name) = upcase(vname(nums(_i_))) then do;
name_numeric_raw = nums(_i_);
leave;
end;
end;
do _i_ = 1 to dim(chars);
if upcase(name) = upcase(vname(chars(_i_))) then do;
name_character_raw = chars(_i_);
leave;
end;
end;
run;
If you perform an 'excessive' amount of dynamic value lookup in your DATA Step a transposition could possibly lead to simpler processing.
I would like to add a new column to a dataset but I am not sure how to do so. My dataset has a variable called KEYVAR (character variable) with three different values. A participant can appear multiple times in my dataset, with each row containing a similar or different value for KEYVAR. What I want to do is create a new variable call NEWVAR that counts how many times a participant has a specific value for KEYVAR; when a participant does not have an observation for that specific value, I want NEWVAR to have a result of zero.
Here's an example of the dataset I would like (in this example, I want to count every instance of "Y" per participants as newvar):
have
PARTICIPANT KEYVAR
A Y
A N
B Y
B Y
B Y
C W
C N
C W
D Y
D N
D N
D Y
D W
want
PARTICIPANT KEYVAR NEWVAR
A Y 1
A N 1
B Y 3
B Y 3
B Y 3
C W 0
C N 0
C W 0
D Y 2
D N 2
D N 2
D Y 2
D W 2
You can use Proc SQL to compute an aggregate result over a group meeting a criteria, and have that aggregate value automatically merged into the result set.
-OR-
Use a MEANS, TRANSPOSE, MERGE approach
Sample Code (SQL)
data have;
input ID $ value $; datalines;
A Y
A N
B Y
B Y
B Y
C W
C N
C W
D Y
D N
D N
D Y
D W
E X
;
proc sql;
create table want as
select ID, value
, sum(value='Y') as Y_COUNT /* relies on logic eval 'math' 0 false, 1 true */
, sum(value='N') as N_COUNT
, sum(value='W') as W_COUNT
from have
group by ID
;
Sample Code (PROC and MERGE)
* format for PRELOADFMT and COMPLETETYPES;
proc format;
value $eachvalue
'Y' = 'Y'
'N' = 'N'
'W' = 'W'
other = '-';
;
run;
* Count how many per combination ID/VALUE;
proc means noprint data=have nway completetypes;
class ID ;
class value / preloadfmt;
format value $eachvalue.;
output out=freqs(keep=id value _freq_);
run;
* TRANSPOSE reshapes to wide (across) data layout, one row per ID;
proc transpose data=freqs suffix=_count out=counts_across(drop=_name_);
by id;
id value;
var _freq_;
where put(value,$eachvalue.) ne '-';
run;
* MERGE;
data want_way_2;
merge have counts_across;
by id;
run;
I want to summarize a dataset by creating a vector that gives information on what departments the id is found in. For example,
data test;
input id dept $;
datalines;
1 A
1 D
1 B
1 C
2 C
3 D
4 A
5 C
5 D
;
run;
I want
id dept_vect
1 1111
2 0010
3 0001
4 1000
5 1001
The position of the elements of the dept_vect is organized alphabetically. So a '1' in the first position means that the id is found in deptartment A and a '1' in the second position means that the id is found in department B. A '0' means the id is not found in the department.
I can solve this problem using a brute force approach
proc transpose data = test out = test1(drop = _NAME_);
by id;
var dept;
run;
data test2;
set test1;
array x[4] $ col1-col4;
array d[4] $ d1-d4;
do i = 1 to 4;
if not missing(x[i]) then do;
if x[i] = 'A' then d[1] = 1;
else if x[i] = 'B' then d[2] = 1;
else if x[i] = 'C' then d[3] = 1;
else if x[i] = 'D' then d[4] = 1;
end;
else leave;
end;
do i = 1 to 4;
if missing(d[i]) then d[i] = 0;
end;
dept_id = compress(d1) || compress(d2) || compress(d3) || compress(d4);
keep id dept_id;
run;
This works but there are a couple of problems. For col4 to appear, I need at least one id to be found on all departments but that could be fixed by creating a dummy id so that id is found on all departments. But the main problem is that this code is not robust. Is there a way to code this so that it would work for any number of departments?
Add a 1 to get a count variable
Transpose using PROC TRANSPOSE
Replace missing with 0
Use CATT() to create desired results.
data have;
input id dept $;
count = 1;
datalines;
1 A
1 D
1 B
1 C
2 C
3 D
4 A
5 C
5 D
;
run;
proc transpose data=test out=wide prefix=dept;
by id;
id dept;
var count;
run;
data want;
set wide;
array _d(*) dept:;
do i=1 to dim(_d);
if missing(_d(i)) then _d(i) = 0;
end;
want = catt(of _d(*));
run;
Maybe TRANSREG can help with this.
data test;
input id dept $;
datalines;
1 A
1 D
1 B
1 C
2 C
3 D
4 A
5 C
5 D
;
run;
proc transreg;
id id;
model class(dept / zero=none);
output design out=dummy(drop=dept);
run;
proc print;
run;
proc summary nway;
class id;
output out=want(drop=_type_) max(dept:)=;
run;
proc print;
run;
I have a dataset similar to the one below
ID A B C D E
1 1
1 1
1 1
2 1
2 1
3 1
3 1
4 1
5 1
I want to condense the data into one row for each ID. So the dataset would look like the one below.
ID A B C D E
1 1 1 1
2 1 1
3 1 1
4 1
5 1
Well I created another table and removed the duplicate ID's. So I have two tables--A and B. I then tried merging the two datasets together. I was playing around with following SAS code.
data C;
merge A B;
by ID;
run;
Here's a neat trick I picked up from another forum. There's no need to split up the original dataset, the first update statement creates the structure and the second updates the values. The BY statement ensures you only get 1 record per ID.
data have;
infile datalines dsd;
input ID A B C D E;
datalines;
1,1,,,,,
1,,,1,,,
1,,1,,,,
2,,1,,,,
2,,,,1,,
3,,,,,1,
3,1,,,,,
4,,,1,,,
5,,1,,,
;
run;
data want;
update have (obs=0) have;
by id;
run;
This could be solved using the retain statement.
data B(rename=(A2=A B2=B C2=C D2=D));
set A;
by id;
retain A2 B2 C2 D2;
if first.id then do;
A2 = .;
B2 = .;
C2 = .;
D2 = .;
end;
if A ne . then A2=A;
if B ne . then B2=B;
if C ne . then C2=C;
if D ne . then D2=D;
if last.id then output;
drop A B C D;
run;
There are other ways to solve this, but hopefully this is helpful.
PROC MEANS is a great tool for something like this. PROC SQL would also give you a reasonable solution, but MEANS is faster.
proc means data=yourdata;
var a b c d e;
class id;
types id; *to avoid the 'overall' row;
output out=yourdata max=; *output the maximum of each var for each ID - use SUM instead if you want more than 1;
run;
How to add new observation to already created dataset in SAS ? For example, if I have dataset 'dataX' with variable 'x' and 'y' and I want to add new observation which is multiplication by two of the
of the observation number n, how can I do it ?
dataX :
x y
1 1
1 21
2 3
I want to create :
dataX :
x y
1 1
1 21
2 3
10 210
where observation number four is multiplication by ten of observation number two.
data X;
input x y;
datalines;
1 1
1 21
2 3
;
run;
data X ;
set X end=eof;
if eof then do;
output;
x=10 ;y=210;
end;
output;
run;
Here is one way to do this:
data dataX;
input x y;
datalines;
1 1
1 21
2 3
run;
/* Create a new observation into temp data set */
data _addRec;
set dataX(firstobs=2); /* Get observation 2 */
x = x * 10; /* Multiply each by 10 */
y = y * 10;
output; /* Output new observation */
stop;
run;
/* Add new obs to original data set */
proc append base=dataX data=_addRec;
run;
/* Delete the temp data set (to be safe) */
proc delete data=_addRec;
run;
data a ;
do kk=1 to 5 ;
output ;
end ;
run;
data a2 ;
kk=999 ;
output ;
run;
data a; set a a2 ;run ;
proc print data=a ;run ;
Result:
The SAS System 1
OBS kk
1 1
2 2
3 3
4 4
5 5
6 999
You can use macro to obtain your desired result :
Write a macro which will read first DataSet and when _n_=2 it will multiply x and y with 10.
After that create another DataSet which will hold only your muliplied value let say x'=10x and y'=10y.
Pass both DataSet in another macro which will set the original datset and newly created dataset.
Logic is you have to create another dataset with value 10x and 10y and after that set wih previous dataset.
I hope this will help !