I'm trying to concatenate two tables using a proc sql - union where certain variables are unique to each table. Is there a way to do this without using a NULL placeholder variable? Basically the equivalent of the following data step.
data total;
set t1 t2;
run;
A simple example of what I'm trying to do is shown below.
data animal;
input common $ Animal $ Number;
datalines;
a Ant 5
b Bird .
c Cat 17
d Dog 9
e Eagle .
f Frog 76
;
run;
data plant;
input Common $ Plant $ Number;
datalines;
g Grape 69
h Hazelnut 55
i Indigo .
j Jicama 14
k Kale 4
l Lentil 88
;
run;
proc sql;
(select animal.*, '' as plant from animal)
union all corresponding
(select plant.*, '' as animal from plant)
;
quit;
I'd like to be able to run the proc sql with having to create the plant and animal variables in the select statement.
You want outer union, not union all. That does what you expect (keeps all variables in either dataset). See Howard Schreier's excellent paper on SQL set theory for more information.
proc sql;
create table test as
select * from animal
outer union corr
select * from plant
;
quit;
Related
I want merge two tables, but they have 2 columns in commun, and i do not want value of var1 in A replaced by that in B, if we don't use drop or rename, does anyone know it?
I can fix it with sql but just curious with Merge!
data a;
infile datalines;
input id1 $ id2 $ var1;
datalines;
1 a 10
1 b 10
2 a 10
2 b 10
;
run;
/* create table B */
data b;
infile datalines;
input id1 $ id2 $ var1 var2;
datalines;
1 a 30 50
2 b 30 50
;
run;
/* Marge A and B */
data c;
merge a (in=N) b(in=M);
if N;
by id1;
run;
but what i like is:
data C;
infile datalines;
input id1 $ id2 $ var1 var2;
datalines;
1 a 10 50
1 b 10 50
2 a 10 50
2 b 10 50
;
run;
Use rename
data c;
merge a (in=N) b(in=M rename=(var1=var1_2));
by id1;
if N;
run;
If you don't want to use rename / drop etc., then you could just flip the merge order such that the datasets whose var1 should be retained overwrites the other:
data c;
merge b (in=M) a(in=N);
by id1;
if N;
run;
When the data step loads data from the datasets mentioned it does it in the order that they appear on the MERGE (or SET or UPDATE) statement. So if you are merging two dataset and the BY variables match values then the record from the first is loaded and the record from the second is loaded, overwriting the values read from the first.
For 1 to 1 matching you can just change the order that the datasets are mentioned.
merge b(in=M) a(in=N) ;
If you really want the variables defined in the output dataset in the order they appear in A then add a SET statement that the compiler will process but that can never execute before your MERGE statement.
if 0 then set a b ;
If you are doing a 1 to many matching then you might have other trouble since when a dataset stops contributing values to the current BY group then SAS does not re-read the last observation. In that case you will have to use some combination of RENAME=, DROP= or KEEP= dataset options.
In PROC SQL when you have duplicate names for selected columns (and are trying to create an output dataset instead of report) then SAS ignores the second copy of the named variable. So in a sense it is the reverse of what happens with the MERGE statement.
I have a summary table which I want to transpose, but I can't get my head around. The columns should be the rows, and the columns are the values.
Some explanation about the table. Each column represents a year. People can be in 3 groups: A, B or C. In 2016, everyone (100) is in group A. In 2017, 35 are in group A (5 + 20 + 10), 15 in B and 50 in C.
DATA have;
INPUT year2016 $ year2017 $ year2018 $ count;
DATALINES;
A A A 5
A A B 20
A A C 10
A B C 15
A C A 50
;
RUN;
I want to be able to make a nice graph of the evolution of the groups through the different periods. So I want to end up with a table where the columns are the rows (=period) and the columns are the values (= the 3 different groups). Please find an example of the table I want:
Image of table want
I have tried different approaches, but I can't get what I want.
Maybe more direct way but this is probably how I would do it.
DATA have;
INPUT year2016 $ year2017 $ year2018 $ count;
id + 1;
DATALINES;
A A A 5
A A B 20
A A C 10
A B C 15
A C A 50
;
RUN;
proc print;
proc transpose data=have out=want1 name=period;
by id count notsorted;
var year:;
run;
proc print;
run;
proc summary data=want1 nway completetypes;
class period col1;
freq count;
output out=want2(drop=_type_);
run;
proc print;
run;
proc transpose data=want2 out=want(drop=_name_) prefix=Group_;
by period;
var _freq_;
id col1;
run;
proc print;
run;
I'm using this SAS code:
data test1;
input cust_id $
month
category $
status $;
datalines;
A 200003 ABC C
A 200004 DEF C
A 200006 XYZ 3
B 199910 ASD X
B 199912 ASD C
;
quit;
proc sql;
create view test2 as
select cust_id, input(put(month, 6.), yymmn6.) as month format date9.,
category, status from test1 order by cust_id, month asc;
quit;
proc expand data=test2 out=test3 to=month method=none;
by cust_id;
id month;
quit;
proc print data=test3;
title "after expand";
quit;
and I want to create a dataset that looks like this:
Obs cust_id month category status
1 A 01MAR2000 ABC C
2 A 01APR2000 DEF C
3 A 01MAY2000 . .
4 A 01JUN2000 XYZ 3
5 B 01OCT1999 ASD X
6 B 01NOV1999 . .
7 B 01DEC1999 ASD C
but the output from proc expand just says "Nothing to do. The data set WORK.TEST3 has 0 observations and 0 variables." I don't want/need to change the frequency of the data, just interpolate it with missing values.
What am I doing wrong here? I think proc expand is the correct procedure to use, based on this example and the documentation, but for whatever reason it doesn't create the data.
You need to add a VAR statement. Unfortunately, the variables need to be numeric. So just expand the month by cust_id. Then join back the original values.
proc expand data=test2 out=test3 to=month ;
by cust_id;
id month;
var _numeric_;
quit;
proc sql noprint;
create table test4 as
select a.*,
b.category,
b.status
from test3 as a
left join
test2 as b
on a.cust_id = b.cust_id
and a.month = b.month;
quit;
proc print data=test4;
title "after expand";
quit;
I want to use dataset B to overwrite some values in dataset A by merging dataset A & B with a merging ID. However it doesn't work as expected. Here is the test I did:
/* create table A */
data a;
infile datalines;
input id1 $ id2 $ var1;
datalines;
1 a 10
1 b 10
2 a 10
2 b 10
;
run;
/* create table B */
data b;
infile datalines;
input id1 $ var1 var2;
datalines;
1 20 30
2 20 30
;
run;
/* merge A&B to overwrite var1 in table A using values in table B */
data c;
merge a b;
by id1;
run;
Table C looks like this:
ID1 ID2 VAR1 VAR2
1 a 20 30
1 b 10 30
2 a 20 30
2 b 10 30
Why the 10s in row 2&4 didn't get replaced by 20 from table B? While var2 works as expected?
I know I can do this simply using proc SQL, and that's what I did to solve the problem. But I still quite curious if there is a way to do what I wanted using merge? And why this wasn't working? I prefer merge over SQL in this circumstance because the logic is easier to implement (util I found this not working properly).
I use SAS 9.4.
This has to do with how SAS iterates over the data sets during the merge. Basically, the second record for each of A doesn't get lined up with a record from B. The value of VAR2 is carried over from the previous record. VAR1 gets its value from A (because there is no B).
IF there is record in B for EVERY ID1, then you can rewrite your merge like this to achieve what you want.
/* merge A&B to overwrite var1 in table A using values in table B */
data c;
merge a(drop=var1) b;
by id1;
run;
This drops the VAR1 from A so that it is carried down from the record in B.
Otherwise you will need more complex logic (might I suggest an SQL left join with the coalesce() function?).
Like DomPazz suggests, proc sql is the way to do this. merge will only keep one value from each data set. The coalesce function pick the first non-missing value from the list, so it uses var1 from b, but if b.var1 is null then it uses a.var1.
proc sql;
create table c as
select
a.id1,
a.id2,
coalesce(b.var1,a.var1) as var1,
b.var2
from
a
left join b
on a.id1 = b.id1
;
quit;
The merge method could still work fine, you would just need to be more explicit about how to choose the 'best' value for var1, such as:
data c (drop = a_var1 b_var1);
merge a(rename=(var1 = a_var1))
b(rename=(var1 = b_var1));
by id1;
* Now you have two different variables named a_var1 and b_var1;
* Implement logic to choose your favorite;
if NOT MISSING(b_var1) Then DO;
var1 = b_var1;
var1_source='B';
END;
else DO;
var1 = a_var1;
var1_source='A';
END;
run;
If your criteria for which 'var1' to choose is as simple as 'If b exists, use it' then this is identical to the the SQL method with coalesce().
Where I've found this method useful is for more complicated criteria, plus its always nice to know the source of the data (which doesn't happen with coalesce()).
I have the below two datasets
Dataset A
id age mark
1 . .
2 . .
1 . .
Dataset B
id age mark
2 20 200
1 10 100
I need the below dataset as output
Output Dataset
id age mark
1 10 100
2 20 200
1 10 100
How to carry out this without using PROC SQL i.e. using DATA STEP?
There are many ways to do this. The easiest is to sort the two data sets and then use MERGE. For example:
proc sort data=A;
by id;
run;
proc sort data=B;
by id;
run;
data WANT;
merge A(drop=age mark) B;
by ID;
run;
The trick is to drop the variables you are adding from the first data set A; the new variables will come from the second data set B.
Of course, this solution does not preserve the original order of the observations in your data set AND only works because your second data set contains unique values of id.
I tried this and it worked for me, even if you have data you would like to preserve in that column. Just for completeness sake I added an SQL variant too.
data a;
input id a;
datalines;
1 10
2 20
;
data b;
input id a;
datalines;
1 .
1 5
1 .
2 .
3 4
;
data c (drop=b);
merge a (rename = (a=b) in=ina) b (in = inb);
by id;
if b ne . then a = b;
run;
proc sql;
create table d as
select a.id, a.a from a right join b on a.id=b.id where a.id is not null
union all
select b.id, b.a from a right join b on a.id = b.id where a.id is null
;
quit;