I want to transform my SAS table from data Have to data want.
I feel I need to use Proc transpose but could not figure it out how to do it.
data Have;
input Stat$ variable_1 variable_2 variable_3 variable_4;
datalines;
MAX 6 7 11 23
MIN 0 1 3 5
SUM 29 87 30 100
;
data Want;
input Variable $11.0 MAX MIN SUM;
datalines;
Variable_1 6 0 29
Variable_2 7 1 87
Variable_3 11 3 87
Variable_4 23 5 100
;
You are right, proc transpose is the solution
data Have;
input Stat$ variable_1 variable_2 variable_3 variable_4;
datalines;
MAX 6 7 11 23
MIN 0 1 3 5
SUM 29 87 30 100
;
/*sort it by the stat var*/
proc sort data=Have; by Stat; run;
/*id statement will keep the column names*/
proc transpose data=have out=want name=Variable;
id stat;
run;
proc print data=want; run;
Related
My goal is to combine these tables into one without having to manually run my macro each time for each column.
The code I currently have with me is the following:
%macro task_Oct(set,col_name);
data _type_;
set &set;
call symputx('col_type', vtype(&col_name));
run;
proc sql;
create table work.oct27 as
select "&col_name" as variable,
"&col_type" as type,
nmiss(&col_name) as missing_val,
count(distinct &col_name) as distinct_val
from &set;
quit;
%mend task_Oct;
%task_Oct(sashelp.cars,Origin)
The above code gives me the following output:
|Var |Type |missing_val|distinct_val|
|Origin|Character|0 | 3 |
But the sashelp.cars data sheet has 15 columns and so I would like to output a new data sheet which has 15 rows with 4 columns.
I would like to get the following combined table as the output of my code:
|Var |Type |missing_val|distinct_val|
|Make |Character|0 | 38 |
|Model |Character|0 | 425 |
|Type |Character|0 | 6 |
|Origin|Character|0 | 3 |
...
...
...
Since I'm using a macro, I could run my code 15 different times by manually entering the names of the columns and then merging the tables into 1; and it wouldn't be a problem. But what if I have a table with 100s of columns? I could use some loop statement but I'm not sure how to go about that in this case. Help would be appreciated. Thank you.
The main output you appear to want can be generated directly by PROC FREQ with the NLEVELS option. If you want to add in the variable type then just merge it with the output of PROC CONTENTS.
ods exclude all;
ods output nlevels=nlevels;
proc freq data=sashelp.cars nlevels;
tables _all_ / noprint ;
run;
ods select all;
proc contents data=sashelp.cars noprint out=contents;
run;
proc sql;
create table want(drop=table:) as
select c.varnum,c.name,c.type,n.*
from contents c inner join nlevels n
on c.name=n.TableVar
order by varnum
;
quit;
Result
NNon
NMiss Miss
Obs VARNUM NAME TYPE NLevels Levels Levels
1 1 Make 2 38 0 38
2 2 Model 2 425 0 425
3 3 Type 2 6 0 6
4 4 Origin 2 3 0 3
5 5 DriveTrain 2 3 0 3
6 6 MSRP 1 410 0 410
7 7 Invoice 1 425 0 425
8 8 EngineSize 1 43 0 43
9 9 Cylinders 1 8 1 7
10 10 Horsepower 1 110 0 110
11 11 MPG_City 1 28 0 28
12 12 MPG_Highway 1 33 0 33
13 13 Weight 1 348 0 348
14 14 Wheelbase 1 40 0 40
15 15 Length 1 67 0 67
The NMissLevels variable counts the number of distinct types of missing values.
If instead you want to count the number of observations with (any) missing value you will need to use code generation. So use the CONTENTS data to generate an SQL query to generate all of the counts you want into a single observation with only one pass through the data. You can then transpose that to make it usable for re-merging with the CONTENTS data.
filename code temp;
data _null_;
set contents end=eof;
length nliteral $65 dsname $80;
nliteral=nliteral(name);
dsname = catx('.',libname,nliteral(memname));
file code;
if _n_=1 then put 'create table counts as select ' / ' ' # ;
else put ',' #;
put 'nmiss(' nliteral ') as missing_' varnum
/',count(distinct ' nliteral ') as distinct_' varnum
;
if eof then put 'from ' dsname ';';
run;
proc sql;
%include code /source2;
quit;
proc transpose data=counts out=count2 name=name ;
run;
proc sql ;
create table want as
select c.varnum, c.name, c.type
, m.col1 as nmissing
, d.col1 as ndistinct
from contents c
left join count2 m on m.name like 'missing%' and c.varnum=input(scan(m.name,-1,'_'),32.)
left join count2 d on d.name like 'distinct%' and c.varnum=input(scan(d.name,-1,'_'),32.)
order by varnum
;
quit;
Result
Obs VARNUM NAME TYPE nmissing ndistinct
1 1 Make 2 0 38
2 2 Model 2 0 425
3 3 Type 2 0 6
4 4 Origin 2 0 3
5 5 DriveTrain 2 0 3
6 6 MSRP 1 0 410
7 7 Invoice 1 0 425
8 8 EngineSize 1 0 43
9 9 Cylinders 1 2 7
10 10 Horsepower 1 0 110
11 11 MPG_City 1 0 28
12 12 MPG_Highway 1 0 33
13 13 Weight 1 0 348
14 14 Wheelbase 1 0 40
15 15 Length 1 0 67
Say I have a dataset like this
day product sales
1 a 1 48
2 a 2 55
3 a 3 88
4 b 2 33
5 b 3 87
6 c 1 97
7 c 2 95
On day "b" there were no sales for product 1, so there is no row where day = b and product = 1. Is there an easy way to add a row with day = b, product = 1 and sales = 0, and similar "missing" rows to get a dataset like this?
day product sales
1 a 1 48
2 a 2 55
3 a 3 88
4 b 1 0
5 b 2 33
6 b 3 87
7 c 1 97
8 c 2 95
9 c 3 0
In R you can do complete(df, day, product, fill = list(sales = 0)). I realize you can accomplish this with a self-join in proc sql, but I'm wondering if there is a procedure for this.
In this particular example you can also use the SPARSE option in PROC FREQ. It tells SAS to generate all the complete types with every value from DAY included with PRODUCT, so similar to a cross join between those elements. If you do not have the value in the table already it cannot add the value. You would need a different method in that case.
data have;
input n day $ product sales;
datalines;
1 a 1 48
2 a 2 55
3 a 3 88
4 b 2 33
5 b 3 87
6 c 1 97
7 c 2 95
;;;;
run;
proc freq data=have noprint;
table day*product / out=want sparse;
weight sales;
run;
proc print data=want;run;
There are, as usual in SAS, about a dozen ways to do this. Here's my favorite.
data have;
input n day $ product sales;
datalines;
1 a 1 48
2 a 2 55
3 a 3 88
4 b 2 33
5 b 3 87
6 c 1 97
7 c 2 95
;;;;
run;
proc means data=have completetypes;
class day product;
types day*product;
var sales;
output out=want sum=;
run;
completetypes tells SAS to put out rows for every class combination, including missing ones. You could then use proc stdize to get them to be 0's (if you need them to be 0). It's possible you might be able to do this in the first place with proc stdize, I'm not as familiar unfortunately with that proc.
You can do this with proc freq using the sparse option.
Code:
proc freq data=have noprint;
table day*product /sparse out=freq (drop=percent);
run;
Output:
day=a product=1 COUNT=1
day=a product=2 COUNT=1
day=a product=3 COUNT=1
day=b product=1 COUNT=0
day=b product=2 COUNT=1
day=b product=3 COUNT=1
day=c product=1 COUNT=1
day=c product=2 COUNT=1
day=c product=3 COUNT=0
I am new to SAS and I want to transpose the following table in SAS
From
ID Var1 Var2 Jul-09 Aug-09 Sep-09
1 10 15 200 300
2 5 17 -150 200
to
ID Var1 Var2 Date Transpose
1 10 15 Jul-09 200
1 10 15 Aug-09 300
2 5 17 Aug-09 -150
2 5 17 Sep-09 200
Can anyone help please?
You can use proc transpose to tranform data.
options validvarname=any;
data a;
infile datalines missover;
input ID Var1 Var2 "Jul-09"n "Aug-09"n "Sep-09"n;
datalines;
1 10 15 200 300
2 5 17 -150 200
;
run;
proc transpose data=a out=b(rename=(_NAME_=Date COL1=Transpose));
var "Jul-09"n--"Sep-09"n;
by ID Var1-Var2;
run;
data a;
input ID Var1 Var2 Jul_09 Aug_09;
CARDS;
1 10 15 200 300
2 5 17 -150 200
;
DATA b(drop=i jul_09 aug_09);
array dates_{*} jul_09 aug_09;
set a;
do i=1 to dim(dates_);
this_value=dates_{i};
this_date=input(compress(vname(dates_{i}),'_'),MONYY5.);
output;
end;
format this_date monyy5.;
run;
I have a dataset with tree variables, three binary variables.
I wrote a proc tabulate
proc tabulate data=mydata;
class country var1 var2;
table Country, var1 var2;
run;
Var1 Var2
0 1 0 1
USA 40 50 40 50
AUS 50 20 50 20
IRE 60 40 60 40
DUB 70 50 70 50
Here I get the table with the totals of both var 1 var 2 for 0s and 1s.
However I want only the totals of 1s in this cross table. How can I do that.
If I use a where caluse as below, it shows only 1ns both..
proc tabulate data=mydata;
class country var1 var2;
table Country, var1 var2;
where var1=1 and var2=2;
run;
When I use the above it brings out only the 1s present in both at the sametime.
Which is not I am looking for.
So the dataset I want is as below.
Var1 Var2
1 1
USA 50 50
AUS 20 20
IRE 40 40
DUB 50 50
Is there any other way of doing this?
Change and to or.
Truth table for
Var1=1, Var2=1
Include?
Var1 Var2 AND OR
0 0 N N
0 1 N Y
1 0 N Y
1 1 Y Y
Since your variables are coded 0,1 you can ask for the SUM statistic to get the "count" of the number of ones.
proc tabulate data=mydata;
class country;
var var1 var2;
table Country, var1*sum var2*sum;
run;
I have a SAS Table like:
DATA test;
INPUT id sex $ age inc r1 r2 Zaehler work $;
DATALINES;
1 F 35 17 7 2 1 w
17 M 40 14 5 5 1 w
33 F 35 6 7 2 1 w
49 M 24 14 7 5 1 w
65 F 52 9 4 7 1 w
81 M 44 11 7 7 1 w
2 F 35 17 6 5 1 n
18 M 40 14 7 5 1 n
34 F 47 6 6 5 1 n
50 M 35 17 5 7 1 w
;
PROC PRINT; RUN;
proc sort data=have;
by county;
run;
I want compare rows if sex and age is equal and build sum over Zaehler. For example:
1 F 35 17 7 2 1 w
and
33 F 35 6 7 2 1 w
sex=f and age=35 are equale so i want to merge them like:
id sex age inc r1 r2 Zaehler work
1 F 35 17 7 2 2 w
I thought i can do it with proc sql but i can't use sum in proc sql. Can someone help me out?
PROC SUMMARY is the normal way to compute statistics.
proc summary data=test nway ;
class sex age ;
var Zaehler;
output out=want sum= ;
run;
Why would you want to include variables other than SEX, AGE and Zaehler in the output?
Your requirement is not difficult to understand or to satisfy, however, I am not sure what is your underline reason for doing this. Explain more on your purpose may help to facilitate better answers that work from the root of your project. Although I have a feeling the PROC MEAN may give you better matrix, here is a one step PROC SQL solution to get you the summary as well as retaining "the value of first row":
proc sql;
create table want as
select id, sex , age, inc, r1, r2, sum(Zaehler) as Zaehler, work
from test
group by sex, age
having id = min(id) /*This is tell SAS only to keep the row with the smallest id within the same sex,age group*/
;
quit;
You can use proc sql to sum over sex and age
proc sql;
create table sum as
select
sex
,age
,sum(Zaehler) as Zaehler_sum
from test
group by
sex
,age;
quit;
You can than join it back to the main table if you want to include all the variables
proc sql;
create table test_With_Sum as
select
t.*
,s.Zaehler_sum
from test t
inner join sum s on t.sex = s.sex
and t.age = s.age
order by
t.sex
,t.age
;
quit;
You can write it all as one proc sql query if you wish and the order by is not needed, only added for a better visibility of summarised results
Not a good solution. But it should give you some ideas.
DATA test;
INPUT id sex $ age inc r1 r2 Zaehler work $;
DATALINES;
1 F 35 17 7 2 1 w
17 M 40 14 5 5 1 w
33 F 35 6 7 2 1 w
49 M 24 14 7 5 1 w
65 F 52 9 4 7 1 w
81 M 44 11 7 7 1 w
2 F 35 17 6 5 1 n
18 M 40 14 7 5 1 n
34 F 47 6 6 5 1 n
50 M 35 17 5 7 1 w
;
run;
data t2;
set test;
nobs = _n_;
run;
proc sort data=t2;by descending sex descending age descending nobs;run;
data t3;
set t2;
by descending sex descending age;
if first.age then count = 0;
count + 1;
zaehler = count;
if last.age then output;
run;
proc sort data=t3 out=want(drop=nobs count);by nobs sex age;run;
thanks for your help. Here is my final code.
proc sql;
create table sum as
select distinct
sex
,age
,sum(Zaehler) as Zaehler
from test
WHERE work = 'w'
group by
sex
,age
;
PROC PRINT;quit;
I just modify the code a little bit. I filtered the w and i merg the Columns with the same value.
It was just an example the real Data is much bigger and has more Columns and rows.