I have one column of data and the column is named (Daily_Mileage). I have 15 different types of daily mileages and 250 rows. I want a separate count for each of the 15 daily mileages. I am using PROC SQL in SAS and it does not like the Cross join command. I am not really sure what I should do but this is what I started:
PROC SQL;
select A, B
From (select count(Daily_Mileage) as A from Work.full where Daily_Mileage = 'Farm Utility Vehicle (Class 7)') a
cross join (select count(Daily_Mileage) as B from Work.full where Daily_Mileage = 'Farm Truck Light (Class 35)') b);
QUIT;
Use case statements to define your counts as below.
proc sql;
create table submit as
select sum(case when Daily_Mileage = 'Farm Utility Vehicle (Class 7)'
then 1 else 0 end) as A,
sum(case when Daily_Mileage = 'Farm Truck Light (Class 35)'
then 1 else 0 end) as B
from Work.full
;
quit ;
Can't you just use a proc freq?
data example ;
input #1 Daily_Mileages $5. ;
datalines ;
TYPE1
TYPE1
TYPE2
TYPE3
TYPE3
TYPE3
TYPE3
;
run ;
proc freq data = example ;
table Daily_Mileages ;
run ;
/* Create an output dataset */
proc freq data = example ;
table Daily_Mileages /out=f_example ;
run ;
You can first create another column of ones, then SUM that column and GROUP BY Daily_Mileage. Let me know if I'm misunderstanding your questions.
PROC SQL;
CREATE TABLE tab1 AS
SELECT Daily_Mileage, 1 AS Count, SUM(Count) AS Sum
FROM <Whatever table your data is in>
GROUP BY Daily_Mileage;
QUIT;
Related
I stumbled upon the following code snippet in which the variable top3 has to be filled from a table have rather than from an array of numbers.
%let top3 = 14 15 42; /* This should be made obsolete.. */
%let no = 3;
proc sql;
create table want as
select *
from (select x, y from foo) a
%do i = 1 %to &no.;
%let current = %scan(&top3.,&i.); /* What do I need to put here? */
left join (select x, y from bar where z=¤t.) row_¤t.
on a.x = row_¤t..x
%end;
;
quit;
The table have contains the xs from the string and looks as follows:
i x
1 14
2 15
3 42
I am now wondering how I should modify the %let current = ... line such that current is populated from the table have. I know how to populate a macro variable using proc sql with select .. into, but I am afraid that the way I am going right now is fully against SAS philosophy.
It looks like you're more or less transposing something. If that's the case, this is doable in macro/sql pretty easily.
First, here's the simple version - no macro.
proc sql;
create table class_t as
select * from (
select name from sashelp.class ) class
left join (
select name, age as age_Alfred
from sashelp.class
where name='Alfred') Alfred
on class.name = Alfred.name
;
quit;
We grab the value of age from the Alfred row and put it on the main join. This isn't exactly what you're doing, but it seems similar. (I'm just using one table, but you can of course use two here.)
Now, how do we extend this to be table-driven and not handwritten? Macros!
First, here's the macro - just taking the Alfred bit and making it generic.
%macro joiner(name=);
left join (
select name, age as age_&name.
from sashelp.class
where name="&name.") &name.
on class.name = &name..name
%mend joiner;
Second, we look at this and see two things we need to put into macro lists: the SELECT variable list (we'll get one new variable for each call), and the JOIN list.
proc sql;
select cats('%joiner(name=',name,')')
into :joinlist separated by ' '
from sashelp.class;
select cats(name,'.age_',name)
into :selectlist separated by ','
from sashelp.class;
quit;
And then, we just call it!
proc sql;
create table class_t as
select class.name,&selectlist. from (
select name from sashelp.class) class
&joinlist.
;
quit;
Now, your dataset you call the macro lists from is perhaps the dataset with the 3 rows in it you have above ("have"). The dataset you actually get the appending data from is some other dataset ("bar"), right? And then the ones you join to is perhaps a third dataset ("foo"). Here I just use the one, for simplicity, but the concept is the same, just different sources.
When the lookup data is in a table you can perform a three way join without any need for SAS Macro. You don't provide any data so the example will mock some.
Example:
Suppose a master record has several associated detail records, and the detail records contain a z value used for selection into a result set per a wanted z lookup table.
data masters;
call streaminit(2020);
do id = 1 to 100;
do x = 1 to 100;
m_rownum + 1;
code = rand('integer', 10,45);
output;
end;
end;
run;
data details;
call streaminit(2020);
do date = 1 to 20;
do x = 1 to 100;
do rep = 1 to 5;
d_rownum + 1;
amount = rand('integer', 100,200);
z = rand('integer', 10,45);
output;
end;
end;
end;
run;
data zs;
input z ##; datalines;
14 15 42
;
proc sql;
create table want as
select
m_rownum
, d_rownum
, masters.id
, masters.x
, masters.code
, details.z
, details.date
, details.amount
from
masters
left join
details
on
details.x = masters.x
inner join
zs
on
zs.z = details.z
order by
masters.id, masters.x, details.z, details.date
;
quit;
I am working in SAS Enterprise guide and am running a proc sql query as follows:
proc sql;
CREATE TABLE average_apples AS
SELECT farm, size, type, mean(apples) as average_apples
FROM input_table
GROUP BY farm, size, type
;
quit;
For some of the data sets I am running this query on there are groups which have no observations assigned to them, so there is no entry for them in the query output.
How can I force this query to return a row for each of my groups (for example with a value of 0in the apples column?
Thanks up front for the help!
I'd do this:
/* sample input table */
data input_table;
length farm size type $3 apples 8;
stop; /* try also with this statement commented out
to check the result for non-empty input table */
run;
proc sql;
CREATE TABLE average_apples AS
SELECT farm, size, type, mean(apples) as average_apples
FROM input_table
GROUP BY farm, size, type
;
quit;
%let group_rows = &SQLOBS;
%put &group_rows;
data average_apples_blank;
if &group_rows ne 0 then set average_apples(obs=0);
else do;
array zeros {*} _numeric_ /* or your list of variables */;
do i=1 to dim(zeros);
zeros[i] = 0;
end;
output; /* empty row */
end;
drop i;
run;
proc append base=average_apples data=average_apples_blank force;
run;
Try this
proc sql;
select f.farm, s.size, t.type, coalesce(mean(apples), 0) as average_apples
from (select distinct farm from input_table) as f
, (select distinct size from input_table) as s
, (select distinct type from input_table) as t
left join input_table as i
on i.farm = f.farm and i.size = s.size and i.type t.type;
quit;
I did not test it, though. It it does not work, put this in a comment and I will debug it.
Data IV_SAS;
set IV;
Total_Loans=Goods+Bads;
Dist_Loans=Total_Loans/sum(Total_Loans));
Dist_Goods=Goods/Sum(Goods);
Dist_Bads=Bads/Sum(Bads);
Difference=Dist_Goods-Dist_Bads;
WOE=log10(Dist_goods/Dist_Bads);
IV=WOE*Difference;
run;
I am facing issues in calculating sum of (Total Loans),its calculating Row total instead of column total.
That's how Base SAS works - it operates on row level in the data step.
You would want to use PROC MEANS or PROC TABULATE or similar proc and find the column total there, then merge that on (or combine in another method).
For example:
proc means data=sashelp.class;
var age height weight;
output out=class_means sum(age)=age_sum sum(height)=height_sum sum(weight)=weight_Sum;
run;
data class;
if _n_=1 then set class_means;
set sashelp.class;
age_prop = age/age_sum;
height_prop = height/height_sum;
weight_prop = weight/weight_Sum;
run;
Alternately, use SAS/IML or PROC SQL, both of which will operate on the column level when asked inline (though I think the above solution is likely superior in speed to both due to lower overhead).
data a;
input goods bads;
datalines;
36945 33337
23820 21761
26990 24647
33195 30299
43755 39014
46100 41100
89765 79978
25940 23508
35940 32506
31840 28846
33430 30366
34480 31388
36640 33129
39640 35992
42490 38325
44240 40075
42840 38840
49690 44936
69190 64740
;
run;
proc sql;
create table b as
select goods,bads,
sum(goods,bads) as Total_Loans format=dollar10.,
sum(goods)as Column_goods_tot format=dollar10. ,
sum(bads) as Column_bads_tot format=dollar10. ,
sum(calculated Column_goods_tot, calculated Column_bads_tot) as Column_Total_Loans format=dollar10. ,
(calculated Total_Loans/calculated Column_Total_Loans) as Dist_Loans
/*add more code to calculate Dist_Goods, Dist_Bads, etc..*/
from a;
quit;
/*Column totals only*/
proc sql;
create table c as
select
sum(goods)as Column_goods_tot format=dollar10. ,
sum(bads) as Column_bads_tot format=dollar10. ,
sum(calculated Column_goods_tot, calculated Column_bads_tot) as Column_Total_Loans format=dollar12.
from a;
quit;
I have two datasets. Both have a common column- ID. I would like to check if ID from df1 lies in df2 and extract all such rows from df1. I'm doing this in SAS.
It is easily done in one sql query.
proc sql;
create table extract_from_df1 as
select
*
from
df1
where
id in (select id from df2)
;
quit;
There are lots of ways to do this. For example:
proc sql;
create table compare as select distinct
a.id as id1, b.id as id2
from table1 as a
left join table2 as b
on a.id = b.id;
quit;
and then keep matches. Or you can try:
proc sql;
delete from table2 where id2 in select distinct id1 from table1;
quit;
data df1;
input id name $;
cards;
1 abc
2 cde
3 fgh
4 ijk
;
run;
data df2;
input id address $;
cards;
1 abc
2 cde
5 ggh
6 ihh
7 jjj
;
run;
data c;
merge df1(in=x) df2(in=y);
if x and y;
keep id name;
run;
proc print data=c;
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;