Hi, I'm new to SAS and I'm struggling with this homework problem below. Any help is greatly appreciated! Thank you.
Employee_id Name gender years dept salary01 salary02 salary03; 1 Mitchell, Jane A f 6 shoe 22,450 23,000 26,600 2 Miller, Frances T f 8 appliance . 32,500 33,000 3 Evans, Richard A m 9 appliance 42,900 43,900 . 4 Fair, Suzanne K f 3 clothing 29,700 32,900 34,500 5 Meyers, Thomas D m 5 appliance 33,700 34,400 37,000 6 Rogers, Steven F m 3 shoe 27,000 27,800 . 7 Anderson, Frank F m 5 clothing 33,000 35,100 36,000 10 Baxter, David T m 2 shoe 23,900 . 31,300 11 Wood, Brenda L f 3 clothing 33,000 34,000 35,700 12 Wheeler, Vickie M f 7 appliance 31,500 33,200 35,600 13 Hancock, Sharon T f 1 clothing 21,000 . 22,500 14 Looney, Roger M m 10 appliance 42,900 36,200 37,800 15 Fry, Marie E f 6 clothing 29,700 30,500 31,200
See this code for doing something similar off seashell.class:
proc sql;
select *
from sashelp.class
group by sex
having weight=max(weight)
;
quit;
Sort the data by dept and salary, then (since this puts the highest salary01 in the last record of each department) and then select the last record via:
data want;
set have;
by dept;
if last.dept;
run;
I suspect you're expected to use the techniques taught in class and there are many many ways to do this one.
@Amy0223 wrote:
Hi, I'm new to SAS and I'm struggling with this homework problem below. Any help is greatly appreciated! Thank you.
- For each department find the employee whose salary01 is the highest in the department. Print the names of these employees and department names.
Employee_id Name gender years dept salary01 salary02 salary03; 1 Mitchell, Jane A f 6 shoe 22,450 23,000 26,600 2 Miller, Frances T f 8 appliance . 32,500 33,000 3 Evans, Richard A m 9 appliance 42,900 43,900 . 4 Fair, Suzanne K f 3 clothing 29,700 32,900 34,500 5 Meyers, Thomas D m 5 appliance 33,700 34,400 37,000 6 Rogers, Steven F m 3 shoe 27,000 27,800 . 7 Anderson, Frank F m 5 clothing 33,000 35,100 36,000 10 Baxter, David T m 2 shoe 23,900 . 31,300 11 Wood, Brenda L f 3 clothing 33,000 34,000 35,700 12 Wheeler, Vickie M f 7 appliance 31,500 33,200 35,600 13 Hancock, Sharon T f 1 clothing 21,000 . 22,500 14 Looney, Roger M m 10 appliance 42,900 36,200 37,800 15 Fry, Marie E f 6 clothing 29,700 30,500 31,200
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