data bbstats;
label atbats="At Bats";
input Player $19. atbats Hits BB;
datalines;
Christian Walker     271 97 36
Scott Wingo          240 81 44
Brady Thomas         231 73 23
Evan Marzilli        220 64 25
Robert Beary         211 61 12
Adrian Morales       249 70 30
Peter Mooney         254 71 44
Jake Williams        209 56 21
Jackie Bradley Jr.   162 40 22
;
run;

*Slide 12;
proc sql;
 select player, atbats
 from bbstats;
quit;


*Slide 13;
proc sql;
 select player,  hits/atbats as avg
 from bbstats;
quit;

*Slide 15;
proc sql;
 select player, atbats
 from bbstats
 where atbats > 230;
quit;

proc sql;
 select player, atbats
 from bbstats
 where hits > 70;
quit;

* Note the calculated columns are not available unless a new table is created;

* Does not work;
proc sql;
 select player,  hits/atbats as avg
 from bbstats
 where avg > 0.270;
quit;

* Works because we create a new table (more on this later);
proc sql;
create table bbstats2 as
 select player,  atbats, hits, hits/atbats as avg
 from bbstats;
proc sql;
 select player,  hits/atbats as avg
 from bbstats2
 where avg > 0.270;
quit;
/* Chapter 2 will discuss a simpler way to do this */


*Slide 18;
proc sql;
 select player, atbats
 from bbstats
 order by atbats desc;
quit;

*Slide 19;
proc sql;
 select player, atbats
 from bbstats
 order by 2 desc;
quit;

* Ordering by two columns;
proc sql;
 select player, bb, atbats
 from bbstats
 order by bb desc, atbats desc;
quit;