标题: Make a frequency function in SAS/IML [打印本页] 作者: shiyiming 时间: 2012-3-16 13:49 标题: Make a frequency function in SAS/IML From Dapangmao's blog on sas-analysis
<div class="separator" style="clear: both; text-align: center;"><a href="http://4.bp.blogspot.com/-Q5S7WVe5jKQ/T2KrbFcvUwI/AAAAAAAAA-Y/7Nhjjv23_jo/s1600/SGPlot.png" imageanchor="1" style="margin-left:1em; margin-right:1em"><img border="0" height="300" width="400" src="http://4.bp.blogspot.com/-Q5S7WVe5jKQ/T2KrbFcvUwI/AAAAAAAAA-Y/7Nhjjv23_jo/s400/SGPlot.png" /></a></div><br />
Aggregation is probably the most popular operation in the data world. R comes with a handy table() function. Usually in SAS, the FREQ procedure would deal with this job. It will be great if SAS/IML has an equivalent function. I just created a user-defined function or module for such a purpose. Since it contains a DO loop, the efficiency is not very ideal -- always 10 times slower than PROC FREQ for a simulated data set of one million records. <br />
<pre style="background-color: #ebebeb; border: 1px dashed rgb(153, 153, 153); color: #000001; font-size: 14px; line-height: 14px; overflow: auto; padding: 5px; width: 100%;"><code>
/* 1 - Use IML for simulation and aggregation */
proc iml;
start freq(invec);
x = t(unique(invec));
y = repeat(x, 1, 2);
do i = 1 to nrow(x);
y[i, 2] = ncol(loc(invec=y[i, 1]));
end;
return(y);
finish;
store module = freq;
quit;
proc iml;
load module = freq;
/* Simulate a vector with 1 million values */
test = abs(floor(rannor(1:1e6)*100));
t0 = time();
result = freq(test);
timer = time() - t0;
print timer;
/* Output the test vector as SAS data set */
create a var{"level" "frequency"};
append from result;
close a;
quit;
proc sgplot data = a;
series x = level y = frequency;
run;
/* 2 - Use PROC FREQ for simulation and aggregation */
data test;
do i = 1 to 1e6;
test = abs(floor(rannor(1234)*100));
output;
end;
drop i;
run;
options fullstimer;
proc freq data = test noprint;
table test / out = b;
run;
</code></pre><div class="blogger-post-footer"><img width='1' height='1' src='https://blogger.googleusercontent.com/tracker/3256159328630041416-7881952112999171992?l=www.sasanalysis.com' alt='' /></div><img src="http://feeds.feedburner.com/~r/SasAnalysis/~4/ZKsrU2VLJZE" height="1" width="1"/>