Proc FCMP

A long time ago I figured out how to write functions for SAS using SAS/Toolkit. It was not a straightforward process and not very useful. In fact, someone recently asked me about it and I was unable to share much useful info. However, I did find proc FCMP which does look to be very useful-- if you're into writing your own functions, that is!

Here is some online info:
http://support.sas.com/rnd/base/datastep/user-written-functions.pdf
http://support.sas.com/documentation/onlinedoc/base/91/fcmp.pdf


If you have SAS 9.1 you can use it to write functions that can be used in some
procedures, but not within the data step. However, if you have SAS 9.2 you can use them in a data step. And it uses data step syntax so you don't have to know C!

The Cats() Function

One of my favorite new functions is the cats() function available in SAS v9. It is a compress() like function in that it removes leading and
trailing blanks, but it also concatenates the results. CATS() stands for concatenate and strip. Basically the cats() function takes this
type of assignment statement:

key = trim(left(firstName)) || trim(left(lastName)) || 
      trim(left(phone)) || trim(left(zip)) ;

and changes it to this:

key = cats(firstName, lastName, phone, zip);

Generally, the cats() function will return a value with a length of 32767 in the data step. So as always, it's a good idea to use
a length statement on the variable you are assigning to. In this example I might use something like:

length key $200;

The cats() function belongs to a family of cat() functions each doing it's own version of concatenate: cat(), cats(), catt(), catx().

Coming up in version 10, the dog() family of functions! :)

Where Did the Observation Come From?

Here is a little snippet of code I created to address the problem of assigning a value to a variable based on what data set an observation came from in a data step. Here is an example:

Suppose I have a whole bunch of data sets each representing a different country. I want to set a lot of them in one data step and create one resulting data set with a variable called language. In order to create the language variable correctly, we need to know which data set the observation is coming from. Typically we would use the IN= option on the data set to create a flag and then check that flag using if/then logic.

data selectedCountries;
  set
    chile(in=chile)
    china(in=china)
    costa_rica(in=costa)
    egypt(in=egypt)
    fiji(in=fiji)
    turkey(in=turkey)
    usa(in=usa)
    saudi_arabia(in=saudi)
  ;

  if chile then language = 'SPANISH';
  else if china then language = 'CHINESE';
  else if costa then language = 'SPANISH';
  etc etc etc...
run;

One of the major problems with this approach is it does not scale well. The more countries you set, the more problematic your if/then logic becomes.

Here is a slightly more elegant solution that uses arrays and variable information functions. You still use the IN= option on the data set, however you want to name the in= variable the same as the value we want to assign. Then you create an array of all those in=variables. Finally, you loop through the array of in= variables and check for their boolean value. If it is true then you assign your new variable the value derived from the vname() function.

data selectedCountries;
  set
    chile(in= SPANISH)
    china(in= CHINESE)
    costa_rica(in= SPANISH)
    egypt(in= ARABIC)
    fiji(in= ENGLISH)
    turkey(in= TURKISH)
    usa(in= ENGLISH)
    saudi_arabia(in= ARABIC)
  ;
  array names[*] SPANISH CHINESE ARABIC ENGLISH TURKISH;
  do i = 1 to dim(names);
    if names[i] eq 1
     then language = vname( names[i] );
  end;
run;

Cool V9 SAS Compress() Function Tricks

In SAS Version 9 there is a new option available for the compress() function. This new third option allows you to use "modifiers" to modify what compress() is doing. There are too many modifiers to list here, but they are worth looking up in the SAS V9 documentation.

Here is an example of a snippet of code I recently created to get rid of "non-printable" hex chars. This is a pretty standard data cleaning routine and is quite useful when some bad hex chars can creep into your text data. Instead of hunting and pecking for the funky hex chars you can just tell compress() to keep only the
"printable characters".

data _null_;
  x = 'A '  '16'x  'bad'  '18'x  ' sequence, with puncuation?';

  put x=;
  x = compress(x,,"kw");  * k is for keep, w is for "write-able";
  put x=;
run;

Notice in the compress() function there is no second parameter, and there is a new third parameter specified: "kw".
K is for keep, and W is for write-able. So this reads as keep only
a-zA-Zwhitespace0-9punctuation.

Pretty nice, eh?

As I said, there is a bunch of other modifiers available so take a look at the documentation. And happy coding!

Also, there are more examples of using the compress function with the optional third argument at my i-Doc site: http://idoc.pelicanprogramming.com/functions/COMPRESS.html