SAS Learning using

Desired Outcome:

High level introduction to SAS using basic overview from with various Lessons Learned:

Accessing data from a file

-Within the code, the first line in tutorial is:

Filename file1 ‘folders/myfolders/file1.csv’

-I was able to easily create the CSV, but within the Mac it was in the myfolders directory, and I didn’t realize that SAS is configured first for ‘folders’

-Within SAS, Code, Server Files and Folders, I first click on select “My Folders”

-Click on the icon above called Folder Properties

-Location: /folders/myfolders

-Note: I was thinking this was just within the tutorial, but this actually is the path

Different formats of files for input

Note: This was an issue because I was getting ahead of the documentation, and didn’t realize that there are different kinds of input file formats (space-delimited, comma-delimited, aligned by columns.  I was creating the file in Mac MS-Excel and saving in comma separated values (.CSV), but there are different forms of that within Save-As, and I’m choosing what’s specifically name “comma separated values (CSV)”.

-Because I’m saving as comma delimited, I’ll try:

Data DS;

Infile file1 firstobs=2 dlm=’,’;

Input ID $ Age;


Issue: Within Output Data, there is only data in first row, ID of: ID0001,2

Note: Properties of the .csv file is that it’s opened within MS-Excel.  Maybe the raw .CSV file needs to be saved differently.

Note: Now I’m finding myriad ways of doing this, including right-clicking on the file1.csv (in SAS Studio), selecting “Import Data”, and accepting all the defaults – does everything for me.

Note: I need to dig deeper into differences between file formats, exporting, importing.  Will probably be a different blog post.

-This is the code that was auto-generated when I right-clicked on the data file and chose to “Import Data”:

/* Generated Code (IMPORT) */
/* Source File: file1.csv */
/* Source Path: /folders/myfolders */
/* Code generated on: 6/9/19, 9:01 AM */


FILENAME REFFILE ‘/folders/myfolders/file1.csv’;




Note: SAS is using various variables like “DBMS”.  This gives me some clues on what’s really required for importing files.


Note: This one didn’t quite work as planned.  I didn’t see the “flag” after running it.  Need to work on this one.

proc sort data=sashelp.class out=class;
by sex height;

data class2;
set class;
by sex height;
if then flag = “Shortest”;
else if then flag = “Tallest”;

Statistical Variables

-SAS has a forte, of course, of statistics.  Appears easy to run a program to request a bunch of data.  The data set is something that comes with SAS University Edition.

Proc univariate;

-This gives results of mean and standard deviation (stdev)

Proc means;

-This gives results of frequencies, with various tables

Proc Freq;
Table Make * DriveTrain;

Proc SQL – Retrieving data from dataset and manipulating it

-This is the primary reason I’m working with SAS University Edition – to learn and practice SQL with various relational databases.

-Example of some code is:

Proc sql;            (SQL commands to retrieve data from data set and do things like sorting)
select make, model, msrp     (focus on specific variables)
from      (location of the dataset)
where make = “Audi”   (subsetting within a variable for a specific field)
order by msrp;    (sorting the results by a specific field)

Proc SQL – Summarizing Data

Proc sql;   (Using SQL commands within SAS)
select make,   (Select a specific field within dataset)
count(make) as n,   (Count up the number of entries by make, and return the count)
mean(msrp) as mean_msrp   (find the mean within each grouping of make)
from   (pull data from this dataset)
group by make;   (group together by make)

Proc SQL – Creating table (data set)

Proc sql;  (SQL commands within SQL)
create table bigfish as  (will create a table and call it bigfish)
select *  (go into dataset and select all fields within the dataset)
from  (specific dataset)
where weight >1000;   (only pull data over a certain weight)

SAS Macro

-I’m going to hold off on this for the moment.  Need to get more comfortable with the manual stuff before automating with scripts.

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