1. Based on Learning SAS by Example: A Programmer’s Guide Chapters 1 & 2
By Tasha Chapman, Oregon Health Authority

2. About these trainings

3. What is SAS? Began as a statistical package Also allows users to:
Store data
Manipulate data
Create reports
PDF
Excel
HTML
XML
RTF / Word
Etc. Etc. Etc.

4. What is SAS? Also allows users to: Create graphs Create maps
Send s
Create web applications
Create iPhone Apps
Access R
Schedule regularly run reports
Etc. Etc. Etc.

5. About these trainings Created by Tasha Chapman
Originally held in early 2013
Examples created using SAS version 9.2

6. About these trainings
Material based on Learning SAS by Example: A Programmer’s Guide by Ron Cody
Book is available for state employees using Books 24x7 through the Oregon State Library
Sample code and data files from the book can be found:
Some slides will have a book icon at the corner of the slide with a hyperlink to additional text

7. Training schedule Basic Data Manipulation Week 1: Chapters 1 & 2
Introduction to SAS
Week 2: Chapters 3 & 4 (except 3.9 through 3.14)
Creating permanent SAS datasets
SAS Libraries
Reading raw data from external files
Proc Print / Proc Contents 

8. Training schedule Basic Data Manipulation (cont.)
Week 3: Chapters 5 & 6 (and 3.9 through 3.14)
Creating formats and labels
Reading and writing data from an Excel spreadsheet
Proc Import with a twist
Proc Datasets
Week 4: Chapters 7 & 10 (except 10.6, 10.13)
Conditional processing
Subsetting and combining SAS datasets

9. Training schedule Basic Data Manipulation (cont.)
Week 5: Chapters 9, 11, & 12 (and 10.13)
Working with dates
About SAS Date, Time, and Datetime values
Anydate informat
Working with numeric functions
Working with character functions
Put and Input

10. Training schedule Basic Reporting Week 6: Chapters 14 & 19
Displaying your data (PROC Print)
Global statements (titles, footnotes, system options)
Introducing the Output Delivery System
 Week 7: Chapters 16 & 17 (and 10.6)
Summarizing your data (PROC Means)
Counting frequencies (PROC Freq)

11. Training schedule Basic Reporting (cont.) Week 8: Chapter 15
Creating customized reports (PROC Report)
Week 9: Chapter 18
Creating Tabular Reports (PROC Tabulate)

12. Training schedule Advanced Topics Week 10: Chapter 26
Introduction to SQL
Week 11: Chapters 8, 13 & 24
Iterative processing and looping
Working with multiple observations per subject
By group processing
Working with arrays

13. Training schedule Advanced Topics (cont.) Week 12: Chapter 25
Introduction to SAS Macro Language
%LET
CALL SYMPUT
Week 13: Chapter 20
Generating high quality graphics

14. Training schedule Advanced Topics (cont.)
Week 14: Chapters 21, 22 & 23
The Leftovers!
Restructuring SAS datasets (PROC Transpose)
Using advanced features of user-defined formats and informats
Using advanced input techniques
Saving and storing macros

15. SAS Display Manager

16. Details about jobs you’ve run, including error messages
Log:
Details about jobs you’ve run, including error messages
Explorer Window:
See libraries and SAS datasets
Enhanced Editor:
Where you write your SAS code

17. List of previously run results
Results tab:
List of previously run results
Output Window:
Basic view of results and output
(Also known as “Listing Destination”)

18. Run:
Submits your SAS code
(“The Running Man”)

19. You can submit the program as a wholeor
Run only a portion of highlighted code

20. Chunks of code will be processed in the order you RUN them, not necessarily in the order you wrote them

21. The elements of a SAS program

22. Read and write data, manipulate data, perform calculations, etc.
DATA steps:
Read and write data, manipulate data, perform calculations, etc.
Every DATA step creates a new dataset

23. Every SAS program can have multiple DATA and PROC steps
Produce reports, summarize data, sort data,
create formats, generate graphs, etc. etc. etc.

24. Titles, Footnotes, Options, Macros, Libname
Global statements:
Remain in effect until changed by another global statement or SAS session ends
Examples:
Titles, Footnotes, Options, Macros, Libname

25. /* comment statement */
Comment statements:
Ignored by SAS when code is run
Used to write comments to yourself or others or
comment out code you don’t want to run
*comment statement; or
/* comment statement */

26. Programming in SAS SAS is generally forgiving
Code can be written on a single line or multiple lines
Code and variable names not case sensitive
Even accepts some misspellings
Fi The Doo
Semicolons are super important
Colors of Enhanced Editor
Always check your log!!!
Often many ways to do the same thing

27. DATA step examples

28. DATA step examples

29. DATA step examples DATA demographic
“DATA demographic” creates a dataset called “Demographic”
Infile statement reads the text file with the data
Input statement tells SAS what to name the new variables. $ sign after “Gender” indicates that this is a character variable. The remaining variables are numeric.

30. DATA step examples DATA newdemo
“DATA newdemo” creates a dataset called “newdemo”
“SET demographic” references the previous dataset “demographic” as the basis for the new dataset
“BMI =” creates a new variable called “BMI” that is calculated as shown. This is called an assignment statement.

31. PROC step examples

32. PROC step examples

33. PROC step examples PROC freq Creates a basic frequency table with:
Percent
Cumulative Frequency
Cumulative Percent
“DATA=newdemo” references the newdemo dataset
TABLE statement indicates which variable(s) to include
Can use multiple variables and even create cross-tab tables

34. PROC step examples PROC means Creates a basic summary table with: N
Std Dev
Minimum
Maximum
Can specify which statistics to use in table
“DATA=newdemo” references the newdemo dataset
VAR statement indicates which variable(s) to include

35. Good SAS programmers use EXPLICIT step boundaries
Other notes
Step boundaries:
Each step is executed when a step boundary is encountered
Explicit step boundary: RUN or QUIT statement
Implicit step boundary: Beginning of a new PROC or DATA step
Good SAS programmers use EXPLICIT step boundaries

36. Good SAS programmers use EXPLICIT dataset references
Other notes
Referencing datasets:
Most procedures and DATA steps reference an existing dataset
Explicit dataset reference: DATA= or SET statement
Implicit dataset reference: If not explicitly referenced, SAS will use the last referenced dataset
Good SAS programmers use EXPLICIT dataset references

37. SAS Help

38. Where to learn more about SAS
Technical papers
SAS User Groups
Websites
Books
Classes
Learning_SAS_-_Resources_You_Can’t_Live_Without
Popular Websites

39.
Popular Websites

40.
Popular Websites

41. www.ats.ucla.edu/stat/sas Explains both the stats and the SAS code
Popular Websites

42.
Popular Websites

43. SAS Help and Documentation
Popular Websites

44. How to read SAS Documentation
DATA output-SAS-data-set (DROP=variable(s) | KEEP=variable(s)); SET SAS-data-set <options>; BY variable(s); RUN;

45. How to read SAS Documentation
DATA output-SAS-data-set (DROP=variable(s) | KEEP=variable(s)); SET SAS-data-set <options>; BY variable(s); RUN;
DATA, DROP=, KEEP=, SET, BY, and RUN are in uppercase bold because they must be spelled as shown.

46. How to read SAS Documentation
DATA output-SAS-data-set (DROP=variable(s) | KEEP=variable(s)); SET SAS-data-set <options>; BY variable(s); RUN;
output-SAS-data-set, variable(s), SAS-data-set, and options are in italics because each represents a value that you supply.

47. How to read SAS Documentation
DATA output-SAS-data-set (DROP=variable(s) | KEEP=variable(s)); SET SAS-data-set <options>; BY variable(s); RUN;
<options> is enclosed in angle brackets because it is optional syntax.

48. How to read SAS Documentation
DATA output-SAS-data-set (DROP=variable(s) | KEEP=variable(s)); SET SAS-data-set <options>; BY variable(s); RUN;
DROP= and KEEP= are separated by a vertical bar ( | ) to indicate that they are mutually exclusive.

49. Sample datasets

50. R:\Training\SAS\Learning SAS by Example (Cody)\60864
Original zip file in:
R:\Training\SAS\Learning SAS by Example (Cody)\60864

51. Permanent location of all SAS Datasets
Text and CSV:
Text and CSV data files used to create the SAS Datasets

52. For next week…
Read chapters 3 & 4
(skip sections 3.9 through 3.14)