1. PROC SQL – Select Codes To Master For Power Programming Codes and Examples from SAS.com Nethra Sambamoorthi, PhD Northwestern University Master of Science in Predictive Analytics Program

2. Data Processing Terminologies Across Data Sciences…

3. Why PROC SQL or What Can It Do For Analysts? Generate reports Generate summary statistics Retrieve data from tables or views Combine data from tables or views Create tables, views, and indexes Update the data values in PROC SQL tables Update and retrieve data from database management system (DBMS) tables Modify a PROC SQL table by adding, modifying, or dropping columns PROC SQL can be used in an interactive SAS session or within batch programs, and it Can include global statements, such as TITLE and OPTIONS.

4. An Example of Extracting, Summarizing, and Printing Using Data Step title 'Large Countries Grouped by Continent'; proc summary data=sql.countries; where Population > 1000000; class Continent; var Population; output out=sumPop sum=TotPop; run; proc sort data=SumPop; by totPop; run; proc print data=SumPop noobs; var Continent TotPop; format TotPop comma15.; where _type_=1; run; /* Extracting and summarizing */ /* Sorting to arrange the output */ /* Printing */

5. Creating The Same Using PROC SQL proc sql; title 'Population of Large Countries Grouped by Continent'; select Continent, sum(Population) as TotPop format=comma15. from sql.countries where Population gt 1000000 group by Continent order by TotPop; quit;

6. Countries Table

7. WordCityCoords Table

8. USCityCoords Table

9. UnitedStates Table

10. PostalCodes Table

11. Worldtemps Table

12. Oilprod Table

13. OILRSRVS Table

14. CONTINENTS Table

15. FEATURES Table

16. SELECT statement

17. Three Important Aspects – Describe, Print, Quit /* Helps understand the structure of the table */ PROC SQL; Describe table sql.unitedstates; Quit;

18. SELECT means PRINTING is Included Unless SELECT * /* all columns */ SELECT city, state /* specific columns */ SELECT distinct continent /* specific columns but avoid dup */ So it is possible to run this

19. The output is…

20. Suppress column headings…

21. Calculated columns and alias name…

22. Retrieving Data From Multiple Tables Means we are JOINING tables If there is no JOIN statement, it means (1) Cartesian product of records [no subset condition ] or (2) inner joins [ we need some subset condition] Alias names can be used for tables too; it helps simplify calling specific columns of a table

23. SELECT … FROM table1, table2; A Cartesian Product

25. Order the output from INNER JOIN INNER JOIN can be used explicitly

26. INNER JOIN with comparison values on another column…

27. Effect of Null Values on JOINS

28. NOT MISSING option

29. Multicolumn JOINS

30. Columns are directly comparable between two tables… Capitals FROM sql.unitedstates City FROM sql.uscitycoord Postalcodes FROM sql.postalcodes

31. Is it possible to do SELFJOIN?

32. Two Types of OUTERJOIN – LEFTJOIN and RIGHTJOIN

33. FULLJOIN …

34. SPECIALTY JOINS

35. NATURAL is applicable for both LEFT and RIGHT JOIN. The purpose is to reduce verbose to match on multiple common columns… Gives the same output; Non matching rows have missing values

36. Use COALESCE to combine multiple columns to create new matching variables

37. Using SUB QUERY or NESTED QUERY – SINGLE VALUE =

38. Correlated SUBQUERY = NESTED QUERY

39. Where “EXISTS” option

40. Multiple NESTED QUERY

41. Combine a JOIN with a SUBQUERY

42. QUERY strategies…

43. UNION is ROWWISE (PROC APPEND), while JOIN is COLUMNWISE (MERGE by) Keep the dups

44. OUTER UNION = KEEP ONLY FROM – Key word EXCEPT

47. To overlay data better: keyword CORRESPONDING