How do you read in the variables that you need?
Using Input statement with the column pointers like @5/12-17 etc.
Are you familiar with special input delimiters? How are they used?
DLM and DSD are the delimiters that I’ve used. They should be included in the infile statement. Comma separated values files or CSV files are a common type of file that can be used to read with the DSD option. DSD option treats two delimiters in a row as MISSING value. DSD also ignores the delimiters enclosed in quotation marks.
If reading a variable length file with fixed input, how would you prevent SAS from reading the next record if the last variable didn't have a value?
By using the option MISSOVER in the infile statement.If the input of some data lines are shorter than others then we use TRUNCOVER option in the infile statement.
What is the difference between an informat and a format? Name three informats or formats. Informats read the data.
Format is to write the data.Informats: comma. dollar. date.Formats can be same as informatsInformats: MMDDYYw. DATEw. TIMEw. , PERCENTw,Formats: WORDIATE18., weekdatew.
Name and describe three SAS functions that you have used, if any?
LENGTH: returns the length of an argument not counting the trailing blanks.(missing values have a length of 1)
Ex: a=’my cat’;x=LENGTH(a);
Result: x=6…SUBSTR: SUBSTR(arg,position,n) extracts a substring from an argument starting at ‘position’ for ‘n’ characters or until end if no ‘n’.
RESULT: x=’916’TRIM: removes trailing blanks from character expression.
Ex: a=’my ‘; b=’cat’;X= TRIM(a)(b);
SUM: sum of non missing values.Ex: x=Sum(3,5,1);
Returns the integer portion of the argument.
How would you code the criteria to restrict the output to be produced?
Use NOPRINT option.
What is the purpose of the trailing @ and the @@? How would you use them?
@ holds the value past the data step.@@ holds the value till a input statement or end of the line. Double trailing @@: When you have multiple observations per line of raw data, we should use double trailing signs (@@) at the end of the INPUT statement. The line hold specifies like a stop sign telling SAS, “stop, hold that line of raw data”. Trailing @: By using @ without specifying a column, it is as if you are telling SAS,” stay tuned for more information. Don’t touch that dial”. SAS will hold the line of data until it reaches either the end of the data step or an INPUT statement that does not end with the trailing.
Under what circumstances would you code a SELECT construct instead of IF statements?
When you have a long series of mutually exclusive conditions and the comparison is numeric, using a SELECT group is slightly more efficient than using IF-THEN or IF-THEN-ELSE statements because CPU time is reduced.
SELECT GROUP: Select: begins with select group. When: identifies SAS statements that are executed when a particular condition is true.
Otherwise (optional): specifies a statement to be executed if no WHEN condition is met.End: ends a SELECT group.
What statement you code to tell SAS that it is to write to an external file?
What statement do you code to write the record to the file?
PUT and FILE statements.
If you're not wanting any SAS output from a data step, how would you code the data statement to prevent SAS from producing a set?
Options statement: This a part of SAS program and effects all steps that follow it.
Have you ever linked SAS code? If so, describe the link and any required statements used to either process the code or the step itself.· How would you include common or reuse code to be processed along with your statements?
By using SAS Macros.
If you have a data set that contains 100 variables, but you need only five of those, what is the code to force SAS to use only those variable?
Using KEEP option or statement.
Code a PROC SORT on a data set containing State, District and County as the primary variables, along with several numeric variables.
Proc sort data=BY State District County ;
How would you delete duplicate observations?
How would you delete observations with duplicate keys?
How would you code a merge that will keep only the observations that have matches from both sets.
Check the condition by using If statement in the Merge statement while merging datasets.
How would you code a merge that will write the matches of both to one data set, the non-matches from the left-most data.
Step1: Define 3 datasets in DATA step
Step2: Assign values of IN statement to different variables for 2 datasets
Step3: Check for the condition using IF statement and output the matching to first dataset and no matches to different datasetsEx: data xxxmerge yyy(in = inxxx) zzz (in = inzzz);by aaa;if inxxx = 1 and inyyy = 1;run;
What is the Program Data Vector (PDV)? What are its functions?
Function: To store the current obs;
PDV (Program Data Vector) is a logical area in memory where SAS creates a dataset one observation at a time. When SAS processes a data step it has two phases. Compilation phase and execution phase. During the compilation phase the input buffer is created to hold a record from external file. After input buffer is created the PDV is created. The PDV is the area of memory where SAS builds dataset, one observation at a time. The PDV contains two automatic variables _N_ and _ERROR_.
SAS compiles the code· At compile time when a SAS data set is read, what items are created? Automatic variables are created. Input Buffer, PDV and Descriptor Information·
Name statements that are recognized at compile time only?
Name statements that are execution only.
Identify statements whose placement in the DATA step is critical.
DATA, INPUT, RUN.
Name statements that function at both compile and execution time.
In the flow of DATA step processing, what is the first action in a typical DATA Step?
The DATA step begins with a DATA statement. Each time the DATA statement executes, a new iteration of the DATA step begins, and the _N_ automatic variable is incremented by 1.
What is _n_?
It is a Data counter variable in SAS.
Note: Both -N- and _ERROR_ variables are always available to you in the data step.
–N- indicates the number of times SAS has looped through the data step.
This is not necessarily equal to the observation number, since a simple sub setting IF statement can change the relationship between Observation number and the number of iterations of the data step.
The –ERROR- variable ha a value of 1 if there is a error in the data for that observation and 0 if it is not. Ex: This is nothing but a implicit variable created by SAS during data processing. It gives the total number of records SAS has iterated in a dataset. It is Available only for data step and not for PROCS.
Eg. If we want to find every third record in a Dataset then we can use the _n_ as follows
if mod(_n_,3)= 1 then;