Tuesday, September 2, 2008

SAS Interview Questions:Base SAS

Very Basic:·

What SAS statements would you code to read an external raw data file to a DATA step?
INFILE statement.

· 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

a=’my cat’;

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’.

data dsn;
RESULT: x=’916’ ;
TRIM: removes trailing blanks from character expression.
Ex: a=’my ‘; b=’cat’;X= TRIM(a)(b); RESULT: x=’mycat’.

SUM: sum of non missing values.Ex: x=Sum(3,5,1); result: x=9.0

INT: 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”.
data dsn;

input sex $ days;
F 53
F 56
F 60
F 60
F 78
F 87
F 102
F 117
F 134
F 160
F 277
M 46
M 52
M 58
M 59
M 77
M 78
M 80
M 81
M 84
M 103
M 114
M 115
M 133
M 134
M 175
M 175

The above program can be changed to make the program shorter using @@ .... 

data dsn;
input sex $ days @@;
F 53 F 56 F 60 F 60 F 78 F 87 F 102 F 117 F 134 F 160 F 277M 46 M 52 M 58 M 59 M 77 M 78 M 80 M 81 M 84 M 103 M 114M 115 M 133 M 134 M 175 M 175

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: 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 reading an external file to produce an external file, what is the shortcut to write that record without coding every single variable on the record?

· 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?
Data _Null_

· What is the one statement to set the criteria of data that can be coded in any step?
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.

· When looking for data contained in a character string of 150 bytes, which function is the best to locate that data: scan, index, or indexc?

SCAN.· 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=one;
BY State District County ;
Run ;

· 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 datasets


data xxx;
merge yyy(in = inxxx) zzz (in = inzzz);
by aaa;
if inxxx = 1 and inyyy = 1;

· 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_.

The Logical Program Data Vector (PDV) is a set of buffers that includes all variables referenced either explicitly or implicitly in the DATA step. It is created at compile time, then used at execution time as the location where the working values of variables are stored as they are processed by the DATA step program(source: http://www2.sas.com/proceedings/sugi24/Posters/p235-24.pdf).

· Does SAS 'Translate' (compile) or does it 'Interpret'? Explain.
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.

· 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 thenwe can use the _n_ as follows

Data new-sas-data-set;
Set old;
if mod(_n_,3)= 1 then;

Note: If we use a where clause to subset the _n_ will not yield the required result.

How do i convert a numeric variable to a character variable?
You must create a differently-named variable using the PUT function.

How do i convert a character variable to a numeric variable?
You must create a differently-named variable using the INPUT function.

How can I compute the age of something?
Given two sas date variables born and calc:

age = int(intck('month',born,calc) / 12);
if month(born) = month(calc) then age = age - (day(born) > day(calc));

How can I compute the number of months between two dates?
Given two sas date variables begin and end:

months = intck('month',begin,end) - (day(end) <>

How can I determine the position of the nth word within a character string?

Use a combination of the INDEXW and SCAN functions:pos = indexw(string,scan(string,n));

I need to reorder characters within a string...use SUBSTR?
You can do this using only one function call with TRANSLATE versus two functions calls with SUBSTR. The following lines each move the first character of a 4-character string to the last:

reorder = translate('2341',string,'1234');
reorder = substr(string,2,3) substr(string,1,1);
How can I put my sas date variable so that December 25, 1995 would appear as '19951225'? (with no separator)

use a combination of the YEAR. and MMDDYY. formats to simply display the value:
put sasdate year4. sasdate mmddyy4.;

or use a combination of the PUT and COMPRESS functions to store the value:
newvar = compress(put(sasdate,yymmdd10.),'/');

How can I put my sas time variable with a leading zero for hours 1-9?
Use a combination of the Z. and MMSS. formats:
hrprint = hour(sastime);
put hrprint z2. ':' sastime mmss5.;

Prepared by Sreeja E V(sreeja@kreara.com) source: kreara.blogspot.com.
Infile has a number of options available.


FLOWOVER is the default option on INFILE statement. Here, when the INPUT statement reaches the end of non-blank characters without having filled all variables, a new line is read into the Input Buffer and INPUT attempts to fill the rest of the variables starting from column one. The next time an INPUT statement is executed, a new line is brought into the Input Buffer.
Consider the following text file containing three variables id, type and amount.
11101 A
11102 A 100
11103 B 43
11104 C
11105 C 67

The following SAS code uses the flowover option which reads the next non missing values for missing variables.

data B;
infile "External file" flowover;
input id $ type $ amount;

which creates the following dataset

MISSOVERWhen INPUT reads a short line, MISSOVER option on INFILE statement does not allow it to move to the next line. MISSOVER option sets all the variables without values to missing.
data B;
infile "External file" missover;
input id $ type $ amount;

which creates the following dataset
Causes the INPUT statement to read variable-length records where some records are shorter than the INPUT statement expects. Variables which are not assigned values are set to missing.
Difference between TRUNCOVER and MISSOVER

Both will assign missing values to variables if the data line ends before the variable’s field starts. But when the data line ends in the middle of a variable field, TRUNCOVER will take as much as is there, whereas MISSOVER will assign the variable a missing value.
Consider the text file below containing a character variable chr.
Consider the following SAS code
data trun;
infile "External file" truncover;
input chr $3. ;

When using truncover option we get the following dataset
data miss;
infile "External file" missover;
input chr $3. ;
While using missover option we get the output

SAS Proficiency Test by Judy Loren

Different Ways to use PUT Statement;


%include statement: which looks like a macro but isn't really, sucks the contents of the just-generated file into the input stream. The result will be that the step will effectively contain all of the rename statements generated in the previous step, accomplishing the renaming of all columns. source:Vancouver_Fall2007/Tips_Tricks.pdf


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