You have a SAS dataset named 'CUSTOMERS' with the following structure: Customer_lD,First_Name,Last_Name,Email 123,John,Doe,[email protected] 456,Jane,Smith,[email protected] 789,Peter,Jones,[email protected] You need to export this data to a CSV file named 'customers_export.csv' with the following requirements: 1. The data should be exported in a specific order: 'Customer ID', 'Last Name', 'First Name', 'Email'. 2. The data should be delimited by a semicolon (;) instead of the default comma (,). 3. The 'Email' column should be enclosed in double quotes ("). Which of the following PROC EXPORT statements would achieve this correctly? (Select all that apply)
Correct Answer: A,C,E
The correct options are A, C, and E. Here's why: PROC EXPORT is used to export SAS datasets to external files. DATA=CUSTOMERS specifies the SAS dataset to be exported. OUTFILE='customers_exportcsv' indicates the location and name of the CSV file to be created- DBMS=CSV specifies the type of data source as a CSV file. REPLACE ensures any existing file with the same name is ovenvritten. PUTNAMES=YES tells SAS to include variable names in the first row of the CSV file- DELIMITER=';' sets the delimiter to a semicolon (;). QUOTECHAR='"' encloses the 'Email' column values within double quotes. ORDER=Customer_lD Last _ Name First_Name Email specifies the desired order for the columns. Option A correctly uses the PROC EXPORT statement to achieve the desired formatting and column order Option C uses a DATA step to enclose the 'Email' column values in double quotes before exporting- The code uses the double quote character (") in conjunction with the concatenation operator (II) to achieve this- This approach allows the data to be formatted in the specified way, as expected for this scenario. Option E uses a DATA step to enclose the 'Email' column values in double quotes before exporting. This approach uses the single quote character (') in conjunction with the concatenation operator (II) and double quotes (") to achieve this. This is also a valid solution and will produce the desired output Why other options are incorrect Option B. Attempts to use the QUOTE() function, which is not a valid function in SAS- The QUOTE() function is available in some other programming languages but not within SAS Option D: Uses unnecessary additional quote characters that will result in incorrect formatting of the 'Email' column. Since the QUOTECHAR option is already specified as "", the extra quotes will lead to incorrect output when exporting to the CSV file.
A00-215 Exam Question 57
You are working with a dataset containing a variable 'Region' with values like 'Northeast', 'Southeast', 'Midwest', etc. You want to create a report that displays these values with more user-friendly labels like 'NE', 'SE', 'MW' respectively, but you don't want to permanently change the dat a. Which PROC step and LABEL statement combination would you use?
Correct Answer: D
PROC PRINT can use the LABEL statement to assign temporary labels tovariables within the report. The syntax 'LABEL Region = 'NE' I Region = 'SE' / Region = 'MW' assigns the desired labels for specific values of the 'Region' variable. This approach provides temporary changes only for the report output, leaving the original data untouched. Option A is incorrect as it only assigns one label and doesnt consider multiple values. Options B and E use PROC SQL to create a new variable 'RegionLabel' with the desired labels, which is a valid solution, but doesnt utilize the LABEL statement specifically. Option C is incorrect because PROC REPORT doesn't have the LABEL statement for temporary attributes, it uses the 'define' statement to define attributes for report columns.
A00-215 Exam Question 58
You have two datasets, 'SALES' and 'CUSTOMER', both containing a common variable 'CUST ID'. You need to create a new dataset 'SALES WITH CUSTOMER INFO that includes all sales records from 'SALES' and corresponding customer information from 'CUSTOMER' based on 'CUST ID'. Which of the following MERGE statements will achieve this, assuming both datasets are sorted by 'CUST ID'?
Correct Answer: A
The correct answer is A The MERGE statement with the BY clause will automatically match observations based on the common variable 'CUST_ID', creating a new dataset with combined information from both datasets. Options B, C, D, and E use conditional statements that are unnecessary and would not accurately merge the datasets. Option B would only output observations from the 'SALES' dataset Option C would output only observations where both datasets have matching 'CUST ID'. Option D would only output the first observation of each dataset, and Option E would only output observations that occur after the first observation in each dataset. The MERGE statement in option A is the most straightforward and efficient way to merge the datasets horizontally.
A00-215 Exam Question 59
You have a dataset named 'SALES' with variables 'Region', 'Product', and 'Quantity'. You want to create a new variable 'SalesValue' based on the following logic: If 'Product' is 'A', then 'SalesValue' = 'Quantity' , 10; If 'Product' is 'B', then 'SalesValue' = 'Quantity' , 15; Otherwise, 'SalesValue' = 'Quantity' , 20. Which code snippet correctly implements this logic in the DATA step?
Correct Answer: A
Option A is the correct code snippet as it uses the correct syntax for the IF-THEN-ELSE statement in SAS. The statement checks the value of the Product' variable and assigns 'SalesValue' accordingly. Option B uses separate IF statements without the ELSE clause, which can lead to incorrect calculations if multiple conditions are met. Option C has redundant IF statements and doesn't consider the 'otherwise' condition. Option D checks for specific values (C and D) in the 'else' clause which might not be appropriate based on the given logic. Option E is the same as option A.
A00-215 Exam Question 60
You have a SAS dataset 'CUSTOMERS' with variables 'CUSTOMER ID', 'NAME', and 'CITY'. You need to create a new dataset 'ACTIVE CUSTOMERS' containing only those customers who have made purchases in the past 3 months. You have another dataset 'ORDERS' with variables 'ORDER ID', 'CUSTOMER ID', and 'ORDER DATE'. How would you use the SET statement to achieve this?
Correct Answer: C
It uses the 'SET' statement to read the 'CUSTOMERS' dataset. The ' if statement filters the customers based on whether their 'CUSTOMER_ID is present in the 'ORDERS dataset, where the 'ORDER DATE is within the past 3 months- The 'intnx('month', today(), -3)' function calculates the date 3 months prior to today. The 'select distinct' statement ensures that only unique customer IDs are retrieved from the 'ORDERS' dataset- Option A uses 'select CUSTOMER ID , which may result in duplicate customer IDs- Option B uses 'merge' , which combines datasets based on a shared variable, and the 'if statement filters the combined dataset Option D only reads the 'ORDERS dataset and filters by the order date, not considering customer information- Option E checks for any existing customer IDs in the 'ORDERS dataset, not filtering by the order date.
