Which statement is true about N/A usage in string columns?

Which statement is true about N/A usage in string columns?

• A. N/A is allowed for all string columns
• B. N/A is not allowed for string columns
• C. N/A must be used for missing values only in numeric columns
• D. N/A is ignored in string processing

Answer: (B)

Missing values in string columns are best represented by a dedicated missing marker, typically NULL, rather than the literal text "N/A." Treating "N/A" as a value makes it a real data point, which can be mistaken for an actual category and complicates filtering, aggregation, and imputation. Using NULL for missingness keeps data consistent across types and simplifies handling missing data in queries and analyses. The other statements don’t fit that practice: storing "N/A" as a string can muddy data quality, and missing data in strings isn’t restricted to numeric columns. Also, "N/A" isn’t automatically ignored during string processing—you’d have to explicitly handle it during preprocessing if you want to treat it as missing.

Missing values in string columns are best represented by a dedicated missing marker, typically NULL, rather than the literal text "N/A." Treating "N/A" as a value makes it a real data point, which can be mistaken for an actual category and complicates filtering, aggregation, and imputation. Using NULL for missingness keeps data consistent across types and simplifies handling missing data in queries and analyses. The other statements don’t fit that practice: storing "N/A" as a string can muddy data quality, and missing data in strings isn’t restricted to numeric columns. Also, "N/A" isn’t automatically ignored during string processing—you’d have to explicitly handle it during preprocessing if you want to treat it as missing.