Which of the following code blocks returns a DataFrame containing only the rows from DataFrame storesDF where the value in column sqft is less than or equal to 25,000 OR the value in column…

Question

Options

• AstoresDF.filter(col("sqft") <= 25000 and col("customerSatisfaction") >= 30)
• BstoresDF.filter(col("sqft") <= 25000 | col("customerSatisfaction") >= 30)
• CstoresDF.filter(col(sqft) <= 25000 or col(customerSatisfaction) >= 30)
• DstoresDF.filter(sqft <= 25000 | customerSatisfaction >= 30)
• EstoresDF.filter(col("sqft") <= 25000 or col("customerSatisfaction") >= 30)

• A
  6% (1)
• B
  88% (14)
• E
  6% (1)

Explanation

In PySpark, the bitwise OR operator | must be used to combine Column expressions with logical OR. Python's built-in or keyword short-circuits and returns one of the operands rather than combining Column expressions, so options A and E using 'and'/'or' will not produce the correct boolean Column. Option B - storesDF.filter(col('sqft') <= 25000 | col('customerSatisfaction') >= 30) - correctly uses | between two Column conditions. Option C omits quotes around column names. Option D omits col() wrappers.

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