The code block shown below should return an exact copy of DataFrame transactionsDf that does not include rows in which values in column storeId have…

transactionsDf.where(transactionsDf.storeId!=25)

Correct. DataFrame.where() is an alias for the DataFrame.filter() method. Using this method, it is

straightforward to filter out rows that do not have value 25 in column storeId.

transactionsDf.select(transactionsDf.storeId!=25)

Wrong. The select operator allows you to build DataFrames column-wise, but when using it as

shown, it does not filter out rows.

transactionsDf.filter(transactionsDf.storeId==25)

Incorrect. Although the filter expression works for filtering rows, the == in the filtering condition is

inappropriate. It should be != instead.

transactionsDf.drop(transactionsDf.storeId==25)

No. DataFrame.drop() is used to remove specific columns, but not rows, from the DataFrame.

transactionsDf.remove(transactionsDf.storeId==25)

False. There is no DataFrame.remove() operator in PySpark.

More info: pyspark.sql.DataFrame.where — PySpark 3.1.2 documentation

Static notebook | Dynamic notebook: See test 3,