A data engineer wants to add a new column `discounted_price` to a PySpark DataFrame `df` that equals `price * 0.9`. Which PySpark method should they use?

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B. df.withColumn(\discounted_price\, col(\price\) * 0.9). In PySpark, `withColumn(columnName, columnExpression)` is the method for adding a new column or replacing an existing column on a DataFrame. It returns a new DataFrame with the additional column. `createTempView` registers a view, not a column. `select` returns a DataFrame with only the selected columns, dropping others. `rename` is not a PySpark DataFrame method; the correct method is `withColumnRenamed`.

A data engineer wants to add a new column `discounted_price` to a PySpark DataFrame `df` that equals `price * 0.9`. Which PySpark method should they use?

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A data engineer wants to add a new column discounted_price to a PySpark DataFrame df that equals price * 0.9. Which PySpark method should they use?

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Discussion

A data engineer wants to add a new column `discounted_price` to a PySpark DataFrame `df` that equals `price * 0.9`. Which PySpark method should they use?