Which of the following code blocks shows the structure of a DataFrame in a tree-like way, containing both column names and types?

itemsDf.printSchema() Correct! Here is an example of what itemsDf.printSchema() shows, you can see the tree-like structure containing both column names and types: root |-- itemId: integer (nullable = true) |-- attributes: array (nullable = true) | |-- element: string (containsNull = true) |-- supplier: string (nullable = true) itemsDf.rdd.printSchema() No, the DataFrame's underlying RDD does not have a printSchema() method. spark.schema(itemsDf) Incorrect, there is no spark.schema command. print(itemsDf.columns) print(itemsDf.dtypes) Wrong. While the output of this code blocks contains both column names and column types, the information is not arranges in a tree-like way. itemsDf.print.schema() No, DataFrame does not have a print method. Static notebook | Dynamic notebook: See test 3,