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,