What command is used to convert a Spark DataFrame to a Pandas DataFrame?

The command used to convert a Spark DataFrame to a Pandas DataFrame is toPandas(). This method is specifically designed to facilitate the transition from the distributed nature of Spark DataFrames, which handle large datasets across multiple nodes, to the single-node, in-memory structure of Pandas DataFrames. It allows users to leverage the powerful data manipulation capabilities of Pandas once the data is manageable within memory, enabling easier exploration and analysis of smaller datasets after they have been processed with Spark.

This command effectively pulls the data from the Spark DataFrame into the driver node and presents it as a Pandas DataFrame, making it convenient for tasks that require immediate data processing in Python, particularly for data scientists and analysts familiar with Pandas.

The other options do not correspond to valid commands in this context. Each fails to represent a legitimate function for converting Spark DataFrames to Pandas DataFrames, which highlights the importance of understanding the specific methods available in the PySpark API for effective data handling.