You have a Fabric tenant containing a new semantic model in OneLake. You use a Fabric notebook to load the data into a Spark DataFrame. You need to evaluate the data by calculating the minimum, maximum, mean, and standard deviation values for all string and numeric columns.

You implement the following PySpark code: df.summary()

Does this solution meet the goal?