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 for all numeric and string columns.

Solution: You run the following PySpark code:

df.describe().show()

df.describe().show()

Does this solution meet the goal?