You have a Fabric tenant with a new semantic model in OneLake. You are using a Fabric notebook to read the data into a Spark DataFrame. You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns.

You implement the following solution: Use the PySpark expression df.show().

Does this solution meet the goal?