You have a Fabric tenant that contains a new semantic model in OneLake. You use 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. Solution: You use the following PySpark expression: df.show() Does this meet the goal?
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