Implementing Analytics Solutions Using Microsoft Fabric — Question 110
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
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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.describe().show()
Does this meet the goal?
Answer options
- A. Yes
- B. No
Correct answer: A
Explanation
The PySpark expression df.describe().show() is designed to provide summary statistics, which include min, max, mean, and standard deviation for all numeric columns. While it does not include string columns in the statistical summary, the question asks if it meets the overarching goal of evaluating the data, which it does for numeric columns. Therefore, the correct answer is A, while B is incorrect as it disregards the evaluation of numeric data.