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Question 47 - DP-600 discussion

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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 .sumary ()

Does this meet the goal?

A.
Yes
Answers
A.
Yes
B.
No
Answers
B.
No
Suggested answer: A

Explanation:

Yes, the df.summary() method does meet the goal. This method is used to compute specified statistics for numeric and string columns. By default, it provides statistics such as count, mean, stddev, min, and max. Reference = The PySpark API documentation details the summary() function and the statistics it provides.

asked 02/10/2024
Rozsahegyi Jozsef
34 questions
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