Microsoft Exam DP-600 Topic 3 Question 17 Discussion

Actual exam question for Microsoft's DP-600 exam

Question #: 17
Topic #: 3

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?

AYes

BNo

Show Suggested Answer

Suggested Answer: B

The df.show() method also does not meet the goal. It is used to show the contents of the DataFrame, not to compute statistical functions. Reference = The usage of the show() function is documented in the PySpark API documentation.

by Jules at Jul 11, 2024, 02:21 PM

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Janine

10 months ago

I'm sorry, but df.show() is not going to give us the statistical analysis we need. I think the correct answer is 'No' on this one. Let's move on to the next question, where we can hopefully find a more challenging problem to solve.

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Lucina

10 months ago

Yeah, we definitely need a different approach for this.

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Claudio

10 months ago

I agree, df.show() won't give us the stats we need.

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My

11 months ago

Haha, I've seen some lazy solutions in my day, but this takes the cake. df.show()? Really? I bet the answer is 'No' on this one.

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Jame

11 months ago

Nah, this isn't going to cut it. We need to dig deeper into the Spark DataFrame API to get the job done. What is this, PySpark for Dummies?

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Rima

11 months ago

Hmm, df.show() just prints the first few rows of the DataFrame. It doesn't actually calculate any statistical measures. I think we need to use functions like min(), max(), mean(), and stddev() to get the job done.

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Mitsue

11 months ago

Wow, that's a pretty basic solution. I'm not sure it's going to give us the full analysis we need. Where are the min, max, mean, and standard deviation calculations?

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