Microsoft Exam DP-600 Topic 1 Question 7 Discussion

Actual exam question for Microsoft's DP-600 exam

Question #: 7
Topic #: 1

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.explain()

Does this meet the goal?

AYes

BNo

Show Suggested Answer

Suggested Answer: B

by Virgina at Mar 05, 2024, 05:15 PM

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Shonda

9 months ago

That's a good point, Miriam. It can help us optimize our code before calculating statistics.

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Miriam

9 months ago

I still think df.explain() could be useful in understanding the DataFrame structure before applying descriptive statistics functions.

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Theron

9 months ago

That makes sense. df.describe() would be more appropriate for calculating the statistics we're looking for.

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Dominga

10 months ago

I think we should use descriptive statistics functions like df.describe() to get the summary statistics we need.

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Shonda

10 months ago

I agree with Theron. df.explain() only displays the execution plan for a DataFrame.

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Theron

10 months ago

I think using df.explain() in PySpark would not give us the min, max, mean, and standard deviation values for all columns.

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Mirta

11 months ago

You know, I heard that the exam writers love to include tricky questions like this, just to see if we're paying attention. I bet they're laughing at us right now for even considering `df.explain()`.

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Anabel

10 months ago

A) Yes

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Ivan

10 months ago

I think they're just trying to trip us up.

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William

10 months ago

A) Yes

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Ben

10 months ago

You're right, they do like to test our attention to detail.

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Kathrine

10 months ago

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Stephaine

10 months ago

A) Yes

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Salena

11 months ago

Exactly! The `df.explain()` function is more for debugging and optimizing the DataFrame operations, not for actually calculating the statistics.

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Lourdes

11 months ago

Yeah, I agree. We need to use functions like `df.agg()` and `df.describe()` to get the statistical summary we need.

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Shaun

11 months ago

I don't think that's the right solution. The `df.explain()` function just shows the execution plan of the DataFrame, it doesn't actually calculate the min, max, mean, and standard deviation.

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