Databricks Machine Learning Associate Exam - Topic 2 Question 12 Discussion

Actual exam question for Databricks's Databricks Machine Learning Associate exam

Question #: 12
Topic #: 2

[All Databricks Machine Learning Associate Questions]

A data scientist is wanting to explore the Spark DataFrame spark_df. The data scientist wants visual histograms displaying the distribution of numeric features to be included in the exploration.

Which of the following lines of code can the data scientist run to accomplish the task?

Aspark_df.describe()

Bdbutils.data(spark_df).summarize()

CThis task cannot be accomplished in a single line of code.

Dspark_df.summary()

Edbutils.data.summarize (spark_df)

Show Suggested Answer

Suggested Answer: E

To display visual histograms and summaries of the numeric features in a Spark DataFrame, the Databricks utility function dbutils.data.summarize can be used. This function provides a comprehensive summary, including visual histograms.

Correct code:

dbutils.data.summarize(spark_df)

Other options like spark_df.describe() and spark_df.summary() provide textual statistical summaries but do not include visual histograms.

Databricks Utilities Documentation

by Sabrina at Aug 08, 2024, 04:32 AM

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Roslyn

3 months ago

E looks interesting, but I haven't seen that before.

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Nicholle

3 months ago

Wait, can you really visualize with just one line?

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Daryl

3 months ago

A is just for basic stats, not histograms.

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Donette

4 months ago

I think C is correct, can't do it in one line.

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Cassie

4 months ago

Option D is the way to go for summaries!

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Veronica

4 months ago

I have a feeling that option C could be correct since visualizing histograms might require more than just one line of code.

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Denny

4 months ago

I practiced a question similar to this, and I feel like `dbutils.data(spark_df).summarize()` is not the right syntax for what we need here.

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Ricarda

4 months ago

I think `spark_df.summary()` might be the right choice for getting a summary of numeric features, but I can't recall if it visualizes them.

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Marsha

5 months ago

I remember that `spark_df.describe()` gives summary statistics, but I'm not sure if it includes histograms.

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Dalene

5 months ago

Hmm, I'm not sure if `describe()` will give us the visual histograms the question is asking for. Maybe we need to use a different method or combination of methods to get the full exploration the data scientist wants.

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Junita

5 months ago

I'm pretty confident I know the answer to this one. The `spark_df.describe()` method should give us the summary statistics we need, including the distribution of numeric features.

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Salina

5 months ago

Okay, I think I've got this. The key is to find a method that can generate visual histograms for the numeric features. Let me see what the options are...

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Ashlyn

5 months ago

Hmm, this looks like a tricky one. I'll need to think through the Spark DataFrame methods carefully to figure out the right approach.

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Christoper

5 months ago

I'm a bit confused by the question. Does "visual histograms" mean we need to generate actual plots, or is there a way to just get the summary statistics in a single line of code?

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An

5 months ago

Okay, I know NVMe is the newer, faster technology, so I'll go with A on this one.

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Ardella

5 months ago

I think the answer is -72 to -67 dBm, but I keep mixing it up with other ranges we studied.

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Zack

5 months ago

Ah, I think I've got it! DataExtractors is the component that takes input data and transforms or outputs it, so that's the answer I'm going with. This is a good example of the kind of question we need to be prepared for on the exam.

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Antonio

2 years ago

I'm not sure, but I think D) spark_df.summary() could also work for this task.

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Tresa

2 years ago

This is a trick question, isn't it? I bet the real answer is hidden in the documentation somewhere. Time to get reading!

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Marshall

2 years ago

No, I believe it's A) spark_df.describe()

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Billy

2 years ago

I think the answer is D) spark_df.summary()

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Isadora

2 years ago

Haha, I bet the answer is hidden in one of those weird-looking Databricks commands. Definitely not going with option E, that's for sure!

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Carline

1 year ago

Let's go with spark_df.summary() then.

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Annice

2 years ago

Yeah, that sounds right. I don't think it's option E either.

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Hayley

2 years ago

I think the answer might be spark_df.summary()

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Corazon

2 years ago

C'mon, there has to be a one-liner to get this done. I don't want to write a bunch of code just to see some histograms.

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Irma

2 years ago

I agree with Kara, because describe() provides summary statistics including histograms.

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Nakita

2 years ago

I'm not sure about this dbutils thing. Isn't there a built-in way to do this in Spark? I think option D might be the way to go.

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Melissa

2 years ago

Option A looks good, but I think we need to do more than just describe the DataFrame. We need to see the actual histograms to get a better understanding of the data.

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Sharee

2 years ago

Option A looks good, but I think we need to do more than just describe the DataFrame. We need to see the actual histograms to get a better understanding of the data.

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