Databricks Exam Databricks Machine Learning Associate 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, 05:32 AM

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Donette

2 days ago

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

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Cassie

8 days ago

Option D is the way to go for summaries!

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Veronica

14 days 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

19 days 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

24 days 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

1 month ago

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

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Dalene

1 month 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

1 month 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

1 month 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

1 month 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

1 month 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

1 month ago

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

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Ardella

1 month 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

1 month 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

1 year ago

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

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Tresa

1 year 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

1 year ago

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

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Billy

1 year ago

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

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Isadora

1 year 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

1 year ago

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

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Hayley

1 year ago

I think the answer might be spark_df.summary()

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Corazon

1 year 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

1 year ago

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

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Nakita

1 year 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

1 year 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

1 year 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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