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Exam Certified Machine Learning Associate All Questions

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Exam Certified Machine Learning Associate topic 1 question 2 discussion

Actual exam question from Databricks's Certified Machine Learning Associate
Question #: 2
Topic #: 1
[All Certified Machine Learning Associate Questions]

A data scientist has a Spark DataFrame spark_df. They want to create a new Spark DataFrame that contains only the rows from spark_df where the value in column price is greater than 0.
Which of the following code blocks will accomplish this task?

  • A. spark_df[spark_df["price"] > 0]
  • B. spark_df.filter(col("price") > 0)
  • C. SELECT * FROM spark_df WHERE price > 0
  • D. spark_df.loc[spark_df["price"] > 0,:]
  • E. spark_df.loc[:,spark_df["price"] > 0]
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️
by [deleted] at May 31, 2024, 8:24 p.m.

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Deuterium44
2 weeks, 4 days ago
Selected Answer: B
B, given answer is correct
upvoted 1 times
...
Shubhamdh1
3 months ago
Selected Answer: B
spark_df.filter(col("price") > 0) this is correct answer
upvoted 3 times
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Spark_Knight
5 months, 1 week ago
B is correct
upvoted 3 times
...
[Removed]
5 months, 3 weeks ago
Selected Answer: A
Both A and B are valid ways to filter a Spark DataFrame. You could argue that A is slightly "more" correct since option B requires you to import "pyspark.sql.functions.col"
upvoted 2 times
...

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