Exam Databricks-Machine-Learning-Associate Topic 2 Question 50 Discussion

Actual exam question for Databricks's Databricks-Machine-Learning-Associate exam
Question #: 50
Topic #: 2
A data scientist is wanting to explore summary statistics for Spark DataFrame spark_df. The data scientist wants to see the count, mean, standard deviation, minimum, maximum, and interquartile range (IQR) for each numerical feature.
Which of the following lines of code can the data scientist run to accomplish the task?

Suggested Answer: A Vote an answer

The summary() function in PySpark's DataFrame API provides descriptive statistics which include count, mean, standard deviation, min, max, and quantiles for numeric columns. Here are the steps on how it can be used:
Import PySpark: Ensure PySpark is installed and correctly configured in the Databricks environment.
Load Data: Load the data into a Spark DataFrame.
Apply Summary: Use spark_df.summary() to generate summary statistics.
View Results: The output from the summary() function includes the statistics specified in the query (count, mean, standard deviation, min, max, and potentially quartiles which approximate the interquartile range).
Reference
PySpark Documentation: https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.sql.DataFrame.summary.html

by Vanessa at Sep 17, 2026, 09:26 AM

Limited Time Offer

15%

Off

Get Premium Databricks-Machine-Learning-Associate Questions as Interactive Self Test Engine or PDF

Comments

Chosen Answer:
This is a voting comment (?) , you can switch to a simple comment.
Switch to a voting comment New
Nick name: Submit Cancel
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.
0
0
0
10