Databricks Certified Machine Learning - Associate

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Explanation:

The correct answer is 'All of the above'. The following are options for obtaining summary statistics on a Spark DataFrame:

describe(): Provides count, mean, standard deviation, minimum, and maximum values.
summary(): Incorporates all the features of describe() with the addition of interquartile range (IQR) values.
dbutils.data.summarize: Calculates and displays summary statistics of an Apache Spark DataFrame or pandas DataFrame. This command is available for Python, Scala, and R.

Explanation:

The correct answer is 'All of the above'. The following are options for obtaining summary statistics on a Spark DataFrame:

describe(): Provides count, mean, standard deviation, minimum, and maximum values.
summary(): Incorporates all the features of describe() with the addition of interquartile range (IQR) values.
dbutils.data.summarize: Calculates and displays summary statistics of an Apache Spark DataFrame or pandas DataFrame. This command is available for Python, Scala, and R.

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Real Exam

dbutils.data.summarize(spark_dataframe)

9.8%

spark_dataframe.describe()

17.1%

spark_dataframe.summary()

12.2%

All of the above

61.0%