DP-100 Question #378: Real Exam Question with Answer & Explanation

Question

You manage an Azure Machine Learning workspace. You have a folder that contains a CSV file. The folder is registered as a folder data asset. You plan to use the folder data asset for data wrangling during interactive development. You need to access and load the folder data asset into a Pandas data frame. Which method should you use to achieve this goal?

Options

• Amltable.from_parquet_files()
• Bmltable.from_delimited_files()
• Cmltable.from_data_lake()
• Dmltable.load()

Explanation

To access and load a registered folder data asset containing a CSV file into a Pandas DataFrame for interactive development, a specific method from the mltable library is required.

Common mistakes.

• D. mltable.load() is used to load an already defined MLTable object from an MLTable YAML definition file, not to create one directly from raw source files like CSVs in a folder.

Concept tested. Loading delimited data assets into MLTable for Pandas

Reference. https://learn.microsoft.com/en-us/azure/machine-learning/how-to-read-write-data-v2?tabs=cli#create-mltable-data-assets

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