Microsoft Certified Azure Data Engineer Associate · Free Practice Question Easy
Question 31
True or False: In simple terms, you could view DataFrames as you might see in excel, which we could also refer to as a table of data
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A
True
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B
False
Reveal correct answer
Correct answer: A
Explanation
What are dataframes?
Basically you could view DataFrames as you might see in excel. It's like a box with squares in it, that organizes data, which we could also refer to as a table of data.
What does a table of data mean?
It is a single set of two-dimensional data that can have multiple rows and columns in the data. Each row, is a sample of data. Each column is a variable or parameter that is able to describe the row that contains the sample of data.
A DataFrame creates a data structure and it's one of the core data structures in Spark. In Spark, it is seen as a distributed collection of data that is organized into columns that have names.
What you see in Data Engineering is that you start with reading or loading data that can be unstructured, semi-structured, or structured, which is stored in a DataFrame and start transforming that data in order to get insights. You can use different functionalities in order to do so, like using Spark SQL, PySpark, and others.
Usually when you see 'df' in some code it refers to a dataframe.
You can either create your own dataframe as this example shows:
- Python
- new_rows = [('CA',22, 45000),("WA",35,65000) ,("WA",50,85000)]
- demo_df = spark.createDataFrame(new_rows, ['state', 'age', 'salary'])
- demo_df.show()
Or load a file that contains data into a dataframe like in the below example where the open taxi dataset is used:
- Python
- from azureml.opendatasets import NycTlcYellow
- data = NycTlcYellow()
- data_df = data.to_spark_dataframe()
- display(data_df.limit(10))
Once you're at the stage where you'd like to manipulate the data that is stored in a DataFrame, you can use User-Defined Functions (UDFs) that are column-based and help you transform and manipulate the data stored in a DataFrame.
A.
True. In simple terms, DataFrames in Azure can be viewed similarly to how you would see a table of data in Excel. They are structured data representations that allow for easy manipulation and analysis, much like a table in a spreadsheet. That said, they are more advanced data structures that offer additional functionalities and capabilities beyond what a traditional spreadsheet can provide. They are designed for handling large datasets and performing complex data operations efficiently.
B.
In simple terms, DataFrames in Azure can be viewed similarly to how you would see a table of data in Excel. They are structured data representations that allow for easy manipulation and analysis, much like a table in a spreadsheet. That said, they are more advanced data structures that offer additional functionalities and capabilities beyond what a traditional spreadsheet can provide. They are designed for handling large datasets and performing complex data operations efficiently.
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