You are analyzing the data in a Fabric notebook. You have a Spark DataFrame assigned to a variable named df. You need to use the Chart view in the notebook to explore the data manually. Which function should you run to make the data available in the Chart view?

In Microsoft Fabric notebooks, the display() function is specifically designed to render Spark DataFrames as a rich, interactive HTML table. This interactive output is a prerequisite for using the notebook's built-in visualization tools. Once the DataFrame is rendered using display(), you can switch from the default "Table" view to the "Chart" view in the cell output to create various charts and graphs manually without writing additional code.

A. displayMTML is not a recognized or valid function within the standard Spark or Fabric notebook environment for displaying data.

B. The show() function is a standard Spark action that prints the DataFrame's content to the console as plain text, which does not enable the interactive Chart view.

C. The write() function is a Spark DataFrame method used to save the data to an external storage system (e.g., files or tables), not for visualization within the notebook.

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1. Microsoft Learn. (2023). Visualize data in Microsoft Fabric notebooks.

Section: display() command

Content: "The display() command allows you to turn Spark and Pandas DataFrames into rich data visualizations. To use the display() command

call the display(df) function in a notebook cell. The notebook automatically renders a rich plot of the DataFrame." This section explicitly states that display() is the function that enables the rich visualization features

including the chart view.

2. Microsoft Learn. (2023). Explore data in a notebook with Microsoft Fabric.

Section: Visualize data

Content: This tutorial demonstrates the use of display(df) to generate a table that can then be switched to a chart view. It contrasts this with df.show()

which only prints a text representation. The document states

"While the show method is useful for viewing the schema and a sample of the data

a more graphical visualization is often a better way to explore the data. You can do this using the display function..."