Which function should you run to make a Spark DataFrame's data available in the Chart view of a notebook?

Which function should you run to make a Spark DataFrame's data available in the Chart view of a notebook?

• A. display
• B. show
• C. render
• D. plot

Answer: (A)

To make a Spark DataFrame visible in the notebook’s Chart view, you feed the DataFrame into the notebook’s visualization system using display. This function is designed to integrate the DataFrame with the notebook’s charting UI, returning a display object that the Chart view can render into interactive charts (bars, lines, etc.). Using display goes beyond just printing data; it activates the notebook’s visualization pipeline so you can switch to Chart view and customize axes and chart types. Printing rows with show shows text output in the cell and doesn’t connect to the charting UI, so it won’t populate the Chart view. The other two options aren’t standard Spark visualization functions, so they won’t enable chart rendering either.

To make a Spark DataFrame visible in the notebook’s Chart view, you feed the DataFrame into the notebook’s visualization system using display. This function is designed to integrate the DataFrame with the notebook’s charting UI, returning a display object that the Chart view can render into interactive charts (bars, lines, etc.). Using display goes beyond just printing data; it activates the notebook’s visualization pipeline so you can switch to Chart view and customize axes and chart types.

Printing rows with show shows text output in the cell and doesn’t connect to the charting UI, so it won’t populate the Chart view. The other two options aren’t standard Spark visualization functions, so they won’t enable chart rendering either.