Hotspot Question You have an Azure Synapse notebook. You need to create the visual shown in the following exhibit (chart 1). How should you complete the code? To answer, select the appropriate…

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Explanation

This question tests your ability to create a visualization (chart) in an Azure Synapse Analytics notebook using PySpark or Python/Pandas by writing the correct chart-rendering code. You must select the right library method and chart type to reproduce the target visual.

Approach. In Azure Synapse notebooks, visualizations are typically created using the built-in display() function combined with DataFrame operations, or by using matplotlib/seaborn libraries. The correct approach depends on the chart type shown in the exhibit: for a built-in Synapse chart, you would call display(df) and configure chart options, while for a custom chart you would use matplotlib (e.g., df.plot(kind='bar') or plt.plot()) followed by plt.show(). If the exhibit shows a specific chart type like a bar chart or line chart, you must match the correct .plot() kind parameter ('bar', 'line', 'pie', etc.) and ensure the correct columns are mapped to the x and y axes.

Concept tested. Creating data visualizations in Azure Synapse Analytics notebooks using PySpark DataFrames with the display() function or Python plotting libraries (matplotlib/seaborn), including selecting the correct chart type and axis mappings.

Reference. https://learn.microsoft.com/en-us/azure/synapse-analytics/spark/apache-spark-data-visualization

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