When a query result contains a string column (categorical data) and a numeric column (a measure), Databricks SQL's auto-charting feature defaults to a bar chart. This visualization type is optimal for comparing a numerical value across distinct categories. In this scenario, the region column serves as the discrete dimension for the X-axis, and the numberofcustomer column provides the corresponding numerical value for the Y-axis, making a bar chart the most logical and automatically selected representation.

A. Violin Chart: This chart is used to visualize the distribution of numerical data, not for comparing a single aggregate value per category. It is not a typical default.

B. Line Chart: Line charts are the default for data with a temporal or continuous numerical component (like a date or timestamp) to show trends, which is not present here.

D. Histogram: A histogram is used to plot the frequency distribution of a single numerical column. The query result has two columns (one categorical, one numerical).

E. There is no default: This is incorrect. Databricks SQL automatically selects a best-effort visualization type based on the query result's schema to provide an initial view.

1. Databricks Documentation

"Visualization types in Databricks": This document describes the use cases for different chart types. It states

"Bar charts represent the change in metrics over a discrete dimension or show proportionality." This directly matches the provided schema of region (discrete dimension) and numberofcustomer (metric).

2. Databricks Documentation

"Create a new visualization": This guide confirms the auto-selection behavior: "When you click Add visualization

Databricks SQL automatically creates a visualization that best matches your query result. It makes a best-effort choice of a useful visualization." This refutes the "no default" option and supports the logic of choosing the most appropriate chart

which is a bar chart in this case.