Visualization types in Databricks
This article outlines the types of visualizations available to use in Databricks.
A boxplot shows the distribution summary of numerical data, optionally grouped by category. See Boxplot visualization.
Charts: line, bar, area, pie
Visualizations that use X and Y axes are called charts. See Chart visualizations. The charts covered include:
A cohort analysis examines the outcomes of predetermined groups, called cohorts, as they progress through a set of stages. See Cohort visualization.
A histogram plots the frequency that a given value occurs in a dataset. See Histogram visualization.
There are two types of map visualizations: choropleth and marker. See Map visualization.
The heatmap visualization allows you to visualize numerical data using colors. See Heatmap visualization.
The pivot table visualization aggregates records from a query result into a new tabular display. It’s similar to PIVOT or GROUP BY statements in SQL. See Pivot table visualization.
The table visualization displays data in a standard table, but with the ability to manually reorder, hide, and format the data. See Table visualization.