> ## Documentation Index
> Fetch the complete documentation index at: https://cubed3-igor-docs-cartesian-chart-builder.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Charts

> Visualize query results as charts, tables, KPIs, and maps directly inside Cube workbooks.

Every tab in a Cube workbook has a chart panel. Once your query returns results, switch to the chart panel to pick a visualization type and configure how the data is displayed — from a simple bar chart to a composable KPI tile or a fully custom Vega-Lite spec.

## Chart types

Cube has built-in support for bar, line, area, pie, scatter, heatmap, KPI, map, boxplot, and more. See the [chart types overview](/docs/explore-analyze/charts/chart-types) for a full list and guidance on which type fits which data shape.

### Selecting a chart type

Chart type icons at the top of the chart panel let you quickly switch between common layouts — grouped vs. stacked bars, line vs. area, table vs. chart view — without opening the full configuration panel.

When you run a query on a new tab, Cube shows the chart type picker rather than picking for you. It outlines the type that best fits your query and labels it **Recommended** — see [Recommended chart type](/docs/explore-analyze/charts/chart-types#recommended-chart-type) — but choosing one is always your action. Any manual configuration you apply is preserved when you change query fields.

On a bar, line, area, or scatter chart the type shown on the button is derived from the fields you assigned rather than set separately, and picking a tile edits those fields instead of resetting them — see [the chart type follows the fields](/docs/explore-analyze/charts/configuration/fields#the-chart-type-follows-the-fields).

### Resetting chart settings

Sections of the configuration panel — fields, style, pivot, column widths — each carry their own **Reset** control, which clears that section back to its defaults. Resetting does not change the chart type you picked.

## Generate charts with AI

Describe the visualization you want in plain language — for example, *"show this as a stacked bar grouped by status"* — and the AI agent will build and configure it. You can also let the agent auto-suggest the best chart for your query results. This is a separate mechanism from the **Recommended** outline in the chart type picker: the agent writes a Vega-Lite spec and applies it, while the recommendation only marks a built-in type for you to pick.

Charts generated by the AI are written as [Vega-Lite v5](https://vega.github.io/vega-lite/) specs and can be further edited in the [custom visualization](/docs/explore-analyze/charts/custom) spec editor.

## Configure charts

Adjust the appearance of any chart through the configuration panel:

* **[Fields](/docs/explore-analyze/charts/configuration/fields)** — Measures, marks, axis sides, break-downs, and orientation
* **[Axes & series style](/docs/explore-analyze/charts/configuration/axes)** — Per-measure appearance, axis titles, grid lines, scale, and reference lines
* **[Color & legend](/docs/explore-analyze/charts/configuration/color-and-stacking)** — Color palettes and legend placement
* **[Small multiples](/docs/explore-analyze/charts/configuration/small-multiples)** — One panel per value of a dimension
* **[Tooltips](/docs/explore-analyze/charts/configuration/tooltips)** — Fields shown on hover
* **[Data labels](/docs/explore-analyze/charts/configuration/data-labels)** — Values displayed directly on chart marks

## Custom visualizations

When the built-in chart types don't cover your use case, write a raw [Vega-Lite spec](/docs/explore-analyze/charts/custom) or use an HTML template with Handlebars. Both options give you complete control over the rendered output.