Chart types

Overview of all built-in chart types available in Cube workbooks.

Cube includes a library of built-in chart types covering the most common visualization patterns. Each type is designed for specific data shapes — choose the one that best fits your query structure and the question you’re answering.

• Bar
• Line
• Area
• Scatter
• Pie & donut
• Heatmap
• Boxplot
• Table
• KPI
• Map
• HTML

For configuration options that apply across chart types — axes, color, series settings, tooltips — see Configure charts.

Recommended chart type

When your query returns a result, Cube outlines the one chart type that best fits it and labels it Recommended. It is a suggestion: every other available type stays selectable, and the outline yields as soon as you pick a type in that picker.

Cube never applies a chart type for you. The recommendation is always only outlined, wherever the picker appears, and choosing a type is always your action.

What Cube looks at

The recommendation reads the shape of your query and its result: how many measures, dimensions and time dimensions you selected, how many distinct values each dimension has, and how long the category labels are. It is computed in your browser and is not saved — the suggestion lasts for the current session only.

Where a threshold is involved, it comes from Draco (Moritz et al., Formalizing Visualization Design Knowledge as Constraints, IEEE VIS 2018), which encodes established visualization research as rules: a category axis becomes crowded past 12 values, a color or stacking channel saturates past 10 series, and no axis reads past 30 values.

One number is Cube’s own rather than Draco’s: a mean label length past 16 characters counts as long.

No threshold is applied to the number of rows. A few rules read the row count directly — a KPI needs exactly one row, a heatmap needs its grid at least half filled — but none of them treats “too many rows” as a reason to recommend a different chart, because the row count follows the granularity you chose rather than the shape of your query.

The conditions

Cube first checks whether the query disqualifies every chart, and recommends the table if it does:

Recommendation	When
Table	The query has no measure, two time dimensions, three or more dimensions, or a category past 30 values

A query meeting any of these has no chart encoding that reads well, so the table is the honest answer. Maps are the exception and are still recommended over the table — a map has no category axis to crowd, so a large number of plotted places is normal rather than unreadable.

Otherwise Cube checks these in order and takes the first that matches:

Recommendation	When
Map	The query contains latitude and longitude
KPI	One measure, no dimensions, and a single row
Line	A measure over a time dimension, optionally split by one category of up to 10 values
Scatter	Two or more measures with no time dimension, across one category or several rows — the shape for correlating them
Bar (stacked)	One measure split by two categories, the first up to 12 values and the second up to 10
Heatmap	One measure split by two categories, both past those bounds — the first past 12 values and the second past 10 — whose combinations fill at least half the grid
Bar	One measure across up to 12 categories whose labels average 16 characters or fewer
Bar (horizontal)	The same, where the labels are longer or the categories run past 12

The two bar rows are variants of the same chart type, not separate ones.

Pie, area, boxplot and HTML are never recommended — pick them yourself. Pie’s shape, one measure across a few categories, is the one Bar already answers, and a bar chart compares those values more accurately. All four stay available in the picker like any other chart type.

When nothing is recommended

Cube suppresses the recommendation rather than guessing. You will see no outline when:

• no rule matches the query cleanly;
• a measure over time is split into 11 to 30 series — too many for a color channel, too few to give up on;
• a value it needs is still unknown, such as the number of distinct values in a dimension;
• the result came back empty, so there is nothing to draw;
• the result was truncated by a row limit, so the counts it would read are incomplete;
• you have picked a type by hand in the picker you are looking at. The outline returns the next time you open it — including on the type you applied, since Cube marks the best fit whether or not it is already on screen.