Skip to main content
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. For configuration options that apply across chart types — axes, color, series settings, tooltips — see Configure charts. 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 disappears once you pick a type yourself. On a report that has no chart yet, a recommendation Cube is confident about is applied for you, and the report names the rule it followed — for example, Applied Line — a measure over time. Anywhere else the recommendation is only outlined, never applied.

​
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, how long the category labels are, and how many rows came back. Nothing is sent anywhere and nothing is 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. Two numbers are Cube’s own rather than Draco’s, and are tuned by us: a mean label length of 16 characters counts as long, and a result over 5,000 rows counts as large.

​
The conditions

Cube checks these in order and takes the first that matches. Pie is not recommended. Its shape — one measure across a few categories — is the same one Bar answers, and a bar chart compares those values more accurately, so Cube recommends Bar and leaves Pie to you. It remains available in the picker like any other chart type. Table’s conditions are disqualifiers rather than a last preference: a query that meets any of them has no chart encoding that reads well, so the table is the honest answer. Maps are the exception — a map has no category axis to crowd, so a large number of plotted places is normal rather than unreadable. Cube suppresses the recommendation rather than guessing. You will see no outline when:
  • no rule matches the query cleanly;
  • a value it needs is still unknown, such as the number of distinct values in a dimension;
  • the result was truncated by a row limit, so the counts it would read are incomplete;
  • the best fit is the chart type you already applied;
  • you have already picked a type by hand in the picker you are looking at.
Automatic application on an empty report clears a higher bar than the outline does. It happens only for Map, KPI, Line, Scatter and vertical Bar, only when no threshold sits within 20% of the observed value — so a row either way would not change the answer — and never on a truncated result. Stacked bar, heatmap and horizontal bar are offered but never applied for you: stacking asserts that the parts compose the whole, which Cube cannot verify from a filtered result, and the others turn on a judgment of Cube’s own.