ThoughtSpot’s new charts
Early Access

Use individual axis when a single measure represents information on its own measuring line. These individual axes can be used to build multivariate charts which are perfect for visualizing multiple measures that have vastly different ranges or distinct business contexts without visual clutter. When multiple measures are added into the measure axis (Y-axis), the system detects ungrouped chips and automatically generates a dedicated chart section.

Use a grouped axis when there is need to add a second layer of dimension to your visualization. It allows you to compare sub-categories within a primary category side-by-side. For instance, when you want to see how different segments sold within a larger group. You are looking at sales by region, but you want to see which Product Category is driving the numbers in each specific region. In such a case, instead of one bar per region, you get a cluster of bars (one for each product) for every region on the X-axis.

A grouped axis is considered as a single entity.

To create a grouped drag a measure chip onto another measure or drop it into an existing group to merge them. An encompassing container immediately wraps the measures, signaling that they are grouped and will share a unified axis scale.

Use a dual axis chart to plot two different measures on the same chart using two separate Y-axes—one on the left and one on the right. These entities on the Y-axes can either be a group or a standalone measure. Dual axis is very useful when you want a performance metrics, like goal versus actual.

Facets partition the chart into a hierarchical grid of sub-sections. Instead of forcing multiple dimensions onto a single, crowded axis, Facets nest your data into distinct, side-by-side modules. This results in enhanced readability, and users can scan complex, multi-dimensional relationships instantly.

Faceting will be the default behavior when there are ≥1 attributes in the x-axis. Users cannot create a concatenated single axis.

Trellis charts, also known as small multiples, are a series of similar graphs arranged in a grid format, where each individual panel displays a different subset of a dataset using the same scale and axes. By partitioning data into manageable chunks, these charts enhance scalability and ensure clarity by preventing a single view from becoming overloaded. The side-by-side layout drives improved comparisons, making it easy to spot emerging patterns or trends across complex datasets. Furthermore, granular customization settings provide total control over subplot aesthetics, from titles and borders to specific color schemes, ensuring the final output is both professional and precise.

Dragging an attribute in the trellis section, will create these small multiples based on the values of the attribute.