Overview

A Clustered Column Chart displays values for different sub-categories grouped (clustered) side-by-side within each main category along the X-axis. This type of chart is useful for comparing multiple series within and across categories.

Unlike stacked charts, clustered charts do not aggregate values into a single bar — instead, each series retains its own bar for direct comparison.

When to Use

• To compare multiple series across a shared category.
• To highlight relative performance of sub-categories.
• To avoid stacking when aggregated values are not meaningful.
• When the goal is to preserve series independence visually.

Data Structure

Clustered Column Charts support two data formats:

Method 1: Wide Table Format (Multiple Measures)

Each sub-category (e.g., Type A, Type B...) is stored in its own column. Each row represents one main category (e.g., Q1, Q2...).

Component Configuration:

• X-Axis: Category
• Measures: Type A, Type B, Type C, Type D

Example Data:

Category	Type A	Type B	Type C	Type D
Q1	30	70	20	65
Q2	40	30	20	10
Q3	60	60	30	10
Q4	25	35	85	15

Chart Example:

Method 2: Long Table Format (Dimension + Measure)

Each row represents a unique combination of main category and sub-category, with the corresponding measure value.

Component Configuration:

• X-Axis: Category
• Legend: Type
• Measure: Sales

Example Data:

Category	Type	Sales
Q1	Type A	40
Q1	Type B	55
Q1	Type C	25
Q2	Type A	50
Q2	Type B	30
Q2	Type C	15
Q3	Type A	30
Q3	Type B	40
Q3	Type C	70
Q4	Type A	35
Q4	Type B	45
Q4	Type C	30

Chart Example:

Notes

• Bars for each sub-category are rendered side-by-side within each main category group.
• Colors are used to differentiate sub-categories.
• Enables direct comparison between sub-categories without stacking.
• Supports tooltips, filters, and style customizations.