Histogram Chart
A Histogram Chart is similar to a bar chart but groups values into continuous ranges (bins). Each bar represents the frequency of values falling within a specific interval, making it ideal for visualizing the distribution of data.
Unlike a vertical bar chart, the X-axis in a histogram is continuous, not categorical. This allows users to quickly understand where most values fall, identify patterns of variation, and detect outliers.
Histograms are widely used to summarize large datasets, assess process performance, and compare results against specification limits.
Best Situations to Use
Use a histogram when:
You need to summarize large datasets graphically.
Identifying frequent values and their distribution is important.
Comparing process outcomes with specification limits.
You want to highlight variability within a dataset.
Examples:
Analyzing customer age distribution.
Comparing manufacturing process output against tolerance limits.
Visualizing exam score distributions.
Variations
Histograms can be styled and customized in different ways:
Default Histogram – Standard distribution visualization.
Histogram with Data Labels – Displays actual values on each bar.
Base & Border Styling – Rectangle, Cylinder, or custom base with border colors.
Gradient Charts – Apply gradient styles (Gradient 1, 2, 3).
Properties
General
Component Name – Auto-generated unique identifier.
Position (Left, Top) – Placement on the dashboard.
Height / Width – Define chart dimensions.
Initial Visibility – Toggle visibility on load.
Max Button – Enable maximize option.
Color From Drill – Inherit colors from drill-down operations.
Base Type – Choose bar base style (Rectangle, Cylinder, Plain, Gradient).
Border Color – Customize border styling.
Background & Styling
Gradient rotation, opacity, and multiple color choices.
Borders (color, radius, width).
Shadows with adjustable color and transparency.
Tooltip
Enable/disable tooltips.
Customize tooltip background, border, opacity, font size, and box width.
Configure precision for numerical values.
Enable highlighter mode to emphasize specific bins.
Title & Subtitle
Show/hide title and subtitle.
Customize font (size, color, weight, alignment, decoration).
Option to use dataset values as dynamic titles.
Axes
X-Axis
Continuous scale (bins).
Show/hide axis line.
Customize label fonts (color, size, style, weight).
Rotate or tilt labels for readability.
Add tick marks and markers.
Option to show dataset description.
Y-Axis
Represents frequency/counts.
Show/hide axis line.
Customize label fonts (color, size, style, weight).
Add descriptions and dataset labels.
Legend
Show/hide chart legend.
Customize font properties.
Option to hide legend on load.
Formatter
Set unit type (%, $, count).
Control decimal precision.
Currency formatting.
International/Indian number formatting.
Axis Setup
Auto Axis Setup – Automatically scale axis values.
Base Zero – Start axis from zero.
Min/Max Values – Define axis ranges manually.
Marker Lines – Add vertical, horizontal, or zero marker lines.
Marker Color & Opacity – Customize marker appearance.
Range
Auto Range – Automatically set axis ranges.
Manual Range – Define custom ranges for X and Y axes.
Export Options
Enable context menu for export.
Supported formats: Excel, CSV, JPEG, PNG, PPT, PDF, Print.
Customize export heading, subheading, and file name.
Choose global export type (Screenshot or Tabular).
Example Use Cases
Business Analytics: Customer spend frequency distribution.
Education: Student score distributions to identify grade ranges.
Healthcare: Patient age group distribution.
Manufacturing: Process capability analysis against limits.
Sample Data Setup:
Category Field (X-Axis): Sales (or other continuous variable).
Series Field (Y-Axis): Profit (numeric frequency/counts).
⚠️ Note:
Category fields can be string, numeric, or date types.
Series fields must be numeric.