Scatter Plot
A Scatter Plot Chart is used to analyze patterns in bivariate data by plotting values along both the horizontal (X) and vertical (Y) axes. Each point on the chart represents a pair of values, allowing users to identify trends, correlations, clusters, and outliers.
Scatter plots are widely used in statistical analysis, quality control, and exploratory data analysis to show how much one variable is related to another.
Best Situations to Use
Use a scatter plot when:
You need to find the relationship between two or more variables.
Analyzing potential causes of problems or deviations in data.
Identifying clusters, trends, or anomalies in large datasets.
Examples:
Comparing advertising spend vs. sales revenue.
Finding correlations between temperature and electricity usage.
Analyzing student study hours vs. exam scores.
Identifying root causes in process control data.
Variations
Scatter plots can be enhanced with additional features:
Add-up Filters – Use combo boxes or filters to refine displayed data.
Differentiate by Type – Assign different shapes or colors for categories.
Range Indicators – Highlight ranges dynamically with color coding.
Properties
General
Component Name – Auto-generated unique identifier.
Position (Left, Top) – Placement coordinates on the canvas.
Height / Width – Set chart dimensions.
Initial Visibility – Show/hide chart on load.
Max Button – Enable maximize option.
Base Type – Choose between Gradient or Plain.
Luminance – Adjust brightness for visual effect.
Drag and Zoom – Allow users to zoom into chart regions.
Actions – Define interactivity (e.g., click or hover actions).
Animation – Enable smooth transitions on load/update.
Tooltip
Show/hide tooltips.
Supported types: None, Default.
Configure tooltip background, opacity, border color, font size, and width.
Set decimal precision for numerical values. ⚠️ Note: Use Custom Tooltip for advanced configuration.
Range Indicators
Define custom ranges with color coding.
Add or delete ranges and configure range names, limits, and colors.
Enable Dynamic Range Colors for automatic assignment.
Option to display Range Color Legend in preview.
Background & Styling
Gradient rotation, opacity, and multiple colors.
Borders (color, width, radius).
Shadows with configurable color and transparency.
Title & Subtitle
Show/hide title and subtitle.
Customize text (color, size, style, weight, family, alignment, decoration).
Option to show dataset description dynamically.
Axes
X-Axis
Show/hide axis line.
Customize label font (color, size, style, weight).
Rotate or tilt labels.
Add tick marks, markers, and dataset descriptions.
Auto-scale or define min/max values.
Threshold support: Minimum/Maximum thresholds for X-axis.
Y-Axis
Show/hide axis line.
Configure label fonts (color, size, style, weight).
Add axis descriptions.
Auto-scale or define min/max values.
Threshold support: Minimum/Maximum thresholds for Y-axis.
Legend
Show/hide legend.
Customize font (color, size, style, weight, decoration).
Option to hide legend on load.
Formatter
Units (%, $, count).
Precision (decimal places).
Currency formatting.
Number formatting (Indian or International).
Value positioning (Prefix/Suffix).
Axis Setup
Auto Axis Setup – Automatically scale axes.
Base Zero – Ensure axis starts at zero.
Min/Max Values – Manually set ranges.
Marker Lines – Add vertical, horizontal, or zero lines.
Customize marker color and opacity.
Export Options
Enable context menu for exporting.
Supported formats: Excel, CSV, JPEG, PNG, PPT, PDF, Print.
Customize export heading, subheading, and file name.
Define global export type (Screenshot or Tabular).
Dataset Properties
Map dataset fields under X Field and Y Field.
Configure properties and indicators for effective display.
Use different colors or shapes to differentiate categories.
Example Use Cases
Finance: Identify relationships between investment amount and return.
Marketing: Correlate campaign spend with conversions.
Healthcare: Study dosage levels vs. patient response.
Operations: Compare process variables to find inefficiencies.
Sample Data Setup:
X-Axis Field: Independent variable (e.g., Advertising Spend).
Y-Axis Field: Dependent variable (e.g., Sales Revenue).
⚠️ Note:
Both X and Y fields must be numeric.
Colors and shapes can be used to represent categories or clusters.