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syncfusion-aspnetmvc-heatmap-chart

Implement HeatMap and Bubble HeatMap visualizations in Syncfusion ASP.NET MVC. Create two-dimensional data visualizations with gradient/fixed colors, configure axes, bind data, customize appearance, and add interactive features. Master data label positioning, legend configuration, tooltip customization, cell selection, and event handling.

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syncfusion/aspnetmvc-ui-components-skills
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September 15, 2026 at 05:06
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syncfusion-aspnetmvc-heatmap-chart
description
Implement HeatMap and Bubble HeatMap visualizations in Syncfusion ASP.NET MVC. Create two-dimensional data visualizations with gradient/fixed colors, configure axes, bind data, customize appearance, and add interactive features. Master data label positioning, legend configuration, tooltip customization, cell selection, and event handling.
metadata
{"author":"Syncfusion Inc","version":"34.1.29","category":"HeatMaps"}
# Implementing HeatMap in Syncfusion ASP.NET MVC The HeatMap control visualizes two-dimensional data where values are represented in gradient or fixed colors. It supports multiple axes types, data binding patterns, legends, tooltips, cell selection, and custom styling for professional data visualization. ## When to Use This Skill Use this skill when you need to: - Create color-coded two-dimensional data visualizations - Display data matrices with gradient or custom color representations - Implement data exploration with cell selection and tooltips - Configure different axis types (Categorical, Numeric, DateTime) - Bind array or JSON data to a HeatMap - Create Bubble HeatMaps for three-variable visualization - Handle HeatMap events and user interactions - Export or print HeatMap visualizations ## Documentation and Navigation Guide ### Getting Started with HeatMap 📄 **Read:** [references/getting-started.md](references/getting-started.md) - Installation via NuGet package - Project setup and namespace configuration - Required script references - Creating your first HeatMap - Minimal working example with sample data ### Working with Data 📄 **Read:** [references/working-with-data.md](references/working-with-data.md) - Array-table data binding patterns - Array-cell data binding approach - JSON-table data structure and mapping - JSON-cell data configuration - Data source initialization and updates - Handling large datasets efficiently ### Configuring Axes 📄 **Read:** [references/axis-configuration.md](references/axis-configuration.md) - Category axis for string labels - Numeric axis for number values - DateTime axis for temporal data - Axis label formatting and customization - Inverted and opposed axis positioning - Multi-level labels and label rotation ### Legend and Color Palettes 📄 **Read:** [references/legend-and-palette.md](references/legend-and-palette.md) - Legend positioning and visibility - Built-in color palettes - Gradient color schemes - Fixed color assignment - Custom palette creation - Legend interaction and styling ### Data Labels and Display 📄 **Read:** [references/data-labels.md](references/data-labels.md) - Enabling and disabling data labels - Label positioning strategies - Label value formatting - Custom label content - Label styling and appearance - Handling label overlap ### Tooltips and Interactivity 📄 **Read:** [references/tooltips.md](references/tooltips.md) - Enabling tooltip functionality - Tooltip content formatting - Template customization - Tooltip styling and appearance - Interactive tooltip positioning - Custom tooltip templates ### Appearance and Rendering 📄 **Read:** [references/appearance-and-rendering.md](references/appearance-and-rendering.md) - Cell styling and customization - Title and subtitle configuration - Responsive chart sizing - SVG and Canvas rendering modes - Theme application - Dimension configuration ### Selection and Interaction 📄 **Read:** [references/selection-and-interaction.md](references/selection-and-interaction.md) - Cell selection modes - Multiple cell selection - Selection styling - Clearing selections programmatically - Cell click events - Selection change events ### Bubble HeatMap Visualization 📄 **Read:** [references/bubble-heatmap.md](references/bubble-heatmap.md) - Bubble HeatMap overview and use cases - Size and color mapping - Three-variable visualization patterns - Bubble sector types - Creating bubble representations - Styling bubble elements ### Event Handling and Callbacks 📄 **Read:** [references/events.md](references/events.md) - Available HeatMap events - Cell click and selection events - Data loading events - Render completion events - Tooltip show/hide events - Custom event handlers - Event parameter structure ## Quick Start Example ```csharp @Html.EJS().HeatMap("container") .Title(title => { title.Text("Sales Trend"); }) .XAxis(xaxis => { xaxis.Labels(new List<string> { "2006", "2007", "2008", "2009", "2010" }); xaxis.ValueType(Syncfusion.EJ2.HeatMap.ValueType.Category); }) .YAxis(yaxis => { yaxis.Labels(new List<string> { "Jan", "Feb", "Mar", "Apr" }); yaxis.ValueType(Syncfusion.EJ2.HeatMap.ValueType.Category); }) .DataSource(GetSalesData()) .CellSettings(cellSettings => { cellSettings.ShowLabel(true); cellSettings.Format("0.0"); }) .Legend(legend => { legend.Visible(true); legend.Position(Syncfusion.EJ2.HeatMap.LegendPosition.Right); }) .Render() ``` ## Common Patterns ### Pattern 1: Basic Category HeatMap Display categorical data with category axes on both dimensions: ```csharp @Html.EJS().HeatMap("container") .XAxis(xaxis => { xaxis.Labels(new List<string> { "A", "B", "C" }); xaxis.ValueType(Syncfusion.EJ2.HeatMap.ValueType.Category); }) .YAxis(yaxis => { yaxis.Labels(new List<string> { "Q1", "Q2", "Q3", "Q4" }); yaxis.ValueType(Syncfusion.EJ2.HeatMap.ValueType.Category); }) .DataSource(Model.SalesData) .Render() ``` ### Pattern 2: JSON Table Binding Bind JSON data structured as table format: ```csharp .DataSource(new HeatMapData { IsJsonData = true, AdaptorType = Syncfusion.EJ2.HeatMap.AdaptorType.Table, Data = Model.JsonTableData }) ``` ### Pattern 3: Array Cell Binding Bind row/column/value triplets: ```csharp .DataSource(new HeatMapData { AdaptorType = Syncfusion.EJ2.HeatMap.AdaptorType.Cell, Data = Model.CellDataArray }) ``` ### Pattern 4: With Tooltips and Labels Complete visualization with all interactive features: ```csharp @Html.EJS().HeatMap("container") .DataSource(Model) .CellSettings(cell => cell.ShowLabel(true)) .Tooltip(tooltip => { tooltip.Visible(true); tooltip.Format("{value}"); }) .Legend(legend => legend.Visible(true)) .Render() ``` ## Key Properties | Property | Type | Purpose | Common Values | |----------|------|---------|----------------| | `DataSource` | Object | Data to visualize | Array, JSON object | | `ValueType` | ValueType | Axis data type | Category, Numeric, DateTime | | `CellSettings` | CellSettings | Cell appearance | ShowLabel, Format | | `Legend` | Legend | Legend configuration | Visible, Position, Type | | `Tooltip` | Tooltip | Tooltip display | Visible, Format, Template | | `Palette` | List<string> | Color palette | Predefined or custom colors | | `SelectionMode` | SelectionMode | Selection behavior | Cell, Series, None | | `RenderingMode` | RenderingMode | Rendering engine | SVG, Canvas, Auto | ## Common Use Cases **Sales Performance Dashboard**: Display sales by region and time period with gradient coloring to identify trends and outliers. **Correlation Matrix**: Visualize relationships between multiple variables using color intensity to represent correlation strength. **User Activity Heatmap**: Show user engagement patterns across time periods with interactive tooltips for detailed analysis. **Inventory Status Grid**: Monitor stock levels across products and warehouses with color-coded alerts for low inventory. **Temperature/Weather Visualization**: Display temperature variations across locations and time with gradient color schemes. **Website Traffic Analysis**: Show visitor patterns by page and hour with bubble HeatMap for three-variable analysis. **Student Performance Matrix**: Visualize grades across subjects and classes with selection for detailed analysis. HeatMap provides powerful two-dimensional data visualization capabilities for analysis, exploration, and presentation of complex datasets.
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