Correlation Heatmap & Matrix Generator
Upload or paste any structured dataset to automatically detect numeric variables, calculate Pearson, Spearman, or Kendall correlation matrices, and visualize associations with interactive heatmaps — 100% in-browser, completely private.
⚙️ Heatmap & Algorithm Settings
🔥 Correlation Matrix Heatmap
Load a dataset and click Generate Heatmap to visualize correlation matrix
📊 Variable Pair Relationship Register
| Variable A | Variable B | Coefficient (r) | Relationship Strength | Statistical Interpretation |
|---|---|---|---|---|
| No correlation pairs evaluated yet | ||||
What is a Correlation Heatmap?
A Correlation Heatmap is a two-dimensional graphical representation of a statistical correlation matrix. It uses a color gradient scale to visually communicate the direction and magnitude of relationships between pairs of numeric variables in a dataset.
Correlation values range from -1.0 to +1.0:
- +1.0 (Perfect Positive Correlation): As one variable increases, the other increases in exact proportion.
- 0.0 (No Linear Correlation): No statistical association exists between changes in the two variables.
- -1.0 (Perfect Negative Correlation): As one variable increases, the other decreases in exact inverse proportion.
By translating raw statistical tables into intuitive color grids, correlation heatmaps enable analysts, data scientists, and business executives to instantly discover hidden patterns, collinear features, and key performance drivers.
Pearson vs. Spearman vs. Kendall Correlation
Measures linear relationships between continuous, normally distributed numeric variables. Sensitive to extreme outliers.
Measures monotonic (always increasing or decreasing) relationships by ranking values. Ideal for non-linear data and ordinal variables.
Measures rank concordance across pairs of observations. Robust against small sample sizes and tied values.
Key Heatmap Generator Features
Designed for data analysts, financial modelers, researchers, and analytics engineers.
Auto Numeric Column Profiling
Automatically isolates numeric variables (Integers, Decimals, Currency, Percentages) while skipping non-numeric fields.
Triple Algorithm Engine
Switch instantly between Pearson linear correlation, Spearman rank correlation, and Kendall Tau concordance.
Customizable Color Palettes
Select from Cool-to-Warm (Blue-White-Red), Viridis, Red-Yellow-Green, or Monochrome gradients.
Interactive Tooltips & Explanations
Hover over any cell to view exact coefficient values, pair names, and natural language statistical interpretations.
Multi-Format Exports
Download PNG image graphics, vector SVG, CSV matrices, Excel spreadsheets (`.xlsx`), JSON, or HTML reports.
100% In-Browser Privacy
Zero server uploads. All calculations run strictly inside your web browser session for complete data safety.
Frequently Asked Questions
What is a Correlation Heatmap and how does it work?
A Correlation Heatmap displays statistical relationships between numeric variables using a color-coded grid. Coefficients range from -1.0 to +1.0, with colors highlighting strong positive or negative associations.
Is my dataset uploaded to any server?
No. All file reading, statistical matrix generation, heatmap rendering, and file downloads execute 100% locally in your browser.
Which correlation methods are supported?
Pearson (linear correlation), Spearman (rank correlation), and Kendall Tau (concordance rank agreement).
What export formats are available?
You can export high-res PNG images, vector SVG graphics, CSV matrices, Excel workbooks (.xlsx), JSON data, or standalone HTML reports.
Analyze Your Dataset Correlations Now
Upload your data file and generate interactive correlation heatmaps and matrix reports in seconds — 100% private.