#Python #Plotly #Heatmap #DataVisualization #DataScience #Tutorial
Welcome to episode #15 of our Data Visualization series! In this tutorial, we’ll dive into creating interactive heatmaps with Plotly in Python. Heatmaps are an excellent way to visualize matrix-style data, correlations, and density patterns at a glance.
What you’ll learn in this video:
✅ Understanding Heatmaps: Learn when and why to use heatmaps for data analysis
✅ Preparing Your Data: Transform your dataset into the right format (pandas DataFrame or 2D array)
✅ Basic Heatmap Creation: Use plotly.express.imshow() to generate your first heatmap
✅ Customizing the Color Scale: Choose from built-in color palettes or define your own to highlight key patterns
✅ Annotations & Labels: Add text annotations, axis labels, and hover tooltips for clarity
✅ Advanced Techniques: Apply clustering, reorder rows/columns, and overlay masks to emphasize regions
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