Data & AI with Mukundan
Data & AI with Mukundan
9 Hidden Data Visualization Tricks to Transform Your Visuals using Plotly library in Python
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9 Hidden Data Visualization Tricks to Transform Your Visuals using Plotly library in Python

Key Takeaways:

1. Why Plotly is a Game-Changer

  • Unlike Matplotlib or Seaborn, Plotly offers interactive and dynamic visualizations that are perfect for storytelling.

  • Unlock powerful features that go beyond basic bar charts or scatter plots.

2. 9 Hidden Plotly Tricks:

  • Custom Pairwise Correlation Matrix: Add annotations and custom color scales for deeper insights.

  • Dynamic Data Highlighting: Like Excel, conditional formatting but on steroids.

  • Density Contours: Visualize class distribution and clustering with ease.

  • Faceted Histograms: Compare subgroups in a single view.

  • Threshold Lines: Emphasize decision boundaries effectively.

  • Custom Annotations: Turn visuals into storytelling tools.

  • 3D Scatter Plots: Explore invisible relationships in 3D.

  • Animated Visualizations: Reveal dynamic patterns over time.

  • Interactive Tooltips: Make charts engaging and informative.

3. Real-world Applications

  • Business intelligence, scientific research, and education examples.

  • Techniques aren’t just about aesthetics—they’re about actionable insights.

4. Bonus Resources

Complete code examples are in the links below: