From Beginner to Pro – a curated list of hands-on visualization challenges that will sharpen your Matplotlib skills 🚀
🔗 Resources
🏆 The Challenges
S.No | Category | Challenge |
---|---|---|
1 | Basic & Essential | Dynamic Scaling: Plot y = sin(x) from 0–2π, auto-rescale with new data. |
2 | Basic & Essential | Custom Style Sheet: Create .mplstyle file to set global defaults. |
3 | Basic & Essential | Data Transformation: Plot log(y) vs x but ticks in original values. |
4 | Customization & Polish | Annotated Events: Plot stock prices, annotate highest/lowest points. |
5 | Customization & Polish | Dual Axes: Temperature (°C) + Humidity (%) with shared time axis. |
6 | Customization & Polish | Custom Ticks: Show only quarterly months (Jan, Apr, Jul, Oct). |
7 | Customization & Polish | Gradient Color Line: Sine wave with color changing from blue → red. |
8 | Customization & Polish | Custom Legends: Legend with unique marker size, color, and style. |
9 | Subplots & Layouts | Complex Layout: 5 plots (2 top row, 3 bottom row) with unique titles. |
10 | Subplots & Layouts | Shared Axes Zoom: Zooming in one subplot updates another subplot. |
11 | Real-Time & Animation | Live Data Simulation: Random walk updating every 200ms. |
12 | Real-Time & Animation | Animated Transition: Animate smoothly from sin(x) → cos(x) . |
13 | Real-Time & Animation | Performance Challenge: Plot 1M points efficiently with zooming. |
14 | Advanced Visualization | Heatmap: 10×10 matrix with annotated cell values. |
15 | Advanced Visualization | 3D Plot: Parametric spiral (cos(t), sin(t), t ) with gradient colors. |
16 | Advanced Visualization | Custom Colormap: Red → Yellow → Green for a contour plot. |
17 | Interactivity & Widgets | Interactive Slider: Control sine wave frequency in real-time. |
18 | Interactivity & Widgets | Clickable Points: Scatter plot shows coordinates when clicked. |
19 | Integration & Export | High-Quality Export: Multi-plot figure → 300 DPI PDF with metadata. |
20 | Integration & Export | Embedding in GUI: Matplotlib plot inside Tkinter with refresh button. |
✅ How to Use This
- Start with basic questions (1–3) to strengthen fundamentals.
- Move to customization & layouts (4–10) for polished plots.
- Experiment with real-time & advanced visualization (11–16).
- Explore interactivity & integration (17–20) for practical applications.
🚀 Save this list, fork the repos, and try solving each question step by step.
By the end, you’ll have a portfolio-ready set of Matplotlib projects!
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