45-Day Roadmap to Python Visualization: Line, Bar, Heatmaps & Interactive Plots

Learn Python data visualization step-by-step in just 45 days! This beginner-friendly plotting course covers Matplotlib, Seaborn, and Plotly with 3 lessons per week, real projects, and practical examples. Perfect for students, developers, and data analysts.

📅 Week 1: Plotting Foundations

• Day 1: Introduction to matplotlib, pyplot, and plot lifecycle
• Day 2: Figure, axes, subplots – procedural vs OOP style
• Day 3: Plot customization – styles, grid, ticks, labels

📅 Week 2: Saving & Line Plots

• Day 4: Saving/exporting plots using savefig()
• Day 5: Basic line plots with multiple lines and legends
• Day 6: Line plots with seaborn and plotly

📅 Week 3: Bar Charts

• Day 7: Vertical and horizontal bar charts
• Day 8: Grouped and stacked bar charts
• Day 9: Bar plots using seaborn and plotly

📅 Week 4: Pie & Donut Charts

• Day 10: Basic pie charts – labels, percentages, angles
• Day 11: Donut charts and exploded views
• Day 12: Interactive pie charts using plotly

📅 Week 5: 🎯 Mini Project 1 – Market Share/Budget Visualization

• Day 13: Project planning: Market share or budget visualization
• Day 14: Implement and refine project (bar + pie combo)
• Day 15: Project review and feedback

📅 Week 6: Histograms

• Day 16: Basics of histograms – bins, density, color
• Day 17: Multiple histograms + customization
• Day 18: Histograms using seaborn.histplot()

📅 Week 7: Box & Violin Plots

• Day 19: Boxplot using matplotlib
• Day 20: Boxplot + Violin Plot with seaborn
• Day 21: Interactive boxplot with plotly

📅 Week 8: 🎯 Mini Project 2 – Performance Comparison

• Day 22: Project setup – Compare exam or income data
• Day 23: Implement box/violin + histogram combo
• Day 24: Finalize & review

📅 Week 9: Scatter Plots

• Day 25: Basic scatter plot with annotations
• Day 26: Colored scatter, trendlines, alpha
• Day 27: Scatter using seaborn and plotly

📅 Week 10: Heatmaps

• Day 28: Heatmap basics using seaborn.heatmap()
• Day 29: Correlation matrix heatmaps
• Day 30: Annotated heatmaps with color bar

📅 Week 11: Subplots

• Day 31: plt.subplot() and plt.subplots() usage
• Day 32: Grid layouts – 2×2, 3×1, shared axes
• Day 33: Mixed plots in one figure

📅 Week 12: 🎯 Mini Dashboard Project

• Day 34: Plan: dashboard with 3–4 subplots
• Day 35: Build and style dashboard
• Day 36: Finalize, share or export

📅 Week 13: Advanced Visualizations

• Day 37: Taylor diagrams and use cases
• Day 38: Radar/spider plots
• Day 39: 3D plots using Axes3D

📅 Week 14: Interactivity & Animation

• Day 40: Plotly animations – bar, scatter
• Day 41: Interactive dashboards using plotly.express
• Day 42: Mini project: live data or interactive exploration

📅 Week 15: Final Project – Visual Storytelling

• Day 43: Capstone: Choose dataset + plan
• Day 44: Build complete multi-plot story
• Day 45: Polish and present final project (or upload to GitHub)