Chapter 1: Introduction to Matplotlib
- Lesson 1: What is Matplotlib?
- Lesson 2: History and Importance of Matplotlib
- Lesson 3: Installing Matplotlib (Windows, macOS, Linux)
- Lesson 4: Importing and Using Matplotlib
- Lesson 5: Understanding Matplotlib’s Role in Data Visualization
Chapter 2: Basic Plotting with Matplotlib
- Lesson 1: Creating a Simple Line Plot
- Lesson 2: Plotting Multiple Lines in a Single Figure
- Lesson 3: Changing Line Styles, Colors, and Markers
- Lesson 4: Adding Titles, Labels, and Legends
- Lesson 5: Saving Figures in Different Formats
Chapter 3: Understanding Figure, Axes, and Subplots
- Lesson 1: Matplotlib’s Figure and Axes Structure
- Lesson 2: Creating Multiple Subplots
- Lesson 3: Adjusting Spacing Between Subplots
- Lesson 4: Sharing Axes Across Subplots
- Lesson 5: Controlling Figure Size and Aspect Ratio
Chapter 4: Working with Different Plot Types
- Lesson 1: Line Plots and Their Customization
- Lesson 2: Scatter Plots: Adding Points and Colors
- Lesson 3: Bar Charts: Vertical and Horizontal Bars
- Lesson 4: Histograms: Data Distribution Visualization
- Lesson 5: Pie Charts: Adding Labels and Formatting
Chapter 5: Customizing Plot Aesthetics
- Lesson 1: Changing Colors, Styles, and Themes
- Lesson 2: Adding Grid Lines and Annotations
- Lesson 3: Using Matplotlib’s Built-in Styles
- Lesson 4: Customizing Ticks and Labels
- Lesson 5: Adding Text to Plots
Chapter 6: Handling Axes and Scales
- Lesson 1: Setting Axis Limits and Scales
- Lesson 2: Logarithmic and Symmetrical Scale Adjustments
- Lesson 3: Formatting Dates on the X-Axis
- Lesson 4: Using Twin Axes for Multiple Scales
- Lesson 5: Rotating and Formatting Tick Labels
Chapter 7: Working with Images in Matplotlib
- Lesson 1: Displaying Images Using Matplotlib
- Lesson 2: Adding Images to Plots
- Lesson 3: Adjusting Image Transparency and Color Maps
- Lesson 4: Annotating Images with Text and Arrows
- Lesson 5: Blending Images with Graphical Elements
Chapter 8: Matplotlib and Pandas Integration
- Lesson 1: Plotting Data from Pandas DataFrames
- Lesson 2: Using Matplotlib with Pandas Time Series Data
- Lesson 3: Handling Missing Data in Visualizations
- Lesson 4: Customizing Pandas Plot Outputs with Matplotlib
- Lesson 5: Using Seaborn for Advanced Styling with Matplotlib
Chapter 9: Advanced Customization with Matplotlib
- Lesson 1: Customizing Legends and Annotations
- Lesson 2: Adding Custom Fonts and Typography
- Lesson 3: Using Custom Markers and Linestyles
- Lesson 4: Combining Different Plot Types in One Figure
- Lesson 5: Creating Thematic and Professional-Looking Plots
Chapter 10: Interactive Plots and Animations
- Lesson 1: Introduction to Matplotlib’s Interactive Mode
- Lesson 2: Using Widgets for User Interaction
- Lesson 3: Creating Simple Animations with FuncAnimation
- Lesson 4: Adding Interactive Buttons and Sliders
- Lesson 5: Exporting Animations to GIF or Video
Chapter 1: Deep Dive into Figures and Axes
- Lesson 1: Advanced Figure Structuring and Multi-Axes Handling
- Lesson 2: Using Multiple Figures in One Script
- Lesson 3: Creating Multi-Panel Layouts Programmatically
- Lesson 4: Sharing Axes Across Figures Dynamically
- Lesson 5: Fine-Tuning Subplot Layouts
Chapter 2: Advanced Line and Scatter Plots
- Lesson 1: Customizing Line Width, Styles, and Dash Patterns
- Lesson 2: Adding Confidence Intervals to Line Plots
- Lesson 3: Advanced Scatter Plot Customizations
- Lesson 4: Handling Large Datasets in Scatter Plots Efficiently
- Lesson 5: Creating Bubble Charts with Custom Sizes and Colors
Chapter 3: Complex Bar and Pie Charts
- Lesson 1: Grouped and Stacked Bar Charts
- Lesson 2: Creating Custom Pie Charts with Exploded Sections
- Lesson 3: Visualizing Data Hierarchies with Sunburst Charts
- Lesson 4: Using Hatching Patterns in Bar Charts
- Lesson 5: Animated Bar Chart Races
Chapter 4: 3D Plotting with Matplotlib
- Lesson 1: Creating Basic 3D Plots
- Lesson 2: Surface and Wireframe Plots
- Lesson 3: 3D Scatter Plots and Line Graphs
- Lesson 4: Contour Plots in 3D
- Lesson 5: Interactive Rotations and Viewing Angles
Chapter 5: Heatmaps and Contour Plots
- Lesson 1: Creating and Customizing Heatmaps
- Lesson 2: Visualizing Correlation Matrices with Heatmaps
- Lesson 3: Advanced Contour Plot Customizations
- Lesson 4: Using Image Data for Heatmaps
- Lesson 5: Interactive Heatmaps with Mouse Hover Effects
Chapter 6: Matplotlib and Seaborn for Statistical Visualization
- Lesson 1: Using Seaborn’s Enhanced Matplotlib Plots
- Lesson 2: Creating Violin and Box Plots
- Lesson 3: Customizing Swarm and Strip Plots
- Lesson 4: Generating Pair Plots and Heatmaps
- Lesson 5: Advanced Aesthetic Customizations
Chapter 7: Interactive Dashboards with Matplotlib
- Lesson 1: Embedding Matplotlib in Web Applications
- Lesson 2: Creating Dashboards with Tkinter and Matplotlib
- Lesson 3: Using Matplotlib with Flask and Django
- Lesson 4: Building Live Data Dashboards
- Lesson 5: Deploying Interactive Matplotlib Plots
Chapter 8: Matplotlib Performance Optimization
- Lesson 1: Optimizing Matplotlib Rendering Speed
- Lesson 2: Reducing Memory Usage in Large Plots
- Lesson 3: Profiling and Debugging Matplotlib Performance Issues
- Lesson 4: Using GPU Acceleration for Faster Rendering
- Lesson 5: When to Use Alternative Visualization Libraries
Chapter 9: Customizing Matplotlib with Object-Oriented API
- Lesson 1: Understanding the Object-Oriented Approach
- Lesson 2: Creating Custom Classes for Matplotlib Plots
- Lesson 3: Extending Matplotlib with Custom Artists
- Lesson 4: Creating Matplotlib Themes and Style Sheets
- Lesson 5: Building a Matplotlib Extension
Chapter 10: Matplotlib in Data Science and Machine Learning
- Lesson 1: Visualizing Regression Models with Matplotlib
- Lesson 2: Plotting Decision Boundaries for Classification
- Lesson 3: Creating Learning Curves and Loss Plots
- Lesson 4: Generating Feature Importance Charts
- Lesson 5: Interactive ML Model Evaluation with Matplotlib
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