Python Book 5 - Python Visualization Mastery for Dummies: Matplotlib and Seaborn

Table of Contents

1. Introduction

1.1 What is Data Visualization?

1.2 Why Data Visualization Matters?

1.3 What are Matplotlib and Seaborn?

1.4 How to Install and Import Matplotlib and Seaborn?

1.5 How to Use This Book?

2. Basic Plotting with Matplotlib

2.1 The Anatomy of a Matplotlib Figure

2.2 How to Create and Customize Line Plots?

2.3 How to Create and Customize Scatter Plots?

2.4 How to Create and Customize Bar Plots?

2.5 How to Create and Customize Pie Charts?

2.6 How to Create and Customize Histograms?

2.7 How to Save and Show Your Plots?

3. Advanced Plotting with Matplotlib

3.1 How to Create and Customize Subplots?

3.2 How to Create and Customize Box Plots?

3.3 How to Create and Customize Violin Plots?

3.4 How to Create and Customize Heatmaps?

3.5 How to Create and Customize Contour Plots?

3.6 How to Create and Customize 3D Plots?

4. Basic Plotting with Seaborn

4.1 How to Load and Explore Data with Seaborn?

4.2 How to Create and Customize Distribution Plots?

4.3 How to Create and Customize Categorical Plots?

4.4 How to Create and Customize Regression Plots?

4.5 How to Create and Customize Pair Plots?

4.6 How to Create and Customize Joint Plots?

5. Advanced Plotting with Seaborn

5.1 How to Create and Customize Facet Grids?

5.2 How to Create and Customize Cluster Maps?

5.3 How to Create and Customize Swarm Plots?

5.4 How to Create and Customize Strip Plots?

5.5 How to Create and Customize Point Plots?

5.6 How to Create and Customize Rug Plots?

6. Tips and Tricks for Data Visualization

6.1 How to Choose the Right Plot for Your Data?

6.2 How to Use Color, Style, and Layout Effectively?

6.3 How to Add Annotations, Legends, and Titles to Your Plots? 6.4 How to Handle Missing Values and Outliers in Your Data? 6.5 How to Improve the Performance and Quality of Your Plots? 7. Conclusion

7.1 Summary of the Main Points

7.2 Further Resources and References

7.3 Feedback and Contact Information