Welcome to Data Visualization with Python

Data visualization is one of the most powerful skills in data science and analytics. The ability to transform raw numbers into meaningful visual stories can reveal patterns, communicate insights, and drive better decisions.

What You'll Learn

In this comprehensive course, you'll master two of Python's most popular visualization libraries:

Matplotlib - The foundational plotting library that gives you complete control over every aspect of your visualizations. You'll learn to create line plots, scatter plots, bar charts, histograms, pie charts, and complex multi-panel figures.

Seaborn - A statistical visualization library built on top of Matplotlib that makes creating beautiful, informative charts effortless. You'll use Seaborn for box plots, violin plots, heatmaps, regression plots, and more.

Course Structure

This course is organized into 12 modules:

1. Introduction to Data Visualization - Why visualization matters and choosing the right chart
2. Matplotlib Basics - Figure, axes, and your first plots
3. Line and Scatter Plots - Visualizing trends and relationships
4. Bar Charts and Histograms - Comparing categories and distributions
5. Pie Charts and Subplots - Part-to-whole relationships and multi-panel layouts
6. Customizing Plots - Colors, labels, legends, and annotations
7. Seaborn Introduction - High-level statistical visualization
8. Statistical Visualizations - Box plots, violin plots, and distributions
9. Heatmaps and Correlation - Visualizing matrices and relationships
10. Time Series Visualization - Working with temporal data
11. Interactive Plots Preview - Introduction to Plotly
12. Visualization Best Practices - Design principles and common mistakes

Prerequisites

This course assumes you have:

• Basic Python programming knowledge (variables, functions, loops)
• Familiarity with NumPy and Pandas fundamentals
• Completed the "Interactive Python Practice" course or equivalent experience

If you're new to Python, we recommend starting with our Python Basics course first.

Interactive Learning

Throughout this course, you'll practice creating visualizations directly in your browser using our Python playground. Each lesson includes:

• Live code examples you can run and modify
• Guided exercises to reinforce concepts
• Quizzes to test your understanding

The best way to learn visualization is by doing. Don't just read the code - run it, experiment with it, and try your own variations.

Let's Get Started

Data visualization bridges the gap between data analysis and communication. Whether you're exploring data for your own understanding or presenting findings to stakeholders, the skills you'll learn here will serve you throughout your data career.

Click "Next" to begin your journey into the world of data visualization with Python.