Data Visualization with Matplotlib for Informatics Practices

Visualizing data is a core skill in modern computer science and a key component of the Informatics Practices syllabus. This text-based course guides you from absolute beginner concepts to creating, customizing, and analyzing professional-grade plots using Python's Matplotlib library. You will learn to transform raw numbers into clear, readable charts using clean, modern Python code. Understand the core structure of a plot, starting with basic figures and axes, before moving on to practical implementations. Build line charts, bar graphs, histograms, and scatter plots with step-by-step written guidance. Customize chart elements including titles, labels, legends, colors, styles, and grid lines. Organize multiple plots side-by-side using modern layout techniques and subplots. Apply best practices for data preparation, utilizing basic pandas integration for seamless plotting. Practice your skills with written exercises and code snippets designed to align with foundational academic standards. You will start with basic plotting syntax and gradually build up to advanced customization techniques, exploring real-world datasets through clear written explanations. This course is perfect for students preparing for school exams, beginners in Python, and anyone looking for a clear, text-based introduction to data visualization. No prior plotting experience is required. Start reading today to turn raw data into clear, impactful visual stories.