Interactive Data Visualization in Python with Plotly Express

Raw data is only as valuable as the stories you can tell with it. If you want to transform complex public health and global datasets into striking, interactive visual narratives without writing hundreds of lines of code, mastering modern Python visualization libraries is the key. This course guides you from Python data analysis basics to building interactive charts, geospatial maps, and temporal animations. You will learn how to clean messy real-world datasets, structure your data pipelines, and use Plotly Express to generate publication-ready visualizations with minimal, clean code. What you'll learn: - Understand the foundational concepts of data visualization and structured data analysis in Python - Clean and prepare real-world datasets using modern pandas techniques for accurate visualization - Build interactive bar charts, scatter plots, and bubble charts to compare global metrics - Create dynamic choropleth maps and animated timelines to track trends over time - Apply clean code principles and modern data workflows to ensure reproducible visual analyses - Design clear, clutter-free layouts that effectively communicate key insights to any audience You will start by mastering foundational data science terminology and setting up your data structures. As you progress through the written explanations and code exercises, you will clean raw datasets and construct a series of increasingly sophisticated interactive visualizations. This course is designed for beginners, aspiring data analysts, and researchers who have a basic familiarity with Python and want to build practical data visualization skills. No advanced programming or statistical background is required. Start reading today and learn how to bring your data to life through interactive visual storytelling.