Bivariate and Multivariate Data Analysis with Plotly

When working with real-world data, variables rarely exist in isolation. Understanding how features interact through bivariate and multivariate analysis is essential for uncovering hidden patterns and making data-driven decisions. This text-based course guides you from the fundamental principles of statistical relationships to writing clean, modern Python code using the Plotly library. You will start by learning how to analyze pairs of variables, exploring both continuous and categorical combinations. From there, you will expand your skills to handle complex, multi-dimensional datasets using contemporary visualization techniques. Along the way, you will practice writing modular Python code, utilizing modern dataframe library patterns, and structuring your analysis for maximum clarity. What you'll learn: - Understand the core mathematical and statistical concepts behind bivariate and multivariate relationships - Create interactive scatter plots, line charts, and bar charts using Plotly to analyze two variables - Visualize complex multi-dimensional data using heatmaps, pair plots, and 3D scatter plots - Handle combinations of categorical and continuous data using box plots and violin plots - Apply modern Python coding practices, including clean data-wrangling patterns, to prepare your datasets - Evaluate and choose the right visualization type for your specific data structure This course begins with essential terminology and foundational statistical concepts before moving into step-by-step code implementations and practical analysis scenarios. You will read clear explanations, study structured code examples, and test your knowledge with targeted review questions. This course is designed for beginners, data analysts, and aspiring data scientists who want to build a solid foundation in multi-variable analysis. No prior visualization experience is required, though a basic familiarity with Python is helpful. Start reading today to unlock the power of multi-variable data visualization.