Descriptive Statistics with Python: Mean, Median, and Mode

Understanding how to summarize and interpret data is the foundation of data analysis and programming. This text-based guide teaches you how to compute and evaluate essential measures of central tendency, including the mean, median, and mode, directly in Python. Through clear explanations and practical code examples, you will explore how datasets behave, how to detect skewness, and how to select the right statistical metrics for different data types. You will work with Python's built-in statistics module as well as foundational data manipulation libraries like pandas, learning clean, modern coding habits along the way. What you'll learn: - Understand core statistical concepts and foundational terminology used in descriptive analytics - Calculate mean, median, and mode using both pure Python logic and standard libraries - Analyze real-world data distributions and identify when median is preferable to mean due to outliers - Apply modern data handling workflows using pandas for efficient data summarization - Practice handling multimodal datasets, categorical data, and missing values effectively - Write clean, readable statistical analysis code using modern Python conventions and type annotations The course begins with fundamental terminology and definitions before moving into hands-on code walkthroughs and structured written exercises. It is designed for beginners with basic Python familiarity who want a solid grounding in practical statistics without complex mathematical prerequisites. Start reading today to build confident data analysis skills in Python.