Reading and Writing CSV Files in Python

Working with CSV files is a fundamental skill for data analysis, automation, and software development. This text-based course guides you through handling structured data efficiently, from simple spreadsheets to complex, real-world datasets. You will transition from basic file operations to advanced data manipulation using modern Python libraries. By reading through clear explanations and practical code examples, you will learn how to parse non-standard files, clean messy data, and write robust scripts to automate your data pipelines. What you'll learn: - Understand the core structure of CSV files and basic file I/O principles in Python - Parse standard and non-standard CSV files using the built-in csv module - Handle complex data anomalies such as custom delimiters, missing headers, and nested quotes - Import and export large datasets efficiently using the modern pandas library - Apply data cleaning techniques to prepare raw CSV files for analysis - Implement type hints and error handling to write reliable, maintainable data scripts The course starts with essential file-handling terminology and foundational Python concepts before moving into practical reading and writing exercises. You will progress from basic built-in modules to high-performance data manipulation tools. This course is designed for beginners, aspiring data analysts, and developers looking to master data import and export workflows. No prior data science experience is required, though a basic familiarity with Python is helpful. Start reading today to master the essentials of data manipulation with Python.