Data Import Techniques in R: Excel, Databases, and Web Sources

Raw data is rarely clean or stored in one place, making data ingestion the first critical step of any analysis. If you want to work with real-world data, you must know how to pull it from spreadsheets, relational databases, and the web directly into R. This text-based course guides you through the foundational concepts of data import in R, equipping you to handle diverse file formats and connection protocols. You will transition from manual data entry to writing efficient, reproducible code that automates data ingestion. What you'll learn: - Understand core data import terminology, including connection strings, APIs, and tidy data principles. - Import Excel spreadsheets accurately by specifying sheets, skipping metadata rows, and defining column types. - Query and extract data from relational databases using modern database interface packages. - Fetch web data by parsing JSON payloads and interacting with basic REST APIs. - Handle common ingestion challenges such as missing values, encoding issues, and data type mismatches. - Test your knowledge through structured written scenarios and code-comprehension exercises. You will start with the absolute basics of file paths and working directories before advancing to database connections and web requests. Each concept is reinforced with clear code snippets and written comprehension checks to solidify your understanding. This course is designed for beginner R programmers, aspiring data analysts, and researchers who want to streamline their data collection workflows. No advanced programming or database experience is required. Start reading today to build a reliable foundation for your data analysis projects.