String Manipulation in R for Data Analysis

Text data is everywhere, from customer feedback and social media posts to chaotic spreadsheet exports. To extract meaningful insights, every data analyst must know how to clean, parse, and restructure character strings efficiently. This text-based course provides a structured path to mastering string manipulation in R, ensuring you can confidently handle any unstructured text data you encounter. You will start by learning core concepts, basic string anatomy, and foundational R functions for text. From there, you will progress to advanced pattern matching and modern practices, learning how to write clean, maintainable code for data preparation. What you'll learn: - Understand the fundamentals of character vectors and string data types in R - Perform essential operations including counting characters, changing case, and concatenating text - Detect, extract, and replace specific patterns within messy datasets using robust string functions - Split complex strings into clean, structured tabular formats for easier analysis - Apply modern regular expressions to match precise text patterns with confidence - Clean and preprocess raw text data to prepare it for downstream statistical modeling This course guides you step-by-step from foundational terminology to practical text-cleaning workflows. You will read clear explanations, study structured code examples, and complete written exercises designed to build real-world data-wrangling skills. This course is designed for beginners, data analysts, and researchers who want to work with text in R. No prior experience with string manipulation or regular expressions is required. Start reading today to transform your raw text data into structured, actionable insights.