Text Wrangling in R with stringr

Text data is everywhere, but it is rarely ready for analysis without significant cleaning and processing. This course teaches you how to confidently manipulate, extract, and clean textual information in R using the powerful stringr package. You will learn to transform raw, unstructured text into structured, analysis-ready formats. By working through practical, text-based lessons, you will transition from manual data cleaning to writing efficient, automated text-processing workflows. You will gain a deep understanding of pattern matching and how to handle common data-cleaning headaches like irregular spacing, mixed casing, and hidden characters. What you will learn: - Understand the core principles of text processing and string behavior in R - Clean and format messy text by managing whitespace, casing, and padding - Extract specific substrings and patterns from complex text datasets - Apply regular expressions (regex) within stringr functions for robust pattern matching - Detect, locate, and replace target text elements across large datasets - Combine stringr operations with modern tidyverse workflows for seamless data preparation This course begins with foundational concepts, establishing essential terminology and string mechanics before moving on to practical text-matching techniques. You will read structured explanations, study clear code examples, and practice your skills with targeted written exercises. This course is designed for beginners who have a basic familiarity with R and want to build essential data-cleaning skills. No prior experience with text mining or regular expressions is required. Start mastering text manipulation in R today and unlock the stories hidden in your unstructured data.