Data Manipulation with R: Clean and Transform Data with the Tidyverse

Raw data is rarely ready for analysis. To extract meaningful insights, you must first master the art of cleaning, reshaping, and organizing your datasets. This text-based course guides you through the essential workflows of data manipulation in R using the powerful tidyverse ecosystem. You will transform raw, messy data into structured, analysis-ready formats. Through structured written lessons and practical code examples, you will learn how to write clean, readable, and highly efficient R code. You will start with core data concepts, learn how to filter and sort information, and progress to advanced reshaping and table-joining techniques. What you'll learn: Understand core tidyverse principles and modern R data structures; Select, filter, and arrange data tables using intuitive verb-based functions; Reshape complex datasets between wide and long formats for easier analysis; Combine and join multiple tables to answer complex business questions; Handle missing values and clean inconsistent records systematically; Apply modern R coding practices, including pipe operators, for clean and readable workflows. This course begins with foundational definitions and key data manipulation concepts before moving step-by-step into practical data-wrangling scenarios. It is designed specifically for beginners who have a basic familiarity with R and want to build a strong foundation in data science. Start mastering data manipulation today and write cleaner, more efficient R code.