Data Wrangling with dplyr in R

Raw data is rarely ready for analysis, often requiring hours of cleaning and restructuring before you can extract meaningful insights. This text-based course guides you through the essential techniques of data manipulation using dplyr, the premier data wrangling package for the R programming language. You will transition from struggling with messy spreadsheets to confidently reshaping, filtering, and summarizing complex datasets. By reading through clear, step-by-step explanations and analyzing structured code examples, you will build a solid foundation in modern data preparation workflows. What you will learn: - Understand foundational data structures in R, including data frames and tibbles. - Filter, sort, and select specific data subsets efficiently using core dplyr verbs. - Create and modify variables to calculate new metrics within your datasets. - Summarize complex data using group-by operations to extract key statistics. - Combine multiple data sources seamlessly using modern join operations. - Apply the native R pipe operator to write clean, readable, and maintainable code. The course begins with essential terminology and data concepts before progressing to hands-on manipulation techniques and advanced relational joins. You will learn through written explanations and practical code snippets designed to reinforce your understanding. This course is designed for beginners who are new to R or looking to transition from spreadsheet tools to code-based data preparation. No prior programming experience is required. Start reading today and unlock the power of efficient data manipulation with dplyr.