Data Analysis with R: Import and Transform Data

To make data-driven decisions, you first need to know how to get your data into R and shape it for analysis. Many beginners struggle with messy datasets and complex syntax, but mastering the fundamentals of data preparation saves hours of frustration. This text-only course guides you through the essentials of R programming, focusing on how to import, clean, and restructure your data. By reading clear explanations and practicing with real-world code snippets, you will build a solid foundation in data manipulation using modern tools. What you'll learn: * Understand core R syntax, data types, and foundational programming concepts * Import data seamlessly from CSV files, Excel spreadsheets, and web sources * Filter, sort, and select data efficiently using modern tidyverse packages * Clean messy datasets by handling missing values and restructuring columns * Apply the modern native pipe operator to write readable and maintainable code * Summarize and group data to extract key insights. The course begins with essential R terminology and basic programming structures before moving into hands-on data import techniques. From there, you will explore step-by-step methods to filter, mutate, and reshape your datasets using clean, modern practices. This course is designed for absolute beginners, aspiring data analysts, and researchers with no prior programming experience. Start your journey into data analysis and learn how to transform raw data into valuable insights.