By Brad Boehmke 🚀
Welcome to Data Wrangling with R! This course provides an intensive, hands-on introduction to Data Wrangling with the R programming language. You will learn the fundamental skills required to acquire, munge, transform, manipulate, and visualize data in a computing environment that fosters reproducibility.
Upon successfully completing this course, you will be able to:
- Perform your data analysis in a literate programming environment
- Manage different types of data
- Manage different data structures
- Import and export data
- Index, subset, reshape and transform your data
- Compute descriptive statistics
- Visualize data
- Make your code efficient by using control statements & iteration
- Write your own functions
- Train and evaluate predictive models
...all with R!
| Module | Description |
|---|---|
| 1 | Introduction |
| R fundamentals & the Rstudio IDE | |
| Deeper understanding of vectors | |
| 2 | Reproducible Documents and Importing Data |
| Managing your workflow and reproducibility | |
| Data structures & importing data | |
| 3 | Tidy Data and Data Manipulation |
| Data manipulation & summarization | |
| Tidy data | |
| 4 | Relational Data and More Tidyverse Packages |
| Relational data | |
| Leveraging the Tidyverse to text & date-time data | |
| 5 | Data Visualization & Exploration |
| Data visualization | |
| Exploratory data analysis | |
| 6 | Creating Efficient Code in R |
| Control statements & iteration | |
| Writing functions | |
| 7 | Introduction to Applied Modeling |
| Introduction to tidymodels | |
| Feature engineering & model evaluation/selection |
The primary course material is provided via this Bookdown resource 📕.