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Joining Data with dplyr
4.8(1,257)82k studentsBEGINNEREnglish
Korshub's take
Combine Multi-Table Datasets in R
In real-world data science, valuable information is rarely stored in a single table. This beginner course provides hands-on practice combining multi-table datasets in R using the powerful dplyr package.
Core Learning Takeaways
- Mutating Joins: Practice four essential mutating joins—inner join, left join, right join, and full join—to enrich your primary dataset.
- Filtering Joins: Master semi joins and anti joins to isolate or exclude specific records across relational tables.
- Hands-On Datasets: Analyze detailed LEGO dataset structures from Rebrickable and examine real Stack Overflow questions tagged with R.
Who Will Benefit
R programmers looking to level up their data manipulation fluency and confidently handle complex, split-table data workflows.
About this course
Often in data science, you'll encounter fascinating data that is spread across multiple tables. This course will teach you the skills you'll need to join multiple tables together to analyze them in combination. You'll practice your skills using a fun dataset about LEGOs from the Rebrickable website. The dataset contains information about the sets, parts, themes, and colors of LEGOs, but is spread across many tables. You'll work with the data throughout the course as you learn a total of six different joins! You'll learn four mutating joins: inner join, left join, right join, and full join, and two filtering joins: semi join and anti join. In the final chapter, you'll apply your new skills to Stack Overflow data, containing each of the almost 300,000 Stack Oveflow questions that are tagged with R, including information about their answers, the date they were asked, and their score. Get ready to take your dplyr skills to the next level!
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