Joining Data in R using dplyr

Perform different join operations using the merge() function
Perform different join operations using dplyr join functions
Perform different join operations using the merge() function
Perform different join operations using dplyr join functions
You will need to join or merge two or more data sets at different points in your work as a data enthusiast. The dplyr package offers very sophisticated functions to help you achieve the join operation you desire. This project-based course, "Joining Data in R using dplyr" is for R users willing to advance their knowledge and skills. In this course, you will learn practical ways for data manipulation in R. We will talk about different join operations and spend a great deal of our time here joining the sales and customers data sets using the dplyr package. By the end of this 2-hour-long project, you will perform inner join, full (outer) join, right join, left join, cross join, semi join, and anti join using the merge() and dplyr functions. This project-based course is an intermediate-level course in R. Therefore, to get the most of this project, it is essential to have prior experience using R for basic analysis. I recommend that you complete the project titled: "Data Manipulation with dplyr in R" before you take this current project.
Data Management
Data Manipulation
Joins
R Programming
dplyr
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Getting Started
Create and Clean data sets
Inner Join - Part 1
Inner Join - Part 2
Inner Join - Part 3
Full (Outer) Join
Left Join
Optional Practice Task: Right Join
Optional Cummulative Task: Cross, Semi & Anti Join
Wrap up
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
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