How to Perform a Cluster Analysis in R
March 22, 2024
Article
Recommended experience
Intermediate level
Prior experience using R for basic analysis
Recommended experience
Intermediate level
Prior experience using R for basic analysis
Perform different join operations using the merge() function
Perform different join operations using dplyr join functions
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Only available on desktop
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.
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Getting Started (9 min)
Create and Clean data sets (5 min)
Inner Join - Part 1 (9 min)
Inner Join - Part 2 (8 min)
Inner Join - Part 3 (10 min)
Full (Outer) Join (6 min)
Left Join (7 min)
Optional Practice Task: Right Join (4 min)
Optional Cummulative Task: Cross, Semi & Anti Join (5 min)
Wrap up (4 min)
Prior experience using R for basic analysis
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Available only on desktop
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