Joining Data in R using dplyr
About this course
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.
56/100
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- What the provider tells you
- 32/45
- Who stands behind it
- 8/35
- How complete the listing is
- 16/20
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What you'll learn
- perform inner join using dplyr
- execute full (outer) join using dplyr
- conduct right join using dplyr
- execute left join using dplyr
- carry out cross join using dplyr
- perform semi join using dplyr
- execute anti join using dplyr
- merge datasets using the merge() function
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