Welcome aboard our enlightening journey through merging data frames using dplyr in R! In the real world, data are rarely consolidated in one location. Often, they're spread across multiple sources, waiting to be collected, organized, and analyzed. Whether we're dealing with sales data from various regions, healthcare records from a multitude of facilities, or educational scores from several institutions, joining diverse chunks of data is a routine task in any data-driven field.

In this lesson, we will learn how to use this powerful tool to combine data frames, and discover various merge operations and their usage in different scenarios. With practical examples to guide you, get ready to master the art of merging data frames with R dplyr!

We utilize the join() functions from dplyr to combine data frames. Here's a general example:

In these examples, the abstract variables df1 and df2 are merged based on a shared or common column.

We shall look at specific examples and unpack the four types of merges: inner join, outer join, left join, and right join.

For this lesson, we will use the following dataset, stored in two separate data frames: