Скачать или смотреть Vertically Join Two Dataframes by Rows with dplyr in R

Discover how to vertically join two dataframes by common values in R using `dplyr` for seamless data integration.
---
This video is based on the question https://stackoverflow.com/q/68101607/ asked by the user 'cholo.trem' ( https://stackoverflow.com/u/12732398/ ) and on the answer https://stackoverflow.com/a/68101734/ provided by the user 'Ronak Shah' ( https://stackoverflow.com/u/3962914/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Vertically join two dataframes by rows with common values

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Vertically Join Two Dataframes by Rows with dplyr in R

When working with dataframes in R, it's common to encounter scenarios where you need to combine datasets based on shared values. This is particularly true when you want to vertically align two dataframes by rows, leveraging specific common values. In this guide, we'll go through a practical example where we have two dataframes and we aim to join them according to the values in their first rows.

Understanding the Problem

Let's start by looking at our two dataframes, dat1 and dat2:

[[See Video to Reveal this Text or Code Snippet]]

Structure of the Dataframes

dat1 consists of five columns with values:

Rows: A1, A2, A3, A4, A5 and B, B, B, B, B.

dat2 has three columns with common values:

Rows: A1, A3, A5 and C.

Objective

We want to join these two dataframes based on the common values (A1, A3, and A5), resulting in a new dataframe that looks like this:

[[See Video to Reveal this Text or Code Snippet]]

Solution: How to Join Dataframes Using dplyr

We'll achieve this using the powerful dplyr library in R. This library provides a suite of functions designed to simplify data manipulation.

Step-by-step Guide

Load the dplyr Library: Ensure you have dplyr installed and loaded into your R session.

[[See Video to Reveal this Text or Code Snippet]]

Transpose and Join: We'll transpose the dataframes, join them, and transpose back. Here’s the code to do that:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Code

Transposing the Dataframe: The use of t() changes rows to columns, allowing us to line up the common identifiers.

left_join: This function combines the two dataframes based on a shared column ('V1'), enabling us to merge rows accordingly.

Re-transposing: After the join, we transpose the dataframe back to its original orientation for a clearer presentation.

as.data.frame(row.names = FALSE): This ensures that row names are not retained, making the final output cleaner.

Result

The final output looks like this:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Combining dataframes in R based on common values is a frequent requirement in data analysis. Through this guide, we've learned how to vertically join two dataframes using the dplyr package. This method not only provides an effective way to merge datasets but also keeps our data organized and easy to manipulate.

Whether you're analyzing corporate data or working on a personal project, mastering these techniques in R will enhance your data processing skills. Happy coding!