Скачать или смотреть How to Remove Duplicate Rows in R when Only One Column Differs

Learn how to effectively remove duplicate rows in R data frames where only one column differs, using either base R or dplyr for simplicity and efficiency.
---
This video is based on the question https://stackoverflow.com/q/74719949/ asked by the user 'ispeakcat' ( https://stackoverflow.com/u/17053500/ ) and on the answer https://stackoverflow.com/a/74719990/ provided by the user 'akrun' ( https://stackoverflow.com/u/3732271/ ) 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: Remove all but one duplicated row, when one column is different for all rows in R

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.
---
How to Remove Duplicate Rows in R when Only One Column Differs

If you work with data sets in R, you might often encounter issues related to duplicate rows, especially when the duplicated rows are almost identical except for one column. This can make it challenging to utilize functions like duplicated() or unique(). In this guide, we'll explore how to effectively remove these duplicates while preserving one row from each set of duplicates.

The Problem: Managing Duplicate Rows

Imagine you have a dataset similar to the following table, where the gene_ID column has multiple entries that only differ at the end:

gene_IDGene_IdentifierCategoryLengthWdfy1_chr1_79702262_79776143(-)_transcript=ENSMUST00000113515.7Wdfy1Spliced4551Wdfy1_chr1_79702262_79776143(-)_transcript=ENSMUST00000113514.7Wdfy1Spliced4551Wdfy1_chr1_79702262_79776143(-)_transcript=ENSMUST00000113513.7Wdfy1Spliced4551Wdfy1_chr1_79702262_79776143(-)_transcript=ENSMUST00000113512.7Wdfy1Spliced4551In this example, you may want to keep only the first entry for each group of duplicates, which can be quite tricky with standard functions.

The Solution: Techniques to Remove Duplicates

Let's break down two effective methods to tackle this problem: using base R and the dplyr package.

Method 1: Using Base R

In base R, you can use the duplicated() function in combination with a logical not operator (!). Here's how to do this:

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

Output:

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

Method 2: Using dplyr

The dplyr package is a popular choice for data manipulation in R. You can filter out duplicates based on all columns except the unique identifier with the following code:

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

Output:

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

Conclusion

Both methods presented above — using base R and dplyr — effectively remove duplicate rows when one column differs. Depending on your comfort level with packages in R, you can select either method that best suits your workflow.

When dealing with large datasets, cleaning up duplicates is crucial for maintaining data integrity and being able to perform accurate analyses. Now you're equipped with the right tools to handle these situations efficiently!