Changing Row Names in R Data.Frame

In this article, we will explore how to rename row names in an R data.frame. This can be useful when working with datasets that have been imported or generated using different methods, and the original row labels are no longer meaningful.

Introduction

R provides several options for renaming row names in a data.frame, each with its own strengths and weaknesses. In this article, we will discuss three approaches: using the factor function with labeled levels, the recode function from the dplyr package, and creating a join with a key-value dataset.

Using the Factor Function with Labeled Levels

The factor function is one of the most straightforward ways to rename row names in R. To use this method, you will need to specify the original labels as well as the new labels.

library(tidyverse)

# Create a data.frame with row names that need to be renamed
DF1 <- data.frame(Station = rep("DA056", 3), Level = 100:102)
DF2 <- data.frame(Station = rep("AB786", 3), Level = 201:203)
DF <- bind_rows(DF1, DF2)

# Rename the row names using factor with labeled levels
DF <- DF %>% 
    mutate(Station = factor(Station, levels = c("DA056", "AB786"), 
                          labels = c("Happy", "Sad")))

In this example, we create a data.frame DF1 and DF2, which are then bound together using the bind_rows function to create the final dataset DF. We then use the factor function to rename the row names. The first argument specifies the original labels (levels = c("DA056", "AB786")), while the second argument specifies the new labels (labels = c("Happy", "Sad")).

Note that when using the factor function, R will automatically create a unique levels for each label.

Using the Recode Function

The recode function is another option for renaming row names in R. This method can be useful when you need to perform other data transformations at the same time.

# Rename the row names using recode
DF <- DF %>% 
    mutate(Station = recode(Station, DA056 = 'Happy', AB786 = 'Sad'))

In this example, we use the recode function to rename the row names. We specify a mapping of old labels to new labels (DA056 -> Happy, AB786 -> Sad).

Using a Join with a Key-Value Dataset

When you have many values that need to be renamed, using a join with a key-value dataset can be the most efficient method.

# Create a key-value dataset
keyval <- data.frame(Station = c("DA056", "AB786"),
                    val = c("Happy", "Sad"), stringsAsFactors = FALSE)

# Rename the row names using a left join with key-value dataset
DF <- DF %>% 
    left_join(keyval) %>% 
    mutate(Station = coalesce(val, Station))

In this example, we create a key-value dataset keyval and then use it to rename the row names. We perform a left join on the original data frame DF, and then use the coalesce function to select either the old label (Station) or the new label (val).

Using Base R

Finally, we can also use the base R functions to rename row names in a data.frame.

# Rename the row names using factor with labeled levels (alternative)
DF$Station <- with(DF, 
                 factor(Station, levels = c("DA056", "AB786"), 
                        labels = c("Happy", "Sad")))

In this example, we use the with function to create a temporary environment for the row names transformation.

Conclusion

Renaming row names in R can be a necessary step when working with datasets that have been imported or generated using different methods. The methods discussed in this article provide different approaches to renaming row names, each with its own strengths and weaknesses. By choosing the right method for your specific use case, you can efficiently rename row names in your data.frame.

Last modified on 2023-09-07