![]() The only difference is that we did not reference the dataframe, df, inside of the rename() function. The first few lines of this example are very similar to the previous example where we renamed both variables in the dataframe. Mutate(exponential_var = exp(numeric_var)) I won't explain all of the details of how it works, but I want to show you a simple example of how you can use rename() with the pipe operator to perform more complex data manipulation. It's a game changer in terms of data science workflow. If you're new to the Tidyverse and you don't know about the pipe operator, I highly recommend that you learn it and start to use it. To show you how rename() works, let’s create a simple dummy dataset with slightly messed up variable names. Having said all of that, let’s talk about rename(). Whether you’re adding a new column to a dataframe, creating substrings, filtering your dataframe, or performing some other critical data manipulation, dplyr and the Tidyverse almost always have the best solution now. Like I just mentioned, R almost always has several different ways to do things, but dplyr and the Tidyverse have provided tools that are easy to use, easy to read, and easy to remember. In my opinion, the best way to rename variables in R is by using the rename() function from dplyr.Īs I’ve written about several times, dplyr and several other packages from R’s Tidyverse (like tidyr and stringr), have the best tools for core data manipulation tasks. The major challenge is finding the best way … the way that will be syntactically easy to write, easy to read, and easy to remember. So when you are trying to learn how to do something simple like rename a variable in R, the major challenge isn’t finding a way to do it … it’s easy to find a variety of ways. The syntax for accomplishing these tasks has been simplified. And it’s not just that they are easier to do, but they are easier to remember. Performing simple tasks like renaming variables or adding columns to a dataframe have become dramatically easier in the last few years. In particular, tools from dplyr have made simple data manipulation tasks much easier. Stack Overflow has suggestions dating to 2011 or earlier that explain how to rename variables, but since then, new techniques have been developed. The problem is that many of those suggestions are several years out of date. In particular, if you search how to do this on Stack Overflow, you’ll typically find 3 to 5 different suggestions for how to do this. If you just do a quick google search, you’ll find several different ways to rename the columns of an R dataframe. ![]() Moreover, R has several different ways to rename variables in a dataframe.īecause R is open source, and because the language is relatively old, several different ways to rename variables have come about. R has several different ways to rename variables in a dataframe And many methods of doing things are a little syntactically awkward. Syntactically, many tools and functions from “early R” are poorly named. With due respect to the people who initially created the language and developed it in its early stages, the structure of the initial parts of the language has some quirks. If you’re relatively new to R, you need to understand that R is sort of an old programming language. ![]() The old ways to rename variables in R are a little awkward The major challenge with renaming columns in R is that there is several different ways to do it. The major challenge with renaming columns in R Towards the end of the post, I’ll show you a few other ways to rename variables in R … although I strongly prefer only one of these methods. Then, I’ll show you the “best” way to rename variables in R. So very briefly, I’ll explain why renaming variables in a dataframe can be a little confusing in R. This is pretty straightforward if you know how to do it properly, but there are also some little challenges in renaming variables. In this blog post, I’ll show you how to rename columns in R.
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