 This tip is tidying your variable names is a breeze with the clean names function from the janitor package. In this video series about the R language, I'm showing you how to iterate with custom functions. Along the way, I'm highlighting tips and tricks for tidying data. As always, see the video description below for a link to the code. The first two videos in this series demonstrated how to iterate over a vector and introduce the per map function for iteration. It's just a brief introduction and we're going to dive deeper into the functions and iteration as the series progresses. In the last video in this series, we'll put it all together. I'll demonstrate using data wrangling tips with iteration and custom functions. In between, such as this video, I want to share some data wrangling tips and tricks. This tip is tidying your variable names is a breeze with the clean names function from the janitor package. So choosing the right name for something can be challenging. What works best in the tidyverse? According to the tidyverse style guide, variable names and function names should use only lowercase letters, numbers, and underscores. Let's look at an example. In this code at line 106, you'll see that we're using the readTSV function that we used before. If we view that data frame, you'll see that that's an example of the camel case. You know that because it's using uppercase letters. But if we run that same data frame through the janitor cleanNames function, when we execute that bit of code, it'll by itself update the variable names, which makes some tidy names so that you then have snake case, right? Spaces are separated by underscores, and it's all lowercase. In practice, I might use the cleanNames function on any data that I ingest and then save a copy of my wrangled data after I've cleaned it all up. In closing, check out the janitor package for its many useful data tidying functions.