You've been using the pipe for a while now, so you already understand the basics. Pipes transform the way you invoke deeply nested functions. Using a pipe doesn't affect what the code does; behind the scenes it is run in (almost) the exact same way. What the pipe does is change how _you_ write, and read, code. The point of this chapter is to explore the pipe in more detail. You'll learn the alternatives to pipe replaces, and their pro and cons. Importantly, you'll also learn the cases where you should avoid the pipe.
The pipe, `%>%`, comes from the __magrittr__ package by Stefan Milton Bache. Packages in the tidyverse load `%>%` for you automatically, so you don't usually explicitly load magrittr. Here, however, we're focussing on piping, and we aren't loading any other packages, so we'll need to load it explicitly. At the end of the chapter, we'll explore some other tool also provided by magrittr.
The point of the pipe is to help you write code in a way that easier to read and understand. To see why the pipe is so useful, we're going to explore a number of ways of writing the same code.
Let's use code to tell a story about a little bunny named Foo Foo:
And we'll use a function for each key verb: `hop()`, `scoop()`, and `bop()`. Using this object and these verbs, there are (at least) four ways we could retell the story in code:
We'll work through each approach, showing you the code and talking about the advantages and disadvantages. These are made up functions; please don't expect this code to actually work!
The main downside of this form is that it forces you to name each intermediate element. If there are natural names, this is a good idea, and you should use it. But many times, like this in this example, there aren't natural names, and you add numeric suffixes just to make the names unique. That leads to two problems: the code is cluttered with unimportant names, and you have to carefully increment the suffix on each line. Whenever I write code like this, I invariably use the wrong number on one line and then spend 10 minutes scratching my head and trying to figure out what went wrong with my code.
You may also worry that this form creates many copies of your data and takes up a lot of memory. Suprisingly, that's not the case. But first note that worrying about memory is not a useful way to spend your time: worry about it when it becomes a problem (i.e. you run out of memory), not before. Second, R isn't stupid: if you're working with data frames, R will share columns where possible. Let's take a look at an actual data manipulation pipeline where we add a new column to `ggplot2::diamonds`:
How can that work? Well, `diamonds2` has 10 columns in common with `diamonds`: there's no need to duplicate all that data, so the two data frames have variables in common. These variables will only get copied if you modify one of them.
In the following example, we modify a single value in `diamonds$carat`. That means the `carat` variable can no longer be shared between the two data frames, and a copy must be made. The individual size of each data frame will be unchanged, but the collective size increases:
(Note that we use `pryr::object_size()` here, not the built-in `object.size()`. `object.size()` isn't quite smart enough to recognise that the columns are shared across multiple data frames.)
Here the disadvantage is that you have to read from inside-out, from right-to-left, and that the arguments end up spread far apart (evocatively called the
This is my favourite form, because it focusses on verbs, not nouns. You can read this series of function compositions like it's a set of imperative actions. Foo foo hops, then scoops, then bops. The downside, of course, is that you need to be familiar with the pipe. If you've never seen `%>%` before, you'll have no idea what this code does. Fortunately, most people pick up the idea very quickly, so when you share you code with others who aren't familiar with the pipe, you can easily teach them.
The pipe works by doing "lexical transformation". Behind the scenes, magrittr reassembles the code in the pipe to a form that works by overwriting an intermediate object. When you run a pipe like the one above, magrittr does something like this:
The pipe is a powerful tool, but it's not the only tool at your disposal, and it doesn't solve every problem! Pipes are most useful for rewriting a fairly short linear sequence of operations. I think you should reach for another tool when:
All packages in the tidyverse automatically make `%>%` avaiable for you, so you don't normally load magrittr explicitly. However, there are some other useful tools inside magrittr that you might want to try out:
