120 lines
4.9 KiB
Plaintext
120 lines
4.9 KiB
Plaintext
# Workflow: Pipes {#workflow-pipes}
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```{r, results = "asis", echo = FALSE}
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status("restructuring")
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```
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The pipe, `|>`, is a powerful tool for clearly expressing a sequence of operations that transform an object.
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We briefly introduced pipes in the previous chapter but before going too much farther I wanted to give a few more details and discuss, `%>%`, an predecessor to `|>`.
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To add the pipe to your code, we recommend using the build-in keyboard shortcut Ctrl/Cmd + Shift + M.
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You'll need to make one change to your RStudio options to use `|>` instead of `%>%` as shown in Figure \@ref(fig:pipe-options); more `%>%` that next.
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```{r pipe-options, out.width = NULL, echo = FALSE}
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#| fig.cap: >
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#| To insert `|>`, make sure the "Use native pipe" option is checked.
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#| fig.alt: >
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#| Screenshot showing the "Use native pipe operator" option which can
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#| be found on the "Editing" panel of the "Code" options.
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knitr::include_graphics("screenshots/rstudio-pipe-options.png")
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```
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## Why use a pipe?
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Each individual dplyr function is quite simple so solving complex problems typically require multiple verbs together.
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For example, the last chapter finished with a moderately complex pipe:
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```{r, eval = FALSE}
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flights |>
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filter(!is.na(arr_delay), !is.na(tailnum)) |>
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group_by(tailnum) |>
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summarise(
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delay = mean(arr_delay, na.rm = TRUE),
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n = n()
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)
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```
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Even though this pipe has four steps, it's quite easy to skim because the verbs come at the start of each line: we start with the flights data, then filter, then group, then summarize.
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What would happen if we didn't have the pipe?
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We could nest each function call inside the previous call:
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```{r, eval = FALSE}
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summarise(
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group_by(
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filter(
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flights,
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!is.na(arr_delay), !is.na(tailnum)
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),
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tailnum
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),
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delay = mean(arr_delay, na.rm = TRUE
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),
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n = n()
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)
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```
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Or we could use a bunch of intermediate variables:
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```{r, eval = FALSE}
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flights1 <- filter(flights, !is.na(arr_delay), !is.na(tailnum))
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flights2 <- group_by(flights1, tailnum)
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flights3 <- summarise(flight2,
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delay = mean(arr_delay, na.rm = TRUE),
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n = n()
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)
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```
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While both of these forms have their place and time, the pipe generally produces code that is easier to read and easier to write.
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## magrittr and the `%>%` pipe
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If you've been using the tidyverse for a while, you might be more familiar with the `%>%` pipe provided by the **magrittr** package.
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The magrittr package is included in the code the tidyverse, so you can use `%>%` whenever you load the tidyverse:
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```{r, message = FALSE}
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library(tidyverse)
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mtcars %>%
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group_by(cyl) %>%
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summarise(n = n())
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```
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For simple cases `|>` and `%>%` behave identically.
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So why do we recommend the base pipe?
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Firstly, because it's part of base R, it's always available for you to use, even when you're not using the tidyverse.
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Secondly, `|>` is quite a bit simpler than `%>%`: in the time between the invention of `%>%` in 2014 and the inclusion of `|>` in R 4.1.0 in 2021, we gained a better understanding of the pipe.
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This allowed the base implementation to jettison infrequently used and less important features.
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## Base pipe vs magrittr pipe
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While `|>` and `%>%` behave identically for simple cases there are a few important differences.
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These are most likely to affect you if you're a long-term `%>%` user who has taken advantage of some of the more advanced features.
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But they're good to know about even if you've never used `%>%`, because you're likely to encounter some of them when reading wild-caught code.
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- By default, the pipe passes the object on its left hand side to the first argument of the function on the right-hand side.
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`%>%` allows you change the placement a `.` placeholder.
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For example, `x %>% f(1)` is equivalent to `f(x, 1)` but `x %>% f(1, .)` is equivalent to `f(1, x)`.
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R 4.2.0 will bring a `_` as a placeholder to the base pipe, with one additional restriction: the argument has to be named.
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For example, `x |> f(1, y = _)` is equivalent to `f(1, y = x)`.
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- The `|>` placeholder is deliberately simple and can't replicate many features of the `%>%` placeholder: you can't pass it to multiple arguments, and it doesn't have any special behavior when the placeholder is used inside another function (i.e. `df %>% split(.$var)` is equivalent to `split(df, df$var)`.
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- You can also use both `.` and `_` on the left-hand side of operators like `$`, `[[`, `[` (which you'll learn about in Chapter \@ref(vectors)):
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``` r
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mtcars %>% .$cyl
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mtcars |> _$cyl
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```
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For the special case of extracting a column out of a data frame, you can also use `dplyr::pull():`
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```{r}
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mtcars |> pull(cyl)
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```
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- `%>%` allowed you to drop the parentheses when calling a function with no other arguments; `|>` always requires the parentheses.
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- `%>%` allowed you to starting a pipe with `.` to create a function rather than immediately executing the pipe; this is not supported by the base pipe.
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