-
Notifications
You must be signed in to change notification settings - Fork 157
/
README.Rmd
136 lines (101 loc) · 4.53 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/"
)
library(magrittr)
```
# magrittr <a href='https:/magrittr.tidyverse.org'><img src='man/figures/logo.png' align="right" height="139" /></a>
<!-- badges: start -->
[](https://cran.r-project.org/package=magrittr)
[](https://app.codecov.io/gh/tidyverse/magrittr?branch=main)
[](https://github.com/smbache/magrittr/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->
## Overview
The magrittr package offers a set of operators which make your code more
readable by:
* structuring sequences of data operations left-to-right (as opposed to
from the inside and out),
* avoiding nested function calls,
* minimizing the need for local variables and function definitions, and
* making it easy to add steps anywhere in the sequence of operations.
The operators pipe their left-hand side values forward into expressions that
appear on the right-hand side, i.e. one can replace `f(x)` with
`x %>% f()`, where `%>%` is the (main) pipe-operator. When coupling
several function calls with the pipe-operator, the benefit will become
more apparent. Consider this pseudo example:
```{r, eval = FALSE}
the_data <-
read.csv('/path/to/data/file.csv') %>%
subset(variable_a > x) %>%
transform(variable_c = variable_a/variable_b) %>%
head(100)
```
Four operations are performed to arrive at the desired data set, and they
are written in a natural order: the same as the order of execution. Also, no
temporary variables are needed. If yet another operation is required, it is
straightforward to add to the sequence of operations wherever it may be needed.
If you are new to magrittr, the best place to start is the
[pipes chapter](https://r4ds.had.co.nz/pipes.html) in R for data science.
## Installation
```{r, eval = FALSE}
# The easiest way to get magrittr is to install the whole tidyverse:
install.packages("tidyverse")
# Alternatively, install just magrittr:
install.packages("magrittr")
# Or the development version from GitHub:
# install.packages("devtools")
pak::pak("tidyverse/magrittr")
```
## Usage
### Basic piping
* `x %>% f` is equivalent to `f(x)`
* `x %>% f(y)` is equivalent to `f(x, y)`
* `x %>% f %>% g %>% h` is equivalent to `h(g(f(x)))`
Here, "equivalent" is not technically exact: evaluation is non-standard,
and the left-hand side is evaluated before passed on to the right-hand side
expression. However, in most cases this has no practical implication.
### The argument placeholder
* `x %>% f(y, .)` is equivalent to `f(y, x)`
* `x %>% f(y, z = .)` is equivalent to `f(y, z = x)`
### Re-using the placeholder for attributes
It is straightforward to use the placeholder several times
in a right-hand side expression. However, when the placeholder
only appears in a nested expressions magrittr will still apply
the first-argument rule. The reason is that in most cases this
results more clean code.
`x %>% f(y = nrow(.), z = ncol(.))` is equivalent to
`f(x, y = nrow(x), z = ncol(x))`
The behavior can be
overruled by enclosing the right-hand side in braces:
`x %>% {f(y = nrow(.), z = ncol(.))}` is equivalent to
`f(y = nrow(x), z = ncol(x))`
### Building (unary) functions
Any pipeline starting with the `.` will return a function which can later
be used to apply the pipeline to values. Building functions in magrittr
is therefore similar to building other values.
```{r}
f <- . %>% cos %>% sin
# is equivalent to
f <- function(.) sin(cos(.))
```
### Pipe with exposition of variables
Many functions accept a data argument, e.g. `lm` and `aggregate`, which
is very useful in a pipeline where data is first processed and then passed
into such a function. There are also functions that do not have a data
argument, for which it is useful to expose the variables in the data.
This is done with the `%$%` operator:
```{r exposition}
iris %>%
subset(Sepal.Length > mean(Sepal.Length)) %$%
cor(Sepal.Length, Sepal.Width)
data.frame(z = rnorm(100)) %$%
ts.plot(z)
```
## Code of Conduct
Please note that the magrittr project is released with a [Contributor Code of Conduct](https://magrittr.tidyverse.org/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.