前言
今天我们要介绍的是
tidyverse
中格式化字符串的软件包：
glue
glue
提供了轻巧、快速和无依赖的可解释字符串，
glue
通过将
R
表达式嵌入到花括号中，然后对其求值并将其插入字符串中。
安装
install.packages("glue")
# or
install.packages("glue")
# install.packages("devtools")
devtools::install_github("tidyverse/glue")
使用
1. 导入
library(glue)
2. 简单使用
将变量直接传递到字符串中
> name <- "Fred"
> glue('My name is {name}.')
My name is Fred.
通过将变量名放置在一对花括号之间，
glue
会将变量名替换为相应的值
字符串可以写成多行的形式，最后会自动将这些行连接起来
> name <- "Fred"
> age <- 50
> anniversary <- as.Date("1991-10-12")
> glue('My name is {name},',
+ ' my age next year is {age + 1},',
+ ' my anniversary is {format(anniversary, "%A, %B %d, %Y")}.')
My name is Fred, my age next year is 51, my anniversary is 星期六, 十月 12, 1991.
在
glue
中使用命名参数来指定临时变量
> glue('My name is {name},',
+ ' my age next year is {age + 1},',
+ ' my anniversary is {format(anniversary, "%A, %B %d, %Y")}.',
+ name = "Joe",
+ age = 40,
+ anniversary = as.Date("2001-10-12"))
My name is Joe, my age next year is 41, my anniversary is 星期五, 十月 12, 2001.
3. glue_data 搭配管道符
glue_data()
搭配管道符非常有用
> head(mtcars)
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
> head(mtcars) %>% glue_data("{rownames(.)} has {hp} hp")
Mazda RX4 has 110 hp
Mazda RX4 Wag has 110 hp
Datsun 710 has 93 hp
Hornet 4 Drive has 110 hp
Hornet Sportabout has 175 hp
Valiant has 105 hp
也可以搭配
dplyr
使用
> head(iris) %>%
+ mutate(description = glue("This {Species} has a petal length of {Petal.Length}"))
Sepal.Length Sepal.Width Petal.Length Petal.Width Species description
1 5.1 3.5 1.4 0.2 setosa This setosa has a petal length of 1.4
2 4.9 3.0 1.4 0.2 setosa This setosa has a petal length of 1.4
3 4.7 3.2 1.3 0.2 setosa This setosa has a petal length of 1.3
4 4.6 3.1 1.5 0.2 setosa This setosa has a petal length of 1.5
5 5.0 3.6 1.4 0.2 setosa This setosa has a petal length of 1.4
6 5.4 3.9 1.7 0.4 setosa This setosa has a petal length of 1.7
4. 字符串
前导空格和第一行以及最后一行的换行符会自动被修剪
> glue("
+ A formatted string
+ Can have multiple lines
+ with additional indention preserved
+ ")
A formatted string
Can have multiple lines
with additional indention preserved
可以在首行或尾行多添加一个换行符来实现空行
> glue("
+
+ leading or trailing newlines can be added explicitly
+
+ ")
leading or trailing newlines can be added explicitly
在行尾使用
\\
可以将两行合并
> glue("
+ A formatted string \\
+ can also be on a \\
+ single line
+ ")
A formatted string can also be on a single line
如果要字符串中使用花括号，需要使用双花括号
> name <- "Fred"
> glue("My name is {name}, not {{name}}.")
My name is Fred, not {name}.
注意
：请对比下面的区别
> a <- "foo"
> glue("{{a}}")
{a}
> glue("{{a} }")
{a} }
> glue("{ {a} }")
foo
> glue("{
+ a
+ }")
foo
> glue("{
+ {a}
+ }")
foo
> glue("{
+ {a}}")
foo
双花括号需要连用
可以使用
+
连接字符串
> x <- 1
> y <- 3
> glue("x + y") + " = {x + y}"
x + y = 4
5. 指定分隔符
glue
默认将花括号之间的字符作为变量名或者表达式，我们可以通过设置
.open
和 .
close
参数来指定分隔符
> one <- "1"
> glue("The value of $e^{2\\pi i}$ is $<<one>>$.", .open = "<<", .close = ">>")
The value of $e^{2\pi i}$ is $1$.
6. SQL 语句
glue
还提供了
glue_sql
函数，用于格式化
SQL
语句，例如
> con <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
> colnames(iris) <- gsub("[.]", "_", tolower(colnames(iris)))
> DBI::dbWriteTable(con, "iris", iris)
> var <- "sepal_width"
> tbl <- "iris"
> num <- 2
> val <- "setosa"
> glue_sql("
+ SELECT {`var`}
+ FROM {`tbl`}
+ WHERE {`tbl`}.sepal_length > {num}
+ AND {`tbl`}.species = {val}
+ ", .con = con)
<SQL> SELECT `sepal_width`
FROM `iris`
WHERE `iris`.sepal_length > 2
AND `iris`.species = 'setosa'
还可以配合
DBI::dbBind()
进行参数化查询
> sql <- glue_sql("
+ SELECT {`var`}
+ FROM {`tbl`}
+ WHERE {`tbl`}.sepal_length > ?
+ ", .con = con)
> query <- DBI::dbSendQuery(con, sql)
> DBI::dbBind(query, list(num))
> DBI::dbFetch(query, n = 4)
sepal_width
1 3.5
2 3.0
3 3.2
4 3.1
还支持更复杂的查询，比例嵌套子查询
> sub_query <- glue_sql("
+ SELECT *
+ FROM {`tbl`}
+ ", .con = con)
>
> glue_sql("
+ SELECT s.{`var`}
+ FROM ({sub_query}) AS s
+ ", .con = con)
<SQL> SELECT s.`sepal_width`
FROM (SELECT *
FROM `iris`) AS s
还可以在
IN
声明之后添加
*
来接受多个值
> glue_sql("SELECT * FROM {`tbl`} WHERE sepal_length IN ({vals*})",
+ vals = 1, .con = con)
<SQL> SELECT * FROM `iris` WHERE sepal_length IN (1)
> glue_sql("SELECT * FROM {`tbl`} WHERE sepal_length IN ({vals*})",
+ vals = 1:5, .con = con)
<SQL> SELECT * FROM `iris` WHERE sepal_length IN (1, 2, 3, 4, 5)
> glue_sql("SELECT * FROM {`tbl`} WHERE species IN ({vals*})",
+ vals = "setosa", .con = con)
<SQL> SELECT * FROM `iris` WHERE species IN ('setosa')
> glue_sql("SELECT * FROM {`tbl`} WHERE species IN ({vals*})",
+ vals = c("setosa", "versicolor"), .con = con)
<SQL> SELECT * FROM `iris` WHERE species IN ('setosa', 'versicolor')
7. 字符串向量的折叠
可以使用
glue_collapse
将任意长度的字符串向量折叠为长度为 1 的字符串向量
glue_collapse(x, sep = "", width = Inf, last = "")
> glue_collapse(glue("{1:10}"))
12345678910
> glue_collapse(glue("{1:10}"), width = 7)
1234...
> glue_collapse(1:4, ", ", last = " and ")
1, 2, 3 and 4
8. 单个元素的引用
下面三个对单个元素引用函数可以搭配
glue_collapse
使用
-
single_quote(x)
：用单引号包裹字符串元素
-
double_quote(x)
：用双引号包裹字符串元素
-
backtick(x)
：用反引号包裹字符串元素
> glue('Values of x: {glue_collapse(backtick(x), sep = ", ", last = " and ")}')
Values of x: `1`, `2`, `3`, `4` and `5`
> glue('Values of x: {glue_collapse(single_quote(x), sep = ", ", last = " and ")}')
Values of x: '1', '2', '3', '4' and '5'
> glue('Values of x: {glue_collapse(double_quote(x), sep = ", ", last = " and ")}')
Values of x: "1", "2", "3", "4" and "5"
9. 为输出着色
glue
可以搭配
crayon
包定义的一些用于终端输出着色的函数，来为我们的输出文本着色
先导入
crayon
> require(crayon)
glue
提供了
glue_col()
和
glue_data_col()
两个着色函数
我们可以设置白底黑字
> white_on_grey <- bgBlack $ white
> glue_col("{white_on_grey
+ Roses are {red {colors()[[552]]}}
+ Violets are {blue {colors()[[26]]}}
+ `glue_col()` can show {red c}{yellow o}{green l}{cyan o}{blue r}{magenta s}
+ and {bold bold} and {underline underline} too!
+ }")
