![[Experimental]](https://vimsky.com/wp-content/uploads/2023/09/73dbf2dc69cc148b712effefdd2659ba.svg)
构造一个字符向量，可以使用预定义的最小宽度或没有宽度限制进行格式化，并且可以在其中配置缩写样式。
当打印或格式化矢量时，以及在 tibble 列中，会应用该格式。
set_char_opts() 将格式化选项添加到任意字符向量，对于与其他类型组合非常有用。
用法
char(
x,
...,
min_chars = NULL,
shorten = c("back", "front", "mid", "abbreviate")
)
set_char_opts(
x,
...,
min_chars = NULL,
shorten = c("back", "front", "mid", "abbreviate")
)参数
- x
-
字符向量。
- ...
-
这些点用于将来的扩展，并且必须为空。
- min_chars
-
分配给该列的最小宽度，默认为 15。不参考
"pillar.min_chars"option。 - shorten
-
必要时如何缩写数据：
-
"back"(默认)：在末尾添加省略号 -
"front": 在前面添加省略号 -
"mid": 在中间添加省略号 -
"abbreviate"：使用abbreviate()
-
也可以看看
其他向量类：num()
例子
# Display as a vector:
char(letters[1:3])
#> <pillar_char[3]>
#> [1] a b c
# Space constraints:
rand_strings <- stringi::stri_rand_strings(10, seq(40, 22, by = -2))
# Plain character vectors get truncated if space is limited:
data_with_id <- function(id) {
tibble(
id,
some_number_1 = 1, some_number_2 = 2, some_number_3 = 3,
some_number_4 = 4, some_number_5 = 5, some_number_6 = 6,
some_number_7 = 7, some_number_8 = 8, some_number_9 = 9
)
}
data_with_id(rand_strings)
#> # A tibble: 10 × 10
#> id some_…¹ some_…² some_…³ some_…⁴ some_…⁵ some_…⁶ some_…⁷ some_…⁸
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 WJSsxf… 1 2 3 4 5 6 7 8
#> 2 HQOlqj… 1 2 3 4 5 6 7 8
#> 3 GR8hYm… 1 2 3 4 5 6 7 8
#> 4 dO0k5C… 1 2 3 4 5 6 7 8
#> 5 3yKhjZ… 1 2 3 4 5 6 7 8
#> 6 uyWa9T… 1 2 3 4 5 6 7 8
#> 7 UaiZMc… 1 2 3 4 5 6 7 8
#> 8 z2qYwl… 1 2 3 4 5 6 7 8
#> 9 ek4O7h… 1 2 3 4 5 6 7 8
#> 10 YCRHBt… 1 2 3 4 5 6 7 8
#> # … with 1 more variable: some_number_9 <dbl>, and abbreviated variable
#> # names ¹some_number_1, ²some_number_2, ³some_number_3, ⁴some_number_4,
#> # ⁵some_number_5, ⁶some_number_6, ⁷some_number_7, ⁸some_number_8
# Use char() to avoid or control truncation
data_with_id(char(rand_strings, min_chars = 24))
#> # A tibble: 10 × 10
#> id some_…¹ some_…² some_…³ some_…⁴ some_…⁵
#> <char> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 WJSsxf5RPiDjFRy7iVoadHgnz4uveI… 1 2 3 4 5
#> 2 HQOlqjZavreUgr3GXLoDX6mpkxihE2… 1 2 3 4 5
#> 3 GR8hYmPYrwJG9UsJm9A47KvwLTo2FQ… 1 2 3 4 5
#> 4 dO0k5CLEp9McpsCkmBt5wkYOioyg9C… 1 2 3 4 5
#> 5 3yKhjZZbegjEYOJm1HIxNkWvYx8Ozl… 1 2 3 4 5
#> 6 uyWa9TGFPzGkVAZsJlCaIHvalJsvMC 1 2 3 4 5
#> 7 UaiZMcOCjm7Lh2Gthq6NgOGsJbR2 1 2 3 4 5
#> 8 z2qYwlo7fldemmrE772uCYLrI6 1 2 3 4 5
#> 9 ek4O7hFxIud6K9YsvhQTB6Oe 1 2 3 4 5
#> 10 YCRHBt1kj2i9JnNgyaa5MB 1 2 3 4 5
#> # … with 4 more variables: some_number_6 <dbl>, some_number_7 <dbl>,
#> # some_number_8 <dbl>, some_number_9 <dbl>, and abbreviated variable
#> # names ¹some_number_1, ²some_number_2, ³some_number_3, ⁴some_number_4,
#> # ⁵some_number_5
data_with_id(char(rand_strings, min_chars = Inf))
#> # A tibble: 10 × 10
#> id some_number_1 some_n…¹ some_…²
#> <char> <dbl> <dbl> <dbl>
#> 1 WJSsxf5RPiDjFRy7iVoadHgnz4uveIpMlA7Qaqjz 1 2 3
#> 2 HQOlqjZavreUgr3GXLoDX6mpkxihE20qyTAB45 1 2 3
#> 3 GR8hYmPYrwJG9UsJm9A47KvwLTo2FQEkuqMT 1 2 3
#> 4 dO0k5CLEp9McpsCkmBt5wkYOioyg9COiuR 1 2 3
#> 5 3yKhjZZbegjEYOJm1HIxNkWvYx8Ozl85 1 2 3
#> 6 uyWa9TGFPzGkVAZsJlCaIHvalJsvMC 1 2 3
#> 7 UaiZMcOCjm7Lh2Gthq6NgOGsJbR2 1 2 3
#> 8 z2qYwlo7fldemmrE772uCYLrI6 1 2 3
#> 9 ek4O7hFxIud6K9YsvhQTB6Oe 1 2 3
#> 10 YCRHBt1kj2i9JnNgyaa5MB 1 2 3
#> # … with 6 more variables: some_number_4 <dbl>, some_number_5 <dbl>,
#> # some_number_6 <dbl>, some_number_7 <dbl>, some_number_8 <dbl>,
#> # some_number_9 <dbl>, and abbreviated variable names ¹some_number_2,
#> # ²some_number_3
data_with_id(char(rand_strings, min_chars = 24, shorten = "mid"))
#> # A tibble: 10 × 10
#> id some_…¹ some_…² some_…³ some_…⁴ some_…⁵
#> <char> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 WJSsxf5RPiDjFRy…4uveIpMlA7Qaqjz 1 2 3 4 5
#> 2 HQOlqjZavreUgr3…pkxihE20qyTAB45 1 2 3 4 5
#> 3 GR8hYmPYrwJG9Us…KvwLTo2FQEkuqMT 1 2 3 4 5
#> 4 dO0k5CLEp9McpsC…5wkYOioyg9COiuR 1 2 3 4 5
#> 5 3yKhjZZbegjEYOJ…HIxNkWvYx8Ozl85 1 2 3 4 5
#> 6 uyWa9TGFPzGkVAZsJlCaIHvalJsvMC 1 2 3 4 5
#> 7 UaiZMcOCjm7Lh2Gthq6NgOGsJbR2 1 2 3 4 5
#> 8 z2qYwlo7fldemmrE772uCYLrI6 1 2 3 4 5
#> 9 ek4O7hFxIud6K9YsvhQTB6Oe 1 2 3 4 5
#> 10 YCRHBt1kj2i9JnNgyaa5MB 1 2 3 4 5
#> # … with 4 more variables: some_number_6 <dbl>, some_number_7 <dbl>,
#> # some_number_8 <dbl>, some_number_9 <dbl>, and abbreviated variable
#> # names ¹some_number_1, ²some_number_2, ³some_number_3, ⁴some_number_4,
#> # ⁵some_number_5
# Lorem Ipsum, one sentence per row.
lipsum <- unlist(strsplit(stringi::stri_rand_lipsum(1), "(?<=[.]) +", perl = TRUE))
tibble(
back = char(lipsum, shorten = "back"),
front = char(lipsum, shorten = "front"),
mid = char(lipsum, shorten = "mid")
)
#> # A tibble: 10 × 3
#> back front mid
#> <char> <cha> <cha>
#> 1 Lorem ipsum dolor sit amet, sit et auctor lacinia etiam co… …iis. Lo…s.
#> 2 Laoreet in nec diam ut suspendisse adipiscing suspendisse … …pis. La…s.
#> 3 Eleifend eleifend, metus nunc turpis. …pis. El…s.
#> 4 Augue massa lobortis faucibus velit efficitur ac faucibus. …bus. Au…s.
#> 5 Elit egestas egestas sit amet ut conubia faucibus facilisi. …isi. El…i.
#> 6 Tempor urna nisi feugiat senectus. …tus. Te…s.
#> 7 Nunc in pretium dui ac. … ac. Nu…c.
#> 8 Elit semper eu. … eu. El…u.
#> 9 Sapien congue, dictum massa sed posuere sagittis. …tis. Sa…s.
#> 10 Interdum ante aenean, nisi dapibus lacinia nulla laoreet, … …bus. In…s.
tibble(abbr = char(lipsum, shorten = "abbreviate"))
#> # A tibble: 10 × 1
#> abbr
#> <char>
#> 1 Loremipsumdolorsitamet,sitetauctorlacinetiamcommodo!Tincidntd,nslvtscs.
#> 2 Laoreetinnecdiamutsuspendissadipiscingsuspendissconubtortorrissdnctrps.
#> 3 Eleifend eleifend, metus nunc turpis.
#> 4 Augue massa lobortis faucibus velit efficitur ac faucibus.
#> 5 Elit egestas egestas sit amet ut conubia faucibus facilisi.
#> 6 Tempor urna nisi feugiat senectus.
#> 7 Nunc in pretium dui ac.
#> 8 Elit semper eu.
#> 9 Sapien congue, dictum massa sed posuere sagittis.
#> 10 Interdumanteaenean,nisidapibuslacinianulllaoreet,felisultriciesdapibus.
相关用法
- R tibble tibble 构建 DataFrame 架
- R tibble frame_matrix 逐行矩阵创建
- R tibble num 设置数值向量的格式
- R tibble rownames 用于处理行名称的工具
- R tibble enframe 将向量转换为数据帧，反之亦然
- R tibble add_row 将行添加到 DataFrame
- R tibble as_tibble 将列表、矩阵等强制转换为 DataFrame
- R tibble subsetting 子集化标题
- R tibble tibble_options 封装选项
- R tibble add_column 将列添加到 DataFrame
- R tibble lst 建立一个清单
- R tibble formatting 打印小标题
- R tibble new_tibble Tibble 构造函数和验证器
- R tibble tribble 逐行小标题创建
- R tidyr separate_rows 将折叠的列分成多行
- R tidyr extract 使用正则表达式组将字符列提取为多列
- R tidyr chop 砍伐和砍伐
- R tidyr pivot_longer_spec 使用规范将数据从宽转为长
- R tidyr unnest_longer 将列表列取消嵌套到行中
- R tidyr uncount “计数” DataFrame
- R tidyr cms_patient_experience 来自医疗保险和医疗补助服务中心的数据
- R tidyr pivot_wider_spec 使用规范将数据从长轴转向宽轴
- R tidyverse tidyverse_update 更新 tidyverse 软件包
- R tidyr replace_na 将 NA 替换为指定值
- R tidyr unnest_wider 将列表列取消嵌套到列中
注：本文由纯净天空筛选整理自Kirill Müller等大神的英文原创作品 Format a character vector。非经特殊声明，原始代码版权归原作者所有，本译文未经允许或授权，请勿转载或复制。