变异多个变量以创建多个新变量 [英] Mutate multiple variable to create multiple new variables
问题描述
假设我有一个 tibble，我需要在其中获取多个变量并将它们变异为新的多个新变量.
举个例子，这是一个简单的小标题:
tb <- tribble(~x, ~y1, ~y2, ~y3, ~z,1,2,4,6,2,2,1,2,3,3,3,6,4,2,1)我想从名称以y"开头的每个变量中减去变量 z，并将结果变异为 tb 的新变量.另外，假设我不知道我有多少y"变量.我希望该解决方案非常适合 tidyverse/dplyr 工作流程.
本质上，我不明白如何将多个变量变异为多个新变量.我不确定您是否可以在这种情况下使用 mutate ?我已经尝试过 mutate_if，但我认为我没有正确使用它(并且出现错误):
tb %>% mutate_if(starts_with("y"), funs(.-z))#Error: 没有注册 tidyselect 变量提前致谢！
因为操作的是列名，所以需要使用 mutate_at 而不是 mutate_if列内的值
tb %>% mutate_at(vars(starts_with(y")), funs(. - z))#># 小块:3 x 5#>x y1 y2 y3 z#><dbl><dbl><dbl><dbl><dbl>#>1 1 0 2 4 2#>2 2 -2 -1 0 3#>3 3 5 3 1 1要创建新列，而不是覆盖现有列，我们可以为 funs
#添加后缀tb %>% mutate_at(vars(starts_with(y")), funs(mod = . - z))#># 小块:3 x 8#>x y1 y2 y3 z y1_mod y2_mod y3_mod#><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>#>1 1 2 4 6 2 0 2 4#>2 2 1 2 3 3 -2 -1 0#>3 3 6 4 2 1 5 3 1# 去除后缀，添加前缀tb%＞%mutate_at(vars(starts_with(y")), funs(mod = . - z)) %>%rename_at(vars(ends_with("_mod")), funs(paste("mod", gsub("_mod", "", .), sep = "_")))#># 小块:3 x 8#>x y1 y2 y3 z mod_y1 mod_y2 mod_y3#><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>#>1 1 2 4 6 2 0 2 4#>2 2 1 2 3 3 -2 -1 0#>3 3 6 4 2 1 5 3 1编辑:在 dplyr 0.8.0 或更高版本中，funs() 将被弃用(source1 & source2)，需要改用list()
tb %>% mutate_at(vars(starts_with(y")), list(~ . - z))#># 小块:3 x 5#>x y1 y2 y3 z#><dbl><dbl><dbl><dbl><dbl>#>1 1 0 2 4 2#>2 2 -2 -1 0 3#>3 3 5 3 1 1tb %>% mutate_at(vars(starts_with(y")), list(mod = ~ . - z))#># 小块:3 x 8#>x y1 y2 y3 z y1_mod y2_mod y3_mod#><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>#>1 1 2 4 6 2 0 2 4#>2 2 1 2 3 3 -2 -1 0#>3 3 6 4 2 1 5 3 1tb%＞%mutate_at(vars(starts_with("y")), list(mod = ~ . - z)) %>%rename_at(vars(ends_with("_mod")), list(~ paste("mod", gsub("_mod", "", .), sep = "_")))#># 小块:3 x 8#>x y1 y2 y3 z mod_y1 mod_y2 mod_y3#><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>#>1 1 2 4 6 2 0 2 4#>2 2 1 2 3 3 -2 -1 0#>3 3 6 4 2 1 5 3 1编辑 2:dplyr 1.0.0+ 有 across() 函数进一步简化了这个任务
基本用法
<块引用>
across() 有两个主要参数:
<块引用>
- 第一个参数
.cols选择要操作的列.它使用整洁的选择(如select())，因此您可以通过以下方式选择变量位置、名称和类型.
<块引用>
- 第二个参数
.fns是一个函数或要应用的函数列表每列.这也可以是 purrr 风格的公式(或公式列表)像~.x/2.(这个参数是可选的，如果你只是想要，你可以省略它获取底层数据；你会看到该技术用于vignette(rowwise").)
# 控制如何使用 `.names` 参数创建名称# 采用 [glue](http://glue.tidyverse.org/) 规范:tb%＞%变异(跨越(starts_with(y")，〜.x - z，.names =mod_{col}"))#># 小块:3 x 8#>x y1 y2 y3 z mod_y1 mod_y2 mod_y3#><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>#>1 1 2 4 6 2 0 2 4#>2 2 1 2 3 3 -2 -1 0#>3 3 6 4 2 1 5 3 1tb%＞%变异(跨越(num_range(前缀 = y"，范围 = 1:3)，~ .x - z，.names = mod_{col}"))#># 小块:3 x 8#>x y1 y2 y3 z mod_y1 mod_y2 mod_y3#><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>#>1 1 2 4 6 2 0 2 4#>2 2 1 2 3 3 -2 -1 0#>3 3 6 4 2 1 5 3 1### 多种功能tb%＞%变异(跨越(c(匹配(x")，包含(z"))，〜max(.x，na.rm = TRUE)，.names =max_{col}")，跨越(c(y1:y3)，〜.x - z，.names =mod_{col}"))#># 小费:3 x 10#>x y1 y2 y3 z max_x max_z mod_y1 mod_y2 mod_y3#><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>#>1 1 2 4 6 2 3 3 0 2 4#>2 2 1 2 3 3 3 3 -2 -1 0#>3 3 6 4 2 1 3 3 5 3 1由 reprex 包 (v0.2.1) 于 2018 年 10 月 29 日创建
Let's say I have a tibble where I need to take multiple variables and mutate them into new multiple new variables.
As an example, here is a simple tibble:
tb <- tribble(
~x, ~y1, ~y2, ~y3, ~z,
1,2,4,6,2,
2,1,2,3,3,
3,6,4,2,1
)
I want to subtract variable z from every variable with a name starting with "y", and mutate the results as new variables of tb. Also, suppose I don't know how many "y" variables I have. I want the solution to fit nicely within tidyverse / dplyr workflow.
In essence, I don't understand how to mutate multiple variables into multiple new variables. I'm not sure if you can use mutate in this instance? I've tried mutate_if, but I don't think I'm using it right (and I get an error):
tb %>% mutate_if(starts_with("y"), funs(.-z))
#Error: No tidyselect variables were registered
Thanks in advance!
Because you are operating on column names, you need to use mutate_at rather than mutate_if which uses the values within columns
tb %>% mutate_at(vars(starts_with("y")), funs(. - z))
#> # A tibble: 3 x 5
#> x y1 y2 y3 z
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 0 2 4 2
#> 2 2 -2 -1 0 3
#> 3 3 5 3 1 1
To create new columns, instead of overwriting existing ones, we can give name to funs
# add suffix
tb %>% mutate_at(vars(starts_with("y")), funs(mod = . - z))
#> # A tibble: 3 x 8
#> x y1 y2 y3 z y1_mod y2_mod y3_mod
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 4 6 2 0 2 4
#> 2 2 1 2 3 3 -2 -1 0
#> 3 3 6 4 2 1 5 3 1
# remove suffix, add prefix
tb %>%
mutate_at(vars(starts_with("y")), funs(mod = . - z)) %>%
rename_at(vars(ends_with("_mod")), funs(paste("mod", gsub("_mod", "", .), sep = "_")))
#> # A tibble: 3 x 8
#> x y1 y2 y3 z mod_y1 mod_y2 mod_y3
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 4 6 2 0 2 4
#> 2 2 1 2 3 3 -2 -1 0
#> 3 3 6 4 2 1 5 3 1
Edit: In dplyr 0.8.0 or higher versions, funs() will be deprecated (source1 & source2), need to use list() instead
tb %>% mutate_at(vars(starts_with("y")), list(~ . - z))
#> # A tibble: 3 x 5
#> x y1 y2 y3 z
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 0 2 4 2
#> 2 2 -2 -1 0 3
#> 3 3 5 3 1 1
tb %>% mutate_at(vars(starts_with("y")), list(mod = ~ . - z))
#> # A tibble: 3 x 8
#> x y1 y2 y3 z y1_mod y2_mod y3_mod
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 4 6 2 0 2 4
#> 2 2 1 2 3 3 -2 -1 0
#> 3 3 6 4 2 1 5 3 1
tb %>%
mutate_at(vars(starts_with("y")), list(mod = ~ . - z)) %>%
rename_at(vars(ends_with("_mod")), list(~ paste("mod", gsub("_mod", "", .), sep = "_")))
#> # A tibble: 3 x 8
#> x y1 y2 y3 z mod_y1 mod_y2 mod_y3
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 4 6 2 0 2 4
#> 2 2 1 2 3 3 -2 -1 0
#> 3 3 6 4 2 1 5 3 1
Edit 2: dplyr 1.0.0+ has across() function which simplifies this task even further
Basic usage
across()has two primary arguments:
- The first argument,
.cols, selects the columns you want to operate on. It uses tidy selection (likeselect()) so you can pick variables by position, name, and type.
- The second argument,
.fns, is a function or list of functions to apply to each column. This can also be a purrr style formula (or list of formulas) like~ .x / 2. (This argument is optional, and you can omit it if you just want to get the underlying data; you'll see that technique used invignette("rowwise").)
# Control how the names are created with the `.names` argument which
# takes a [glue](http://glue.tidyverse.org/) spec:
tb %>%
mutate(
across(starts_with("y"), ~ .x - z, .names = "mod_{col}")
)
#> # A tibble: 3 x 8
#> x y1 y2 y3 z mod_y1 mod_y2 mod_y3
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 4 6 2 0 2 4
#> 2 2 1 2 3 3 -2 -1 0
#> 3 3 6 4 2 1 5 3 1
tb %>%
mutate(
across(num_range(prefix = "y", range = 1:3), ~ .x - z, .names = "mod_{col}")
)
#> # A tibble: 3 x 8
#> x y1 y2 y3 z mod_y1 mod_y2 mod_y3
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 4 6 2 0 2 4
#> 2 2 1 2 3 3 -2 -1 0
#> 3 3 6 4 2 1 5 3 1
### Multiple functions
tb %>%
mutate(
across(c(matches("x"), contains("z")), ~ max(.x, na.rm = TRUE), .names = "max_{col}"),
across(c(y1:y3), ~ .x - z, .names = "mod_{col}")
)
#> # A tibble: 3 x 10
#> x y1 y2 y3 z max_x max_z mod_y1 mod_y2 mod_y3
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 4 6 2 3 3 0 2 4
#> 2 2 1 2 3 3 3 3 -2 -1 0
#> 3 3 6 4 2 1 3 3 5 3 1
Created on 2018-10-29 by the reprex package (v0.2.1)
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