如何通过从R中的列名生成键来透视/收集多组/多对列？

我有以下数据集

grade9_math_zscore <- rnorm(10, 0,1)
grade9_science_zscore <- rnorm(10, 0,1)
grade10_math_zscore <- rnorm(10, 0,1)
grade10_science_zscore <- rnorm(10, 0,1)
grade9_math_passed_lab<- sample(0:1,10,replace=TRUE)
grade10_math_passed_lab<- sample(0:1,10,replace=TRUE)
grade9_science_passed_lab<- sample(0:1,10,replace=TRUE)
grade10_science_passed_lab<- sample(0:1,10,replace=TRUE)
grade9_math_used_comp  <- sample(0:1,10,replace=TRUE)
grade10_math_used_comp  <- sample(0:1,10,replace=TRUE)
grade9_science_used_comp  <- sample(0:1,10,replace=TRUE)
grade10_science_used_comp  <- sample(0:1,10,replace=TRUE)
students<-as.data.frame(cbind(grade9_math_zscore, grade9_science_zscore, grade10_math_zscore , grade10_science_zscore , grade9_math_passed_lab, grade10_math_passed_lab, grade9_science_passed_lab,  grade10_science_passed_lab, grade9_math_used_comp,  grade10_math_used_comp, grade9_science_used_comp, grade10_science_used_comp ))

我一直在尝试从R上的

dplyr

中使用

pivot\u longer

获取此信息。我需要的帮助主要是找出

names\u模式

选项。另外，我似乎无法

收集
（用dplyr术语）所有三列
z_分数，通过实验室，在一个命令中使用comp

欢迎提供任何编码解决方案或建议。不使用dplyr的任何解决方案也将受到欢迎。
使用
pivot\u更长的时间
您可以：

tidyr::pivot_longer(students, 
                    cols = everything(), 
                    names_to = c('grade', 'course', '.value'), 
                    names_pattern = 'grade(\\d+)_(.*?)_(.*)')

# A tibble: 40 x 5
#   grade course  zscore passed_lab used_comp
#   <chr> <chr>    <dbl>      <int>     <int>
# 1 9     math    -1.04           0         1
# 2 9     science  0.608          0         0
# 3 10    math     1.27           0         1
# 4 10    science  1.38           1         1
# 5 9     math    -1.30           1         1
# 6 9     science  0.582          1         1
# 7 10    math    -0.196          1         1
# 8 10    science -0.198          0         1
# 9 9     math    -1.28           1         1
#10 9     science  2.05           0         0
# … with 30 more rows

与
rnorm
或
sample
等函数共享示例时，请使用
set.seed
，以确保再现性
tidyr::pivot_longer(students, 
                    cols = everything(), 
                    names_to = c('grade', 'course', '.value'), 
                    names_pattern = 'grade(\\d+)_(.*?)_(.*)')

# A tibble: 40 x 5
#   grade course  zscore passed_lab used_comp
#   <chr> <chr>    <dbl>      <int>     <int>
# 1 9     math    -1.04           0         1
# 2 9     science  0.608          0         0
# 3 10    math     1.27           0         1
# 4 10    science  1.38           1         1
# 5 9     math    -1.30           1         1
# 6 9     science  0.582          1         1
# 7 10    math    -0.196          1         1
# 8 10    science -0.198          0         1
# 9 9     math    -1.28           1         1
#10 9     science  2.05           0         0
# … with 30 more rows

students<-data.frame(grade9_math_zscore, grade9_science_zscore....)