R 在和包含时使用case_进行变异
我觉得当和R 在和包含时使用case_进行变异,r,dplyr,tidyverse,R,Dplyr,Tidyverse,我觉得当和包含时,应该有一种有效的方法来使用dplyr使用case\u变异新列,但无法使其工作 我理解在mutate中使用case_是“有点实验性的”(如在文章中),但如果您有任何建议,我将不胜感激 不起作用: library(tidyverse) set.seed(1234) x <- c("Black", "Blue", "Green", "Red") df <- data.frame(a = 1:20, b = sample(x,20,
包含
时,应该有一种有效的方法来使用dplyr
使用case\u变异新列,但无法使其工作
我理解在mutate
中使用case_是“有点实验性的”(如在文章中),但如果您有任何建议,我将不胜感激
不起作用:
library(tidyverse)
set.seed(1234)
x <- c("Black", "Blue", "Green", "Red")
df <- data.frame(a = 1:20,
b = sample(x,20, replace=TRUE))
df <- df %>%
mutate(group = case_when(.$b(contains("Bl")) ~ "Group1",
case_when(.$b(contains("re", ignore.case=TRUE)) ~ "Group2")
)
库(tidyverse)
种子集(1234)
x我们可以使用grep
df %>%
mutate(group = case_when(grepl("Bl", b) ~ "Group1",
grepl("re", b, ignore.case = TRUE) ~"Group2"))
# a b group
#1 1 Black Group1
#2 2 Green Group2
#3 3 Green Group2
#4 4 Green Group2
#5 5 Red Group2
#6 6 Green Group2
#7 7 Black Group1
#8 8 Black Group1
#9 9 Green Group2
#10 10 Green Group2
#11 1 Green Group2
#12 2 Green Group2
#13 3 Blue Group1
#14 4 Red Group2
#15 5 Blue Group1
#16 6 Red Group2
#17 7 Blue Group1
#18 8 Blue Group1
#19 9 Black Group1
#20 10 Black Group1
想添加一些示例,使用str_detect
和paste0
函数,这也将使连接公共组成为一件轻而易举的事。假设你与gapminder或其他国家的df合作
interest <- c("Austria", "Belgium", "Bulgaria", "Croatia", "Cyprus",
"Czech Republic", "Denmark", "Estonia", "Finland",
"France", "Germany", "Greece", "Hungary", "Ireland",
"Italy", "Latvia", "Lithuania", "Luxembourg","Malta",
"The Netherlands", "Poland","Portugal", "Romania",
"Slovakia", "Slovenia","Spain", "Sweden","United Kingdom")
EU <- paste0(countrycode::countryname(
sourcevar = interest, destination = "iso2c"),
sep = "|", collapse = "")
df%<>%mutate(Region=case_when(
str_detect(Country, "AT|BE|BG|HR|CY|CZ|DK|EE|FI|FR|DE|GR|HU|IE|
IT|LV|LT|LU|MT|NL|PL|PT|RO|SK|SI|ES|SE|GB|UK|G8")~ "EU",
TRUE ~ "Not EU")) ```
You'll need to load `library(magittr)` to get `%<>%` the compound pipe to work, it's basically an abbreviation of `df<-funs(df)`
兴趣我相信包含的仅用于选择中。至少,这是我从的文档中收集到的。包含。谢谢-是的,我认为这可能是真的,但从文档中不确定。似乎在mutate
中也很有用,尽管下面的grep
解决方案是一个很好的替代方案。看起来这也可以通过stru detect
实现:@QAsena是的,你是对的str_detect
也可以工作,但是grep
更通用一些,因为它可以在不同的正则表达式模式下工作,例如perl