英文:
How to pass different lines of code based on multiple arguments in R?
问题
由于编辑太多而开启新会话。
我有一个数据框，看起来像这样：
df <- data.frame(ID = c("A","A","A","B","B","B","C","C","C"),value = c(1,2,3,1,2,3,1,2,3))
我想要使用条件语句 if else 传递类似以下内容，但它不起作用，因为条件的长度大于1：
if (df$ID == "A" | df$ID == "B") {df$nat[df$value %in% c(1,2)] <- 1df$hrv[df$value %in% c(3)] <- 1} else {df$nat[df$value %in% c(1)] <- 1df$hrv[df$value %in% c(2,3)] <- 1}
我知道我可以拆分数据集并分别进行计算，然后再将它们绑定在一起，但是否有更简单的方法，类似我上面提到的？
所以最终我想要的是这样的：
df <- data.frame(ID = c("A","A","A","B","B","B","C","C","C"),value = c(1,2,3,1,2,3,1,2,3),nat = c(1,1,NA,1,1,NA,1,NA,NA),hrv = c(NA,NA,1,NA,NA,1,NA,1,1))
英文:
Opening up a new session due to too many edits.
I have a dataframe that looks like this:
df <- data.frame(ID = c("A","A","A","B","B","B","C","C","C"),value = c(1,2,3,1,2,3,1,2,3))
And I would like to pass something like this using an if else statement, but it does not work because the condition has length >1:
if (df$ID =="A"| df$ID=="B"){df$nat[df$value %in% c(1,2)] <- 1df$hrv[df$value %in% c(3)] <- 1}else {df$nat[df$value %in% c(1)] <- 1df$hrv[df$value %in% c(2,3)] <- 1}
I know I could split the dataset and do seperate calcululations and bind it together again, but is there a simpler approach, something like I suggested above?
So I would end up with something like this:
df <- data.frame(ID = c("A","A","A","B","B","B","C","C","C"),value = c(1,2,3,1,2,3,1,2,3),nat = c(1,1,NA,1,1,NA,1,NA,NA),hrv = c(NA,NA,1,NA,NA,1,NA,1,1))
答案1
得分: 2
你可以使用ifelse、if_else或case_when语句的变体。以下是使用dplyr中的case_when的示例。
library(dplyr)df %>%mutate(isAB = ID %in% c("A", "B"),nat = case_when((isAB & value %in% c(1, 2))|(!isAB & value %in% 1) ~ 1),hrv = case_when((isAB & value %in% 3)|(!isAB & value %in% c(2, 3)) ~ 1))# ID value isAB nat hrv#1 A 1 TRUE 1 NA#2 A 2 TRUE 1 NA#3 A 3 TRUE NA 1#4 B 1 TRUE 1 NA#5 B 2 TRUE 1 NA#6 B 3 TRUE NA 1#7 C 1 FALSE 1 NA#8 C 2 FALSE NA 1#9 C 3 FALSE NA 1
isAB是一个临时列，用于避免多次执行ID %in% c("A", "B")。如果不需要，你可以在最后删除它。
我们使用了OR (|) 来组合两个条件。
英文:
You can use variations of ifelse, if_else or case_when statements. Here is one using case_when in dplyr.
library(dplyr)df %>%mutate(isAB = ID %in% c("A", "B"),nat = case_when((isAB & value %in% c(1, 2))|(!isAB & value %in% 1) ~ 1),hrv = case_when((isAB & value %in% 3)|(!isAB & value %in% c(2, 3)) ~ 1))# ID value isAB nat hrv#1 A 1 TRUE 1 NA#2 A 2 TRUE 1 NA#3 A 3 TRUE NA 1#4 B 1 TRUE 1 NA#5 B 2 TRUE 1 NA#6 B 3 TRUE NA 1#7 C 1 FALSE 1 NA#8 C 2 FALSE NA 1#9 C 3 FALSE NA 1
isAB is a temporary column created to avoid doing ID %in% c("A", "B") multiple times. You can drop it at the end if it is not needed.
We have combined two conditions using OR (|).
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