从现有数据添加新列的ifelse语句错误(ifelse statement error for adding new column from existing data)

我有一个包含两列的数据集，我想将它们组合成一个列。

这是一个例子：

newdata<-data.frame(Tow.y=c(21,"NA","NA","NA",22,"NA","NA"),Tow=c("NA","NA","NA",21,"NA","NA",22)) newdata$Tow.y<-as.numeric(as.character(newdata$Tow.y)) newdata$Tow<-as.numeric(as.character(newdata$Tow)) newdata Tow.y Tow 1 21 NA 2 NA NA 3 NA NA 4 NA 21 5 22 NA 6 NA NA 7 NA 22

我想要的是让另一列从其他两列的每一行获取非NA值，并将所有其他行与NA作为NA。

像这样

newdata Tow.y Tow Station 1 21 NA 21 2 NA NA NA 3 NA NA NA 4 NA 21 21 5 22 NA 22 6 NA NA NA 7 NA 22 22

我以为我可以使用ifelse语句，但它不起作用。只有两列中的一列被添加到新列中。

示例ifelse语句：

newdata$Station<-ifelse(newdata$Tow.y<0 & is.na(newdata$Tow), newdata$Tow.y, ifelse(is.na(newdata$Tow.y) & is.na(newdata$Tow), "NA", ifelse(is.na(newdata$Tow.y) & newdata$Tow<0, newdata$Tow, "check")))

我已经尝试了，如果代码没有运气。

I have a dataset with two columns and I would like to combine them into a single column.

Here is an example:

newdata<-data.frame(Tow.y=c(21,"NA","NA","NA",22,"NA","NA"),Tow=c("NA","NA","NA",21,"NA","NA",22)) newdata$Tow.y<-as.numeric(as.character(newdata$Tow.y)) newdata$Tow<-as.numeric(as.character(newdata$Tow)) newdata Tow.y Tow 1 21 NA 2 NA NA 3 NA NA 4 NA 21 5 22 NA 6 NA NA 7 NA 22

What I would like is to have another column that takes the non NA values from each row for the other two columns and leaves all of the other rows with NAs as NAs.

Like this

newdata Tow.y Tow Station 1 21 NA 21 2 NA NA NA 3 NA NA NA 4 NA 21 21 5 22 NA 22 6 NA NA NA 7 NA 22 22

I thought I could use an ifelse statement, but it is not working. Only one of the two columns is being added to the new column.

Example ifelse statement:

newdata$Station<-ifelse(newdata$Tow.y<0 & is.na(newdata$Tow), newdata$Tow.y, ifelse(is.na(newdata$Tow.y) & is.na(newdata$Tow), "NA", ifelse(is.na(newdata$Tow.y) & newdata$Tow<0, newdata$Tow, "check")))

I have tried and and if with no luck in the code.

最满意答案

我们可以使用coalesce

library(tidyverse) newdata %>% mutate(Station = coalesce(Tow.y, Tow)) # Tow.y Tow Station #1 21 NA 21 #2 NA NA NA #3 NA NA NA #4 NA 21 21 #5 22 NA 22 #6 NA NA NA #7 NA 22 22

We can use coalesce

library(tidyverse) newdata %>% mutate(Station = coalesce(Tow.y, Tow)) # Tow.y Tow Station #1 21 NA 21 #2 NA NA NA #3 NA NA NA #4 NA 21 21 #5 22 NA 22 #6 NA NA NA #7 NA 22 22

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