R:更改多列以创建新列 [英] R: mutate over multiple columns to create a new column
问题描述
我正在尝试根据其他列的值创建一个新列.
I'm trying to create a new column based on values of other columns.
这里是一个与我正在研究的数据集相似的数据集.我有三个变量,Test1,Test2,Test3.我正在尝试创建一个新的变量,如果任何测试变量为1DF60,DF61,DF63或DF64,否则为0.
Here is a dataset that is similar to what I'm working on. I have three variables, Test1, Test2, Test3. I am trying to create a new variable that is 1 if any of the Test variables are either DF60, DF61, DF63 or DF64 or 0 otherwise.
Test1<-c("DF64", "DF63", "DF89", "DF30", "DF70")
Test2<-c("DF61", "DF25", "DF00", "DF30", "DF99")
Test3<-c("DF80", "DF63", "DF60", "DF63", "DF70")
Test<-data.frame(Test1, Test2, Test3)
我目前有很多 ifelse 语句,正在寻找可以循环遍历多个Test变量,同时允许查找多个值.
I have many ifelse statements at the moment and am looking for a code that can loop over the multiple Test variables while allowing multiple values to be looked up.
在浏览了一些类似的线程之后,我尝试了mutate_at,但是我认为这不是正确的方法.
After looking through some similar threads, I tried mutate_at but I don't think that is the right way.
Test2<- Test %>%
mutate_at(vars(starts_with("Test")), funs(Test=ifelse("DF60" | "DF61" |
"DF62" | "DF63", 1, 0)))
非常感谢您的帮助!
谢谢!
推荐答案
Test2<- Test %>%
dplyr::select(starts_with("Test"))%>%
mutate_all(function(x){x %in% c("DF60","DF61","DF62","DF63")})%>%
mutate(out = ifelse(rowSums(.)<1,0,1))
评论后调整
如果要保留其他列,则由yutannihilation提出的mutate_at要好得多.然后,问题就变成了在选择列时对rowums进行突变.不知道下一件事是否是最佳实践,但它能奏效(对我之前的问题进行了重新解答:
If you want to keep other columns, mutate_at, as is proposed by yutannihilation, is far better. The problem then becomes doing the rowsums in mutate on a selection of the columns. No idea if the next thing is best practice, but it works (reworked an answer on a previous question of mine: dplyr mutate on column subset (one function on all these columns combined))
library(tidyverse)
library(anomalyDetection)
Test1<-c("DF64", "DF63", "DF89", "DF30", "DF70")
Test2<-c("DF61", "DF25", "DF00", "DF30", "DF99")
Test3<-c("DF80", "DF63", "DF60", "DF63", "DF70")
Test<-data.frame(Test1, Test2, Test3)
Test$ExtraCol<-LETTERS[1:5]
Test2<- Test %>%
mutate_at(vars(starts_with("Test")),funs(bin=.%in% c("DF60","DF61","DF62","DF63")))%>%
split(.,1<10)%>%
map_df(~mutate(.,out=rowSums(.[paste0("Test",1:3,"_bin")])>0))
Test1 Test2 Test3 ExtraCol Test1_bin Test2_bin Test3_bin out
DF64 DF61 DF80 A FALSE TRUE FALSE TRUE
DF63 DF25 DF63 B TRUE FALSE TRUE TRUE
DF89 DF00 DF60 C FALSE FALSE TRUE TRUE
DF30 DF30 DF63 D FALSE FALSE TRUE TRUE
DF70 DF99 DF70 E FALSE FALSE FALSE FALSE
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