当两个列满足R中的某些条件时创建一个新列
当两个列满足R中的某些条件时创建一个新列
提问于 2022-01-02 08:24:27
我的数据如下：
country supporter1 supporter2 supporter3 supporter4 supporter5
USA Albania Germany USA NA NA
France USA France NA NA NA
UK UK Chile Peru NA NA
Germany USA Iran Mexico India Pakistan
USA China Spain NA NA NA
Cuba Cuba UK Germany South Korea NA
China Russia NA NA NA NA我想要做的是创建一个新的变量，当国家列和剩下的一个支持者列(支持者1、支持者2、支持者3、支持者4和支持者5)相同时(例如，法国和supporter2法国是相同的)。在这种情况下，新变量应该取1，0否则。
我希望有这样的：
country supporter1 supporter2 supporter3 supporter4 supporter5 new variable
USA Albania Germany USA NA NA 1
France USA France NA NA NA 1
UK UK Chile Peru NA NA 1
Germany USA Iran Mexico India Pakistan 0
USA China Spain NA NA NA 0
Cuba Cuba UK Germany South Korea NA 1
China Russia NA NA NA NA 0回答 3
Stack Overflow用户
回答已采纳
发布于 2022-01-02 09:03:41
只使用if_any更新dplyr解决方案
library(dplyr)
df %>%
rowwise() %>%
mutate(new_var = as.integer(as.logical(if_any(starts_with("supporter"), ~ . %in% country)))) country supporter1 supporter2 supporter3 supporter4 supporter5 new_var
<chr> <chr> <chr> <chr> <chr> <chr> <int>
1 USA Albania Germany USA NA NA 1
2 France USA France NA NA NA 1
3 UK UK Chile Peru NA NA 1
4 Germany USA Iran Mexico India Pakistan 0
5 USA China Spain NA NA NA 0
6 Cuba Cuba UK Germany South Korea NA 1
7 China Russia NA NA NA NA 0第一个答案:也是正确的:这里有一个可能的解决方案：
如果country是rowwise
- check，那么
- 在cols
supporter1tosupporter5中计算，如果所有的新列都是一个，并且使用ifelse语句，则取1或0
library(dplyr)
library(stringr)
library(tidyr)
df %>%
rowwise() %>%
mutate(across(supporter1:supporter5, ~ifelse(. %in% country, 1,0), .names = "new_{col}")) %>%
unite(New_Col, starts_with('new'), na.rm = TRUE, sep = ' ') %>%
mutate(New_Col = ifelse(str_detect(New_Col, "1"), 1,0)) country supporter1 supporter2 supporter3 supporter4 supporter5 New_Col
<chr> <chr> <chr> <chr> <chr> <chr> <dbl>
1 USA Albania Germany USA NA NA 1
2 France USA France NA NA NA 1
3 UK UK Chile Peru NA NA 1
4 Germany USA Iran Mexico India Pakistan 0
5 USA China Spain NA NA NA 0
6 Cuba Cuba UK Germany South Korea NA 1
7 China Russia NA NA NA NA 0Stack Overflow用户
发布于 2022-01-02 09:16:36
这是一个基本的R解。
首先，mapply检查suporter*和country的相等性。NA被认为是返回FALSE，然后as.integer/rowSums将至少一个TRUE的行转换为1，否则为0。
eq <- mapply(\(x, y){x == y & !is.na(x)}, df1[-1], df1[1])
as.integer(rowSums(eq) != 0)
#[1] 1 1 1 0 0 1 0
df1$new_variable <- as.integer(rowSums(eq) != 0)数据
df1 <- read.table(text = "
country supporter1 supporter2 supporter3 supporter4 supporter5
USA Albania Germany USA NA NA
France USA France NA NA NA
UK UK Chile Peru NA NA
Germany USA Iran Mexico India Pakistan
USA China Spain NA NA NA
Cuba Cuba UK Germany 'South Korea' NA
China Russia NA NA NA NA
", header = TRUE)Stack Overflow用户
发布于 2022-01-02 09:12:40
另一种解决方案是检查每一行中是否存在country：
df <- data.frame(country=c("USA","France","UK","Germany","USA","Cuba","China"),
supporter1=c("Albania","USA","UK","USA","China","Cuba","Russia"),
supporter2=c("Germany","France","Chile","Iran","Spain","UK","NA"),
supporter3=c("USA","NA","Peru","Mexico","NA","Germany","NA"),
supporter4=c("NA","NA","NA","India","NA","South Korea","NA"),
supporter5=c("NA","NA","NA","Pakistan","NA","NA","NA"))这将使：
df$new <- sapply(seq(1,nrow(df)), function(x) ifelse(df$country[x] %in% df[x,2:6],1,0))
> df$new
[1] 1 1 1 0 0 1 0页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/70554560
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