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R,dplyr,基于R中的一个条件列有条件地更改多列中的值

[英]R, dplyr, Conditionally change values in multiple columns based on one conditional column in R

Given the following data frame: 给定以下数据框:

df <- data.frame("a" = 1:5, "b" = 2:6, "c" = 3:7, "d" = c(NA,1,1,0,0))

How can I change values in columns a , b , and c to NA if values in column d are either NA or 0 ? 如果d列的值为NA0 ,如何将abca值更改为NA I can get it to work easily for individual columns, eg, df[,3][df$d==0|is.na(df$d)] <- NA , but I'm having trouble getting something to work across multiple columns. 我可以轻松地使它适用于各个列,例如df[,3][df$d==0|is.na(df$d)] <- NA ,但是我很难使某些东西可以工作多列。 I'd very much appreciate solutions in base R or dplyr . 我非常感谢R或dplyr基中的解决方案。 Thanks 谢谢

Do you mean this? 你是这个意思吗

cols <- c("a", "b", "c")
df[is.na(df$d) | df$d == 0, cols] <- NA
df
#   a  b  c  d
#1 NA NA NA NA
#2  2  3  4  1
#3  3  4  5  1
#4 NA NA NA  0
#5 NA NA NA  0

Or in dplyr 或在dplyr

library(dplyr)
df %>% mutate_at(vars(a:c), funs(ifelse(is.na(d) | d == 0, NA, .)))
#   a  b  c  d
#1 NA NA NA NA
#2  2  3  4  1
#3  3  4  5  1
#4 NA NA NA  0
#5 NA NA NA  0

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