Replace values across time series columns based on another column-CodePudding

My question is similar to another one: R replace specific value in many columns across dataframe

However I need to replace values based on a vector from another column rather than with NA or a constant.

Can you please help?

#there are many more yrs in the data set
yr1<-c("1","missing")
yr2<-c("3","4")
right<-c("2","3")
df<-data.frame(yr1,yr2,right)

df<-df %>%
  mutate(
      across(starts_with('yr'), ~replace(.x, ~.x=="missing", right) ))

Where right is another column where I want to "lookup" the value to replace the "missing" value.

CodePudding user response：

Using ifelse instead of replace should solve your problem.

library(dplyr)

df %>%
  mutate(across(starts_with('yr'), ~ifelse(.x=="missing", right, .x)))

#  yr1 yr2 right
#1   1   3     2
#2   3   4     3

In general, I would suggest to use replace only when you have a fixed (constant) value to replace for all other things using ifelse is better.

CodePudding user response：

base R option:

cols <- grep("^yr\\d $", names(df))
df[cols][df[cols] == "missing"] <- df[df[cols] == "missing", "right"]

Output:

  yr1 yr2 right
1   1   3     2
2   3   4     3