Replacing specific values with NA in a dataframe

Question

I am trying to replace all * values in my dataset with NA but I get errors. Here is what I do:

strt = as.POSIXct("2021-01-08") end = as.POSIXct("2021-01-12") time = seq.POSIXt(strt, end, by = "day") x = c(1,2,3,'*','*') y = c('*',2,3,4,5) df = data.frame(time, x, y) df[df == '*'] = NA #This doesn't work df[df[-1] == '*'] = NA #Same as above df[df[,-1] == '*'] = NA #Same as above

There is a problem with POSIXct variable (time). The error is:

Error in as.POSIXlt.character(x, tz, ...) : character string is not in a standard unambiguous format

I tried disregarding time variable by writing df[df[-1] == '*'] but then I get another error:

Error in [<-.data.frame(*tmp*, df[, -1] == "", value = NA) : unsupported matrix index in replacement*

So now I'm stuck. Does anyone know what's the problem here and why R can't run consistently with all types of variables?!

Duck · Accepted Answer · 2021-01-12 17:33:43Z

Try this. The issue is because of the date variable. Using dplyr you can have:

library(dplyr) #Code new <- df %>% mutate(across(everything(),~as.character(.))) %>% replace(.=='*',NA) %>% mutate(time=as.Date(time))

Output:

 time x y 1 2021-01-08 1 <NA> 2 2021-01-09 2 2 3 2021-01-10 3 3 4 2021-01-11 <NA> 4 5 2021-01-12 <NA> 5

The base R way:

#Base R df[-1][df[-1]=='*']<-NA

Output:

 time x y 1 2021-01-08 1 <NA> 2 2021-01-09 2 2 3 2021-01-10 3 3 4 2021-01-11 <NA> 4 5 2021-01-12 <NA> 5

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