问题
I had a dataframe where I recoded several columns so that 999 was set to NA
dfB <-dfA %>%
mutate(adhere = if_else(adhere==999, as.numeric(NA), adhere)) %>%
mutate(engage = if_else(engage==999, as.numeric(NA), engage)) %>%
mutate(quality = if_else(quality==999, as.numeric(NA), quality)) %>%
mutate(undrstnd = if_else(undrstnd==999, as.numeric(NA), undrstnd)) %>%
mutate(sesspart = if_else(sesspart==999, as.numeric(NA), sesspart)) %>%
mutate(attended = if_else(attended>=9, as.integer(NA), attended))
I want to use mutate_at() and a range of columns and recode() instead of if_else(), but I am stuck on how to give it the condition. I think something like 999
= NA based on some mutate_all examples -- but I also need the NA to match the type of .x and I am unsure how to get it to be type sensitive
I tried:
y <- data.frame(y1=c(1,2,999,3,4), y2=c(1L, 2L, 999L, 3L, 4L), y3=c(T,T,F,F,T))
z <- y %>%
mutate_at( vars(y1:y2), funs(recode(.,`999` = as.numeric(NA))))
But I get a warning "Unreplaced values treated as NA as .x is not compatible. Please specify replacements exhaustively or supply .default " and I can see that it worded for the numeric column, but not for the integer column y2"
> z
y1 y2 y3
1 1 NA TRUE
2 2 NA TRUE
3 NA NA FALSE
4 3 NA FALSE
5 4 NA TRUE
回答1:
I'm having trouble understanding exactly what you want to accomplish, so let me know if this isn't quite it.
library(tidyverse)
y <- data.frame(y1=c(1,2,999,3,4), y2=c(1L, 2L, 999L, 3L, 4L), y3=c(T,T,F,F,T))
y
#> y1 y2 y3
#> 1 1 1 TRUE
#> 2 2 2 TRUE
#> 3 999 999 FALSE
#> 4 3 3 FALSE
#> 5 4 4 TRUE
z <- y %>%
mutate_at(.vars = vars(y1:y2),
.funs = ~ ifelse(. == 999, NA, .))
z
#> y1 y2 y3
#> 1 1 1 TRUE
#> 2 2 2 TRUE
#> 3 NA NA FALSE
#> 4 3 3 FALSE
#> 5 4 4 TRUE
回答2:
I think it is related the column type. I added mutate_if
to convert all integer columns to numeric, and then set the recode value to be NA_real_
. It seems working.
library(dplyr)
y <- data.frame(y1=c(1,2,999,3,4), y2=c(1L, 2L, 999L, 3L, 4L), y3=c(T,T,F,F,T))
z <- y %>%
mutate_if(is.integer, as.numeric) %>%
mutate_at(vars(y1:y2), funs(recode(.,`999` = NA_real_)))
z
# y1 y2 y3
# 1 1 1 TRUE
# 2 2 2 TRUE
# 3 NA NA FALSE
# 4 3 3 FALSE
# 5 4 4 TRUE
回答3:
Now that funs
has been depreciated in dplyr, here's the new way to go:
z <- y %>%
mutate_if(is.integer, as.numeric) %>%
mutate_at(vars(y1:y2), list(~recode(.,`999` = NA_real_)))
Replace funs
with list
and insert a ~
before recode
.
来源:https://stackoverflow.com/questions/47521920/recode-multiple-columns-using-dplyr