I have function which is an extension of an earlier question here
my function below
library(outliers)
MscoreMax <- 3
scores_na <- function(x, ...) {
not_na <- !is.na(x)
scores <- rep(NA, length(x))
scores[not_na] <- outliers::scores(na.omit(x), ...)
scores
}
mediansFunction <- function(x){
labmedians <- sapply(x[-1], median)
median_of_median <- median(labmedians)
grand_median <- median(as.matrix(x[-1]))
labMscore <- as.vector(round(abs(scores_na(labmedians, "mad")), digits = 2)) #calculate mscore by lab
labMscoreIndex <- which(labMscore > MscoreMax) #get the position in the vector that exceeds Mscoremax
x[-1][labMscoreIndex] <- NA # discharge values above threshold by making NA
return(x)
}
the function has the desired outcome of converting my Mscore values above the threshold to NA. However, I would like to send
As their own variables to the global environment from within the function, but not as a list of items as 3 variables. Can i do this or is better to create a second function which is slightly different that sends the variables to the global environment as a function then use list2env outside the function afterwards to extract the variables as seperate items?
my df below
structure(list(Determination_No = 1:6, `2` = c(0.08, 0.08, 0.08,
0.08, 0.08, 0.08), `3` = c(0.08, 0.07, 0.07, 0.08, 0.07, 0.07
), `4` = c(0.07, 0.08, 0.08, 0.08, 0.07, 0.08), `5` = c(0.08,
0.08, 0.08, 0.08, 0.09, 0.09), `7` = c(0.09, 0.09, 0.11, 0.1,
0.1, 0.1), `8` = c(0.086, 0.087, 0.086, 0.09, 0.083, 0.079),
`10` = c(0.049748274, 0.049748274, 0.066331032, 0.066331032,
0.066331032, 0.049748274), `12` = c(0.086, 0.078, 0.078,
0.077, 0.077, 0.068)), class = "data.frame", row.names = c(NA,
-6L))
It is not recommended to write to global environment from inside the function. If you want to create multiple objects in the global environment return a named list from the function and use list2env.
mediansFunction <- function(x){
labmedians <- sapply(x[-1], median)
median_of_median <- median(labmedians)
grand_median <- median(as.matrix(x[-1]))
labMscore <- as.vector(round(abs(scores_na(labmedians, "mad")), digits = 2)) #calculate mscore by lab
labMscoreIndex <- which(labMscore > MscoreMax) #get the position in the vector that exceeds Mscoremax
x[-1][labMscoreIndex] <- NA # discharge values above threshold by making NA
dplyr::lst(data = x, labmedians, grand_median, labMscore)
}
result <- mediansFunction(df)
list2env(result, .GlobalEnv)
Now you have variables data, labmedians, grand_median and labMscore in the global environment.