I've currently got a very lengthy and repetitive bit of code for data normalisation and inversion ((x-min)/(max-min)*-1)+1) that I want to clean up a bit.
This is a small sample of what it currently looks like:
W3_E1_Norm_New <- W3_E1_Average%>%
mutate(W3_E1_Norm_New = ((W3_E1_zoo-W3_E1_Min)/(W3_E1_Max-W3_E1_Min)*-1)+1)
W3_E2_Norm_New <- W3_E2_Average%>%
mutate(W3_E2_Norm_New = ((W3_E2_zoo-W3_E2_Min)/(W3_E2_Max-W3_E2_Min)*-1)+1)
W3_E3_Norm_New <- W3_E3_Average%>%
mutate(W3_E3_Norm_New = ((W3_E3_zoo-W3_E3_Min)/(W3_E3_Max-W3_E3_Min)*-1)+1)
Each 'W3_E1' refers to a sample ID, and at present each sample ID requires the two lines of code to be written out each time. Ideally I'd like to write a function which can call a character string (Sample_IDs) into the names of each data frame, so something like
a_Norm_New
would return
W3_E1_Norm_New
then
W3_E2_Norm_New
etc.
Is there a way to write a function that could accomplish this?
Many thanks
I don't have your data but this should work. Define a function:
my_fun <- function (x) {
norm_new <- paste0(x,"_Norm_New")
average <- paste0(x,"_Average")
zoo <- paste0(x, "_zoo")
min <- paste0(x, "_Min")
max <- paste0(x, "_Max")
df <- get(average) %>%
mutate(new_norm = ((zoo - min) / (max - min) * - 1) + 1)
assign(df, norm_new)
}
Then run a for loop:
Sample_IDs <- c("W3_E1", "W3_E2", "W3_E3")
for (i in Sample_IDs) {
my_fun(i)
}
With data.table
, it is very easy to write functions that use quoted variable names (see a blog post I wrote on the subject ).
Here, we paste the pattern of your column name everywhere with the sufx
variable:
library(data.table)
normalize <- function(dt, sufx = "W3_E1"){
df <- as.data.table(dt)
df[, (paste0(sufx,"_Norm_New")) := (
(get(paste0(sufx,_zoo)) - get(paste0(sufx,"_Min"))
)/(
get(paste0(sufx,"_Max")) - get(paste0(sufx,"_Min"))
)*-1)+1)
}
Here the code is not easy to read because I wanted to show that this can be done in one line but you can give more readability easily.
In this solution, you use get
to unquote your variable name.
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