Let's say, I have the following my_dt datatable:

Also I have the following named list (my_list):

> my_list
$particles   
[1] "neutrons"

$station   
[1] NA

$energy      
[1] "spectrum"

$area   
[1] "geography"

$gamma   
[1] NA 

The values of this list correspond to the columns names from my dataset (if they exist, if they are absent - NA). Based on my dataset and this list, I need to check which columns exist in my_dt and rename them (based on my_list names), and for NA values - I need to create columns filled with NAs.

So, I want to obtain the following dataset:

>final_dt

I try to implement this using apply family functions, but at the moment I can't obtain exactly what I want.
So, I would be grateful for any help!

CodePudding user response：

I wrote a simple code that should do the job for you:

l = list(c = 'cc', a = 'aa', b = NA) # replace this with your my_list

dt = data.frame(aa = 1:3, cc = 2:4) # replace this with my_dt 

dtl = data.frame(l)

names(dt) = names(l)[na.omit(match(l, names(dt)))]

m = merge(dt, dtl[!is.element(names(dtl), names(dt))])

CodePudding user response：

This may not meet your needs, but since I had come up with this separately thought I would share just in case. You can use setnames to rename the columns based on my_list. After that, add in the missing column names with values of NA. Finally, you can use setcolorder to reorder based on your list if desired.

library(data.table)

my_vec <- unlist(my_list)
setnames(my_dt, names(my_vec[match(names(my_dt), my_vec)]))
my_dt[, (setdiff(names(my_vec), names(my_dt))) := NA]
setcolorder(my_dt, names(my_vec))
my_dt

Output

   particles station energy area gamma
1:      2.30      NA   -1.2 KIEL    NA
2:      2.54      NA   -1.6 KIEL    NA
3:      2.56      NA   -0.9 JUNG    NA
4:      2.31      NA   -0.3  ANT    NA

CodePudding user response：

data.table using lapply

library(data.table)

setDT(my_dt)
setDT(my_list)

final_dt <- setnames( my_list[, lapply( .SD, function(x){
  if( x %in% colnames(my_dt)){ my_dt[,x,with=F] }else{ NA } } ) ],
  names(my_list) )

final_dt
   particles station energy area gamma
1:      2.30      NA   -1.2 KIEL    NA
2:      2.54      NA   -1.6 KIEL    NA
3:      2.56      NA   -0.9 JUNG    NA
4:      2.31      NA   -0.3  ANT    NA

base R using sapply

setDF(my_dt)
setDF(my_list)

data.frame( sapply( my_list, function(x) if(!is.na(x)){ my_dt[,x] }else{ NA } ) )
  particles station energy area gamma
1      2.30      NA   -1.2 KIEL    NA
2      2.54      NA   -1.6 KIEL    NA
3      2.56      NA   -0.9 JUNG    NA
4      2.31      NA   -0.3  ANT    NA

Data

my_dt <- structure(list(neutrons = c(2.3, 2.54, 2.56, 2.31), spectrum = c(-1.2, 
-1.6, -0.9, -0.3), geography = c("KIEL", "KIEL", "JUNG", "ANT"
)), class = "data.frame", row.names = c(NA, -4L))

my_list <- list(particles = "neutrons", station = NA, energy = "spectrum", 
    area = "geography", gamma = NA)