根据列表中的值列表对 dataframe 进行子集

Question

I have a dataframe with participants' IDs and observations. I also have a list of the IDs of some participants that need to be removed from this data frame - I want to remove the whole row associated with this participant ID. I have tried the following:

ListtoRemove <- as.list(ListtoRemove)
NewDataFrame <-    
subset(OldDataFrame,OldDataFrame$ParticipantsIDs!=ListtoRemove)

This gives two warnings and does not remove the rows.

1: In `!=.default`(DemographicsALL$subject_label, AllSibs) :
longer object length is not a multiple of shorter object length
2: In is.na(e1) | is.na(e2) :
longer object length is not a multiple of shorter object length
> 

Example of the data:

structure(list(ParticipantsIDs = structure(c(2L, 1L, 3L, 4L, 
6L, 5L), .Label = c("B0002", "B001", "B003", "B004", "L004", 
"M003"), class = "factor"), Age = structure(c(3L, 1L, 4L, 2L, 
5L, 6L), .Label = c("15", "23", "45", "53", "65", "98"), class =      
"factor")), class = "data.frame", row.names = c(NA, 
-6L))

ListtoRemove <- as.list(B004,M003)

Answer 1

NewDataFrame[ !NewDataFrame[,1] %in% unlist(ListtoRemove), ]
#      ParticipantsIDs Age 
# [1,] "B001"          "45"
# [2,] "B0002"         "15"
# [3,] "B003"          "53"
# [4,] "L004"          "98"

I think there might be some mistakes in the code you provided.

1. You use subset in a way that suggests NewDataFrame is a data.frame , but you gave us a matrix . My code works either way, but your subset is going to fail (in a different way than you showed).

2. as.list(B004, M003) is perhaps wrong on up to three points:

   • if those are names of variables, then we do not have them;

   • if those are strings, then we see

     as.list(B004, M003) # Error in as.list(B004, M003): object 'B004' not found

   • as.list(1, 2, 3) only list -ifies the first argument, here 2 and 3 are ignored (so we would have only seen "B004" , not M003 ; perhaps you meant list("B004", "M003") or c("B004", "M003") ?

Instead, I used

ListtoRemove <- list("B004","M003")

Answer 2

If you're using a data frame, an easier-to-read way to do it would be:

# create data.frame
df <- data.frame(ParticipantsIDs = c("B001", "B0002", "B003", "B004", "M003", "L004"), 
                        Age = c("45", "15", "53", "23", "65", "98"))

# vector containing ids to remove
ids.remove <- c('B004','M003')

df

# subset df by rows where ParticipantsIDs are not found in ids.remove
subset(df, !(ParticipantsIDs %in% ids.remove))

Answer 3

Using your data (ListtoRemove slightly edited - I hope this is correct):

data=structure(c("B001", "B0002", "B003", "B004", "M003", "L004", 
"45", "15", "53", "23", "65", "98"), .Dim = c(6L, 2L), .Dimnames = list(
NULL, c("ParticipantsIDs", "Age")))
ListtoRemove <- list("B004","M003")

What about:

data_subset=data[!data[,"ParticipantsIDs"] %in% unlist(ListtoRemove),]

Output:

> data_subset
     ParticipantsIDs Age 
[1,] "B001"          "45"
[2,] "B0002"         "15"
[3,] "B003"          "53"
[4,] "L004"          "98"

Answer 4

I ended up using:

data_subset = data[!data[, "ParticipantsIDs"] %in% unlist(ListtoRemove), ]

and it worked well.