Remove last column in list of tables-CodePudding

I have a list if tables:

tables <- lapply(file_list, read.csv, header = F, sep="\t")

I would like to remove the column V25, for those tables that have this column Tried this (which does not work):

for (i in 1:length(file_list)) {
    as.data.frame(tables[[i]])$V25 <- NULL
}

CodePudding user response：

Something like: lapply(list(mtcars, iris), \(x) x[,-length(x)]) ?

So in your example, you could do:

lapply(lapply(file_list, read.csv, header = F, sep="\t"),\(x) x[,-length(x)])

CodePudding user response：

You may setdiff to a vector of names to be excluded.

lapply(list.files('./foo1/', full.names=TRUE), read.csv) |>
  {\(.) lapply(., \(.) .[setdiff(names(.), c("V25"))])}()
# [[1]]
#   X1 X2 X3 X4
# 1  1  4  7 10
# 2  2  5  8 11
# 3  3  6  9 12
# 
# [[2]]
#   X1 X2 X3
# 1  1  4  7
# 2  2  5  8
# 3  3  6  9
# 
# [[3]]
#   X1 X2 X3 X4
# 1  1  4  7 10
# 2  2  5  8 11
# 3  3  6  9 12
# 
# [[4]]
#   X1 X2 X3
# 1  1  4  7
# 2  2  5  8
# 3  3  6  9
# 
# [[5]]
#   X1 X2 X3 X4
# 1  1  4  7 10
# 2  2  5  8 11
# 3  3  6  9 12

Note: R >= 4.1 used.

Data:

df1 <- df2 <- data.frame(matrix(1:12, 3, 4))
names(df2)[4] <- 'V25'
Map(\(x, y) write.csv(x, file=y, row.names=F), list(df1, df2, df1, df2, df1), sprintf('./foo1/%s.csv', paste0('tb', 1:5)))

df1
#   X1 X2 X3 X4
# 1  1  4  7 10
# 2  2  5  8 11
# 3  3  6  9 12

df2
#   X1 X2 X3 V25
# 1  1  4  7  10
# 2  2  5  8  11
# 3  3  6  9  12