按名称删除数据框列

#1 楼

DF <- data.frame(
  x=1:10,
  y=10:1,
  z=rep(5,10),
  a=11:20
)
drops <- c("x","z")
DF[ , !(names(DF) %in% drops)]

keeps <- c("y", "a")
DF[keeps]

keeps <- "y"
DF[ , keeps, drop = FALSE]

#2 楼

df <- data.frame(a = 1:10, b = 2:11, c = 3:12)
df <- subset(df, select = c(a, c))

#3 楼

within(df, rm(x))

within(df, rm(x, y))

dt[, x := NULL]   # Deletes column x by reference instantly.

dt[, !"x"]   # Selects all but x into a new data.table.

dt[, c("x","y") := NULL]

dt[, !c("x", "y")]

#4 楼

df[, !(colnames(df) %in% c("x","bar","foo"))]

#5 楼

dat <- mtcars
colnames(dat)
# [1] "mpg"  "cyl"  "disp" "hp"   "drat" "wt"   "qsec" "vs"   "am"   "gear"
# [11] "carb"
dat[,c("mpg","cyl","wt")] <- list(NULL)
colnames(dat)
# [1] "disp" "hp"   "drat" "qsec" "vs"   "am"   "gear" "carb"

#6 楼

library(data.table)

df <- data.frame(a=1:10, b=1:10, c=1:10, d=1:10)
DT <- data.table(df)
# or more simply  DT <- data.table(a=1:10, b=1:10, c=1:10, d=1:10) #

DT[, c('a','b') := NULL]

del <- c('a','b')
DT <- data.table(a=1:10, b=1:10, c=1:10, d=1:10)
DT[, (del) := NULL]
DT <-  <- data.table(a=1:10, b=1:10, c=1:10, d=1:10)
DT[, {del} := NULL]
# force or `c` would also work.   

df <- data.frame(a=1:10, b=1:10, c=1:10, d=1:10)
DT <- data.table(df)

# drop `a` from df (no copying involved)

set(df, j = 'a', value = NULL)
# drop `b` from DT (no copying involved)
set(DT, j = 'b', value = NULL)

#7 楼

dfrm2 <- dfrm[ , -grep("\.B$", names(dfrm)) ]

DF <- DF[, -grep( paste("^",drops,"$", sep="", collapse="|"), names(DF) )]

#8 楼

library(dplyr)
df <- data.frame(var1 = rnorm(5), var2 = rnorm(5), var3 = rnorm (5), 
                 var4 = rnorm(5), char1 = rnorm(5), char2 = rnorm(5))
df
#        var2      char1        var4       var3       char2       var1
#1 -0.4629512 -0.3595079 -0.04763169  0.6398194  0.70996579 0.75879754
#2  0.5489027  0.1572841 -1.65313658 -1.3228020 -1.42785427 0.31168919
#3 -0.1707694 -0.9036500  0.47583030 -0.6636173  0.02116066 0.03983268
df1 <- df %>% select(-starts_with("char"))
df1
#        var2        var4       var3       var1
#1 -0.4629512 -0.04763169  0.6398194 0.75879754
#2  0.5489027 -1.65313658 -1.3228020 0.31168919
#3 -0.1707694  0.47583030 -0.6636173 0.03983268

df2 <- df1 %>% select(-c(var2:var3) )  
df2
#        var1
#1 0.75879754
#2 0.31168919
#3 0.03983268

#9 楼

undesired <- c('mpg', 'cyl', 'hp')

mtcars <- mtcars %>%
  select(-one_of(undesired))

#10 楼

df <- df[, setdiff(names(df), c("a", "c"))]

df <- df[, grep('^(a|c)$', names(df), invert=TRUE)]

#11 楼

DF <- data.frame(
  x=1:10,
  y=10:1,
  z=rep(5,10),
  a=11:20
)
DF

    x  y z  a
1   1 10 5 11
2   2  9 5 12
3   3  8 5 13
4   4  7 5 14
5   5  6 5 15
6   6  5 5 16
7   7  4 5 17
8   8  3 5 18
9   9  2 5 19
10 10  1 5 20

DF[c("a","x")] <- list(NULL)

        y z
    1  10 5
    2   9 5
    3   8 5
    4   7 5
    5   6 5
    6   5 5
    7   4 5
    8   3 5    
    9   2 5
    10  1 5

#12 楼

df <- data.frame(x=1, y=2)

subset(df, select=-y)

df[,-2]

#13 楼

#df[ -c(1,3:6, 12) ]  # original
df.cut <- df %>% select(-col.to.drop.1, -col.to.drop.2, ..., -col.to.drop.6)  # with dplyr::select()

#14 楼

df <- data.frame(a=1:10, b=1:10, c=1:10, d=1:10)

# return everything except a and c
df <- df[,-match(c("a","c"),names(df))]
df

#15 楼

BBmisc::dropNamed(df, "x")

#16 楼

df[,-which(names(df) == "COLUMN_NAME")]

#17 楼

library(dplyr)
starwars %>% 
  select(-(name:mass)) %>%        # the range of columns from 'name' to 'mass'
  select(-contains('color')) %>%  # any column name that contains 'color'
  select(-starts_with('bi')) %>%  # any column name that starts with 'bi'
  select(-ends_with('er')) %>%    # any column name that ends with 'er'
  select(-matches('^f.+s$')) %>%  # any column name matching the regex pattern
  select_if(~!is.list(.)) %>%     # not by column name but by data type
  head(2)

# A tibble: 2 x 2
homeworld species
  <chr>     <chr>  
1 Tatooine  Human  
2 Tatooine  Droid 

starwars %>% 
  select_if(!names(.) %in% c('height', 'mass', 'bad_column'))

#18 楼

remove_features <- function(df, features) {
  rem_vec <- unlist(strsplit(features, ', '))
  res <- df[,!(names(df) %in% rem_vec)]
  return(res)
}

remove_features(iris, "Sepal.Length, Petal.Width")

#19 楼

DF <- data.frame(one=c('a','b'), two=c('c', 'd'), three=c('e', 'f'), four=c('g', 'h'))
DF
#  one two three four
#1   a   d     f    i
#2   b   e     g    j

DF[which(names(DF) %in% c('two','three')) *-1]
#  one four
#1   a    g
#2   b    h

#20 楼

getData <- function() {
  n <- 1e7
  set.seed(7)
  data.frame(a = runif(n), b = runif(n), c = runif(n), d = runif(n))
}

DF <- getData()
tt <- sum(.Internal(gc(FALSE, TRUE, TRUE))[13:14])
DF <- DF[setdiff(names(DF), c("a", "c"))] ##
#DF <- DF[!(names(DF) %in% c("a", "c"))] #Alternative
#DF <- DF[-match(c("a","c"),names(DF))]  #Alternative
sum(.Internal(gc(FALSE, FALSE, TRUE))[13:14]) - tt
#0.1 MB are used

DF <- getData()
tt <- sum(.Internal(gc(FALSE, TRUE, TRUE))[13:14])
DF <- subset(DF, select = -c(a, c)) ##
sum(.Internal(gc(FALSE, FALSE, TRUE))[13:14]) - tt
#357 MB are used

DF <- getData()
tt <- sum(.Internal(gc(FALSE, TRUE, TRUE))[13:14])
DF <- within(DF, rm(a, c)) ##
sum(.Internal(gc(FALSE, FALSE, TRUE))[13:14]) - tt
#0.1 MB are used

DF <- getData()
tt <- sum(.Internal(gc(FALSE, TRUE, TRUE))[13:14])
DF[c("a", "c")]  <- NULL ##
sum(.Internal(gc(FALSE, FALSE, TRUE))[13:14]) - tt
#0.1 MB are used