Is there an equivalent R function to Stata 'order' command?

Question

'order' in R seems like 'sort' in Stata. Here's a dataset for example (only variable names listed):

v1 v2 v3 v4 v5 v6 v7 v8 v9 v10 v11 v12 v13 v14 v15 v16 v17 v18

and here's the output I expect:

v1 v2 v3 v4 v5 v7 v8 v9 v10 v11 v12 v17 v18 v13 v14 v15 v6 v16

In R, I have 2 ways:

data <- data[,c(1:5,7:12,17:18,13:15,6,16)]

OR

names <- c("v1", "v2", "v3", "v4", "v5", "v7", "v8", "v9", "v10", "v11", "v12",  "v17", "v18", "v13", "v14", "v15", "v6", "v16")
data <- data[names]

To get the same output in Stata, I may run 2 lines:

order v17 v18, before(v13)
order v6 v16, last

In the ideal data above, we can know the positions of the variables we want to deal with. But in most real cases, we have variables like 'age' 'gender' with no position indicators and we may have more than 50 variables in one dataset. Then the advantage of 'order' in Stata could be more obvious. We don't need to know the exact place of the variable and just type its name:

order age, after(gender)

Is there a base function in R to deal with this issue or could I get a package? Thanks in advance.

tweetinfo <- data.frame(uid=1:50, mid=2:51, annotations=3:52, bmiddle_pic=4:53, created_at=5:54, favorited=6:55, geo=7:56, in_reply_to_screen_name=8:57, in_reply_to_status_id=9:58, in_reply_to_user_id=10:59, original_pic=11:60, reTweetId=12:61, reUserId=13:62, source=14:63, thumbnail_pic=15:64, truncated=16:65)
noretweetinfo <- data.frame(uid=21:50, mid=22:51, annotations=23:52, bmiddle_pic=24:53, created_at=25:54, favorited=26:55, geo=27:56, in_reply_to_screen_name=28:57, in_reply_to_status_id=29:58, in_reply_to_user_id=30:59, original_pic=31:60, reTweetId=32:61, reUserId=33:62, source=34:63, thumbnail_pic=35:64, truncated=36:65)
retweetinfo <- data.frame(uid=41:50, mid=42:51, annotations=43:52, bmiddle_pic=44:53, created_at=45:54, deleted=46:55, favorited=47:56, geo=48:57, in_reply_to_screen_name=49:58, in_reply_to_status_id=50:59, in_reply_to_user_id=51:60, original_pic=52:61, source=53:62, thumbnail_pic=54:63, truncated=55:64)
tweetinfo$type <- "ti"
noretweetinfo$type <- "nr"
retweetinfo$type <- "rt"
gtinfo <- rbind(tweetinfo, noretweetinfo)
gtinfo$deleted=""
gtinfo <- gtinfo[,c(1:16,18,17)]
retweetinfo <- transform(retweetinfo, reTweetId="", reUserId="")
retweetinfo <- retweetinfo[,c(1:5,7:12,17:18,13:15,6,16)]
gtinfo <- rbind(gtinfo, retweetinfo)
write.table(gtinfo, file="C:/gtinfo.txt", row.names=F, col.names=T, sep="\t", quote=F)
# rm(list=ls(all=T))

Answer 1

Because I'm procrastinating and experimenting with different things, here's a function that I whipped up. Ultimately, it depends on append:

moveme <- function(invec, movecommand) {
  movecommand <- lapply(strsplit(strsplit(movecommand, ";")[[1]], ",|\\s+"), 
                        function(x) x[x != ""])
  movelist <- lapply(movecommand, function(x) {
    Where <- x[which(x %in% c("before", "after", "first", "last")):length(x)]
    ToMove <- setdiff(x, Where)
    list(ToMove, Where)
  })
  myVec <- invec
  for (i in seq_along(movelist)) {
    temp <- setdiff(myVec, movelist[[i]][[1]])
    A <- movelist[[i]][[2]][1]
    if (A %in% c("before", "after")) {
      ba <- movelist[[i]][[2]][2]
      if (A == "before") {
        after <- match(ba, temp)-1
      } else if (A == "after") {
        after <- match(ba, temp)
      }    
    } else if (A == "first") {
      after <- 0
    } else if (A == "last") {
      after <- length(myVec)
    }
    myVec <- append(temp, values = movelist[[i]][[1]], after = after)
  }
  myVec
}

Here's some sample data representing the names of your dataset:

x <- paste0("v", 1:18)

Imagine now that we wanted "v17" and "v18" before "v3", "v6" and "v16" at the end, and "v5" at the beginning:

moveme(x, "v17, v18 before v3; v6, v16 last; v5 first")
#  [1] "v5"  "v1"  "v2"  "v17" "v18" "v3"  "v4"  "v7"  "v8"  "v9"  "v10" "v11" "v12"
# [14] "v13" "v14" "v15" "v6"  "v16"

So, the obvious usage would be, for a data.frame named "df":

df[moveme(names(df), "how you want to move the columns")]

And, for a data.table named "DT" (which, as @mnel points out, would be more memory efficient):

setcolorder(DT, moveme(names(DT), "how you want to move the columns"))

---

Note that compound moves are specified by semicolons.

The recognized moves are:

• before (move the specified columns to before another named column)
• after (move the specified columns to after another named column)
• first (move the specified columns to the first position)
• last (move the specified columns to the last position)

Answer 2

I get your problem. I now have code to offer:

move <- function(data,variable,before) {
  m <- data[variable]
  r <- data[names(data)!=variable]
  i <- match(before,names(data))
  pre <- r[1:i-1]
  post <- r[i:length(names(r))]
  cbind(pre,m,post)
}

# Example.
library(MASS)
data(painters)
str(painters)

# Move 'Expression' variable before 'Drawing' variable.
new <- move(painters,"Expression","Drawing")
View(new)

Answer 3

You could write your own function that does this.

The following will give you the new order for your column names using similar syntax to stata

• where is a named list with 4 possibilities

  • list(last = T)
  • list(first = T)
  • list(before = x) where x is the variable name in question
  • list(after = x) where x is the variable name in question

• sorted = T will sort var_list lexicographically (a combination of alphabetic and sequential from the stata command

The function works on the names only, (once you pass a data.frame object as data, and returns a reordered list of names

eg

stata.order <- function(var_list, where, sorted = F, data) {
    all_names = names(data)
    # are all the variable names in
    check <- var_list %in% all_names
    if (any(!check)) {
        stop("Not all variables in var_list exist within  data")
    }
    if (names(where) == "before") {
        if (!(where %in% all_names)) {
            stop("before variable not in the data set")
        }
    }
    if (names(where) == "after") {
        if (!(where %in% all_names)) {
            stop("after variable not in the data set")
        }
    }

    if (sorted) {
        var_list <- sort(var_list)
    }
    where_in <- which(all_names %in% var_list)
    full_list <- seq_along(data)
    others <- full_list[-c(where_in)]

    .nwhere <- names(where)
    if (!(.nwhere %in% c("last", "first", "before", "after"))) {
        stop("where must be a list of a named element first, last, before or after")
    }

    do_what <- switch(names(where), last = length(others), first = 0, before = which(all_names[others] == 
        where) - 1, after = which(all_names[others] == where))

    new_order <- append(others, where_in, do_what)
    return(all_names[new_order])
}

tmp <- as.data.frame(matrix(1:100, ncol = 10))

stata.order(var_list = c("V2", "V5"), where = list(last = T), data = tmp)

##  [1] "V1"  "V3"  "V4"  "V6"  "V7"  "V8"  "V9"  "V10" "V2"  "V5" 

stata.order(var_list = c("V2", "V5"), where = list(first = T), data = tmp)

##  [1] "V2"  "V5"  "V1"  "V3"  "V4"  "V6"  "V7"  "V8"  "V9"  "V10"

stata.order(var_list = c("V2", "V5"), where = list(before = "V6"), data = tmp)

##  [1] "V1"  "V3"  "V4"  "V2"  "V5"  "V6"  "V7"  "V8"  "V9"  "V10"

stata.order(var_list = c("V2", "V5"), where = list(after = "V4"), data = tmp)

##  [1] "V1"  "V3"  "V4"  "V2"  "V5"  "V6"  "V7"  "V8"  "V9"  "V10"

# throws an error
stata.order(var_list = c("V2", "V5"), where = list(before = "v11"), data = tmp)

## Error: before variable not in the data set

if you want to do the reordering memory-efficiently (by reference, without copying) use data.table

DT <- data.table(tmp)
# sets by reference, no copying
setcolorder(DT, stata.order(var_list = c("V2", "V5"), where = list(after = "V4"), 
    data = DT))

DT

##     V1 V3 V4 V2 V5 V6 V7 V8 V9 V10
##  1:  1 21 31 11 41 51 61 71 81  91
##  2:  2 22 32 12 42 52 62 72 82  92
##  3:  3 23 33 13 43 53 63 73 83  93
##  4:  4 24 34 14 44 54 64 74 84  94
##  5:  5 25 35 15 45 55 65 75 85  95
##  6:  6 26 36 16 46 56 66 76 86  96
##  7:  7 27 37 17 47 57 67 77 87  97
##  8:  8 28 38 18 48 58 68 78 88  98
##  9:  9 29 39 19 49 59 69 79 89  99
## 10: 10 30 40 20 50 60 70 80 90 100

Answer 4

It is very unclear what you would like to do, but your first sentence makes me assume you would like to sort dataset.

Actually, there is a built-in order function, which returns the indices of the ordered sequence. Are you searching this?

> x <- c(3,2,1)

> order(x)
[1] 3 2 1

> x[order(x)]
[1] 1 2 3

Answer 5

This should give you the same file:

#snip
gtinfo <- rbind(tweetinfo, noretweetinfo)
gtinfo$deleted=""
retweetinfo <- transform(retweetinfo, reTweetId="", reUserId="")
gtinfo <- rbind(gtinfo, retweetinfo)
gtinfo <-gtinfo[,c(1:16,18,17)]
#snip

It is possible to implement a function like Strata's order function in R, but I don't think there is much demand for that.

Answer 6

The package dplyr and the function dplyr::relocate, a new verb introduced in dplyr 1.0.0, does exactly what you are looking for.

library(dplyr)

data %>% relocate(v17, v18, .before = v13)

data %>% relocate(v6, v16, .after = last_col())

data %>% relocate(age, .after = gender)