本文介绍了是否有等同于Stata;Order命令的R函数?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
R中的"ORDER"与STATA中的"SORT"类似。下面是一个数据集(仅列出变量名):
v1 v2 v3 v4 v5 v6 v7 v8 v9 v10 v11 v12 v13 v14 v15 v16 v17 v18
以下是我预期的输出:
v1 v2 v3 v4 v7 v8 v9 v10 v11 v12 v18 v13 v14 v15 v6 v16
在R中,我有两种方式:
data <- data[,c(1:5,7:12,17:18,13:15,6,16)]
或
names <- c("v1", "v2", "v3", "v4", "v5", "v7", "v8", "v9", "v10", "v11", "v12", "v17", "v18", "v13", "v14", "v15", "v6", "v16")
data <- data[names]
要在Stata中获得相同的输出,我可能会运行两行:
order v17 v18, before(v13)
order v6 v16, last
在上面的理想数据中,我们可以知道要处理的变量的位置。但在大多数实际情况下,我们有像‘年龄’、‘性别’这样的变量,没有位置指标,而且一个数据集中可能有超过50个变量。那样的话,Stata中的"秩序"优势就会更加明显。我们不需要知道变量的确切位置,只需键入其名称:
order age, after(gender)
R中是否有处理此问题的基本函数,或者我可以得到一个包吗?提前谢谢。
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=" ", quote=F)
# rm(list=ls(all=T))
推荐答案
因为我在拖延时间并尝试不同的东西,所以我创建了一个函数。最终,它取决于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
}
以下是表示数据集名称的一些示例数据:
x <- paste0("v", 1:18)
现在想象一下,我们希望"v17"和"v18"在"v3"之前,"v6"和"v16"在末尾,"v5"在开头:
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"
因此,对于名为"df"的data.frame
,明显的用法是:
df[moveme(names(df), "how you want to move the columns")]
并且,对于名为"dt"的data.table
(正如@MNEL指出的那样,这将更有效地利用内存):
setcolorder(DT, moveme(names(DT), "how you want to move the columns"))
请注意,复合移动由分号指定。
可识别的动作包括:
before
(将指定列移到另一个命名列之前)after
(将指定列移动到另一个命名列之后)first
(将指定的列移动到第一个位置)last
(将指定的列移动到最后位置)
这篇关于是否有等同于Stata;Order命令的R函数?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!