如何将多列转换为观察

Question

我有一个这样的数据框:

structure(list(one = structure(1:4, .Label = c("a", "b", "c", 
"d"), class = "factor"), two = c(2, 4, 7, 3), x.1 = c("x1a", 
"x1b", "x1c", "x1d"), x.2 = c("x2a", "x2b", "x2c", "x2d"), x.3 = c("x3a", 
"x3b", "x3c", "x3d"), y.1 = c(NA, "y1b", "y1c", NA), y.2 = c(NA, 
"y2b", "y2c", NA), y.3 = c(NA, "y3b", "y3c", NA)), .Names = c("one", 
"two", "x.1", "x.2", "x.3", "y.1", "y.2", "y.3"), row.names = c(NA, 
-4L), class = "data.frame")

如您所见,每个事件a,b,c和d(变量"one")的观察结果存储为列,其中x和y定义单独的观察值,1,2和3定义变量.变量"two"在这里没有意义.

我喜欢重塑这个数据框,让它整洁,每个观察都有自己的行,每个变量都有自己的列.

最终数据框应如下所示:

structure(list(one = structure(c(1L, 2L, 2L, 3L, 3L, 4L), .Label = c("a", 
"b", "c", "d"), class = "factor"), two = c(2, 4, 2, 7, 5, 3), 
var1 = c("x1a", "x1b", "y1b", "x1c", "y1c", "x1d"), var2 = c("x2a", 
"x2b", "y2b", "x2c", "y2c", "x2d"), var3 = c("x3a", "x3b", 
"y3b", "x3c", "y3c", "x3d")), .Names = c("one", "two", "var1", 
"var2", "var3"), row.names = c(1L, 2L, 5L, 3L, 6L, 4L), class = "data.frame")

我稍微熟悉了重塑包的铸造和熔化功能,但还没有找到一种以智能方式重塑DF的方法.现在,以下提供了我所得到的状态:

df.between <- melt(df.in, id.vars=c("one", "two"))
df.between$variable <- gsub("x.|y.", "", df.between$variable)

现在,"变量"列可以正确识别变量(1,2或3).但是,我无法将其转换为所需的形式,并且由于使用此解决方案似乎对较大的数据集似乎没有用grepl.

很高兴在这里轻轻推进正确的方向.

Answer 1

我们可以使用melt从的开发人员版本data.table,即v1.9.5,它可以处理多个patterns的measure变量.

library(data.table)
melt(setDT(df1), measure=patterns('.1', '.2', '.3'),
      na.rm=TRUE, value.name=paste0('var', 1:3))[, variable:=NULL][order(one)]
#   one two var1 var2 var3
#1:   a   2  x1a  x2a  x3a
#2:   b   4  x1b  x2b  x3b
#3:   b   4  y1b  y2b  y3b
#4:   c   7  x1c  x2c  x3c
#5:   c   7  y1c  y2c  y3c
#6:   d   3  x1d  x2d  x3d

编辑:我们不需要c内部patterns,它也会提供完全匹配(来自@ Jaap的评论).