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我想使用人口普查的县邻接数据，但我一直坚持把它变成一个好的形式。数据分为四列：第一县、第一代码、第二县、第二代码。第一个县列不重复，而是按照我现在读到的方式取值“”：

                     c1   cd1                    c2   cd2
1   Alamance County, NC 37001   Alamance County, NC 37001
2                          NA    Caswell County, NC 37033
3                          NA    Chatham County, NC 37037
4                          NA   Guilford County, NC 37081
5                          NA     Orange County, NC 37135
6                          NA   Randolph County, NC 37151
7                          NA Rockingham County, NC 37157
8  Alexander County, NC 37003  Alexander County, NC 37003
9                          NA   Caldwell County, NC 37027
10                         NA    Catawba County, NC 37035
11                         NA    Iredell County, NC 37097
12                         NA     Wilkes County, NC 37193
13 Alleghany County, NC 37005  Alleghany County, NC 37005
14                         NA       Ashe County, NC 37009
15                         NA      Surry County, NC 37171
16                         NA     Wilkes County, NC 37193
17                         NA    Grayson County, VA 51077
18     Anson County, NC 37007      Anson County, NC 37007
19                         NA Montgomery County, NC 37123
20                         NA   Richmond County, NC 37153

我碰巧只对该链接中发现的北卡罗来纳州部分数据感兴趣，其中一部分是您在上面看到的：

#
nc_cc <- structure(list(c1 = c("Alamance County, NC", "", "", "", "", "", "", "Alexander County, NC", "", "", "", "", "Alleghany County, NC", "", "", "", "", "Anson County, NC", "", ""), cd1 = c(37001L, NA, NA, NA, NA, NA, NA, 37003L, NA, NA, NA, NA, 37005L, NA, NA, NA, NA, 37007L, NA, NA), c2 = c("Alamance County, NC", "Caswell County, NC", "Chatham County, NC", "Guilford County, NC", "Orange County, NC", "Randolph County, NC", "Rockingham County, NC", "Alexander County, NC", "Caldwell County, NC", "Catawba County, NC", "Iredell County, NC", "Wilkes County, NC", "Alleghany County, NC", "Ashe County, NC", "Surry County, NC", "Wilkes County, NC", "Grayson County, VA", "Anson County, NC", "Montgomery County, NC", "Richmond County, NC" ), cd2 = c(37001L, 37033L, 37037L, 37081L, 37135L, 37151L, 37157L, 37003L, 37027L, 37035L, 37097L, 37193L, 37005L, 37009L, 37171L, 37193L, 51077L, 37007L, 37123L, 37153L)), .Names = c("c1", "cd1", "c2", "cd2"), row.names = c(NA, 20L), class = "data.frame")
#

我想要一个干净的邻接关联（县名是多余的），所以我想要的输出可以采用多种形式：data.frame，列表，......

我想出的粗略解决方案（经过深思熟虑）是这样的：

require(data.table)
DT <- data.table(nc_cc)
DT[,list(cd1=cd1[1],cd2),by=cumsum(!is.na(cd1))][,list(cd1,cd2)]

给予

      cd1   cd2
 1: 37001 37001
 2: 37001 37033
 3: 37001 37037
 4: 37001 37081
 5: 37001 37135
 6: 37001 37151
 7: 37001 37157
 8: 37003 37003
 9: 37003 37027
10: 37003 37035
11: 37003 37097
12: 37003 37193
13: 37005 37005
14: 37005 37009
15: 37005 37171
16: 37005 37193
17: 37005 51077
18: 37007 37007
19: 37007 37123
20: 37007 37153

我已经标记了这个，data.table因为我在上面的解决方案中使用了它，我怀疑可以用roll. 真的，我从来没有理解过的文档roll，所以我希望在这里学到一些东西......所以：这可以做得更好吗？

编辑： 这个问题问的是同样的事情，所以我将我的问题修改为：“有没有更好的方法来使用data.table或使用 R 来做到这一点（因为我不愿意安装更多的包）？”

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2 回答 2

11

一个非常标准的方法是：

library(data.table)
dt = data.table(nc_cc)

dt[, cd1 := cd1[1], by = cumsum(!is.na(cd1))]
于 2013-09-17T05:11:48.237 回答
0

我找到了一个roll基于@Arun 的答案的解决方案！

在我的应用程序中，它比cumsum@eddi（......我在陈述问题时）使用的答案更加复杂：

DT <- data.table(nc_cc)
setkey(DT[,i:=.I],i)

DT[
    DT[c1!=""][J(1:20),roll=TRUE][,list(c1,cd1),key=i],
    `:=`(c1=i.c1,cd1=i.cd1)
]

我从@eddi对我的另一个问题的回答中学到了这i.name一点。

于 2013-09-29T03:29:20.420 回答