r - 合并两个公共列上的多个数据框

Question

我见过一些关于将 csv 文件合并到一个数据框中的问题。如果数据框已经在工作区中怎么办。我有五个广泛的动物园，我将它们转换为数据框，然后融化。这是一个人的头：

> head(df.mon.ssf.ret)
      date variable value
1 2009.000     AA1C    NA
2 2009.083     AA1C    NA
3 2009.167     AA1C    NA
4 2009.250     AA1C    NA
5 2009.333     AA1C    NA
6 2009.417     AA1C    NA

我可以将这些在“日期”和“变量”上与一系列嵌套合并合并，但这似乎很笨拙。有没有更程序化的合并方式？

如果我确信所有动物园中的列的顺序相同，我是否可以确信 melt 保持这种排序和使用cbind？谢谢！

更新：

关于融化的使用理念，我缺少一些东西。当我合并为一个动物园并使用三个动物园融化为一个非常宽的数据框时，会发生以下情况：

> temp <- merge(z.ssf.oi, z.ssf.oig, z.ssf.ret)
> class(temp)
[1] "zoo"
> temp2 <- cbind(index(temp), as.data.frame(temp))
> class(temp2)
[1] "data.frame"
> names(temp2)[1] <- "date"
> dim(temp2)
[1]   12 1204
> temp3 <- melt(temp2, id="date")
Error in data.frame(ids, variable, value) : 
  arguments imply differing number of rows: 12, 14436
> head(temp2)[, 1:5]
             date AA1C.z.ssf.oi AAPL1C.z.ssf.oi ABT1C.z.ssf.oi ABX1C.z.ssf.oi
Jan 2009 Jan 2009      1895.800        49191.25             NA             NA
Feb 2009 Feb 2009      1415.579        42650.26             NA        6267.96
Mar 2009 Mar 2009      1501.398        36712.20             NA       11581.65
Apr 2009 Apr 2009      1752.936        74376.27             NA       12168.29
May 2009 May 2009      1942.874        96307.30             NA       13490.60
Jun 2009 Jun 2009            NA        79170.70             NA       16337.21

更新2：感谢您的帮助！这是一个非常手动的解决方案

> A <- cbind(index(z.ssf.oi), as.data.frame(z.ssf.oi))
> names(A)[1] <- "date"
> B <- cbind(index(z.ssf.oig), as.data.frame(z.ssf.oig))
> names(B)[1] <- "date"
> C <- cbind(index(z.ssf.ret), as.data.frame(z.ssf.ret))
> names(C)[1] <- "date"
> A.melt <- melt(A, id="date")
> head(A.melt)
      date variable value
1 Jan 2009      A1C    NA
2 Feb 2009      A1C    NA
3 Mar 2009      A1C    NA
4 Apr 2009      A1C    NA
5 May 2009      A1C    NA
6 Jun 2009      A1C    NA
> B.melt <- melt(B, id="date")
> C.melt <- melt(C, id="date")
> ans <- merge(merge(A.melt, B.melt, by=c("date", "variable")), C.melt, by=c("date", "variable"))
> names(ans)[3:5] <- c("oi", "oig", "ret")
> head(ans)
      date variable       oi       oig         ret
1 Apr 2009      A1C       NA        NA          NA
2 Apr 2009     AA1C       NA        NA          NA
3 Apr 2009   AAPL1C 59316.88 0.3375786 0.008600073
4 Apr 2009    ABB1C       NA        NA          NA
5 Apr 2009    ABT1C       NA        NA          NA
6 Apr 2009    ABX1C       NA        NA          NA

（并且 NA 来自家里不完整的数据集，需要在我的数据库中进行过滤）

更新 3：这里是一些 dputs（我取了每个宽动物园的 [1:10, 1:10] 子集并转换为数据帧）

> dput(A)
structure(list(group = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L), class = "factor", .Label = "oi"), date = structure(c(2009, 
2009.08333333333, 2009.16666666667, 2009.25, 2009.33333333333, 
2009.41666666667, 2009.5, 2009.58333333333, 2009.66666666667, 
2009.75), class = "yearmon"), AA1C = c(NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), AAPL1C = c(49226.391, 42662.1589473684, 35354.4254545455, 
57161.6495238095, 84362.895, NA, NA, 47011.8519047619, 57852.2171428571, 
33058.0090909091), ABT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), 
    ABX1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ACE1C = c(NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_), ACI1C = c(NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_), ACS1C = c(NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_), ADBE1C = c(NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
    ), ADCT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ADI1C = c(NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_)), .Names = c("group", "date", 
"AA1C", "AAPL1C", "ABT1C", "ABX1C", "ACE1C", "ACI1C", "ACS1C", 
"ADBE1C", "ADCT1C", "ADI1C"), row.names = c("Jan 2009", "Feb 2009", 
"Mar 2009", "Apr 2009", "May 2009", "Jun 2009", "Jul 2009", "Aug 2009", 
"Sep 2009", "Oct 2009"), class = "data.frame")
> dput(B)
structure(list(group = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L), class = "factor", .Label = "oig"), date = structure(c(2009.08333333333, 
2009.16666666667, 2009.25, 2009.33333333333, 2009.41666666667, 
2009.5, 2009.58333333333, 2009.66666666667, 2009.75, 2009.83333333333
), class = "yearmon"), AA1C = c(NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), AAPL1C = c(-0.143117562125788, -0.187888745830302, 0.480459636485712, 
0.389244461579155, NA, NA, NA, 0.207492040517069, -0.559627909130612, 
NA), ABT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ABX1C = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_), ACE1C = c(NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), ACI1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ACS1C = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_), ADBE1C = c(NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), ADCT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ADI1C = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_)), .Names = c("group", "date", "AA1C", "AAPL1C", 
"ABT1C", "ABX1C", "ACE1C", "ACI1C", "ACS1C", "ADBE1C", "ADCT1C", 
"ADI1C"), row.names = c("Feb 2009", "Mar 2009", "Apr 2009", "May 2009", 
"Jun 2009", "Jul 2009", "Aug 2009", "Sep 2009", "Oct 2009", "Nov 2009"
), class = "data.frame")
> dput(C)
structure(list(group = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L), class = "factor", .Label = "ret"), date = structure(c(2009, 
2009.08333333333, 2009.16666666667, 2009.25, 2009.33333333333, 
2009.41666666667, 2009.5, 2009.58333333333, 2009.66666666667, 
2009.75), class = "yearmon"), AA1C = c(NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), AAPL1C = c(-0.143117562125788, -0.187888745830302, 0.480459636485712, 
0.389244461579155, NA, NA, NA, 0.207492040517069, -0.559627909130612, 
NA), ABT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ABX1C = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_), ACE1C = c(NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), ACI1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ACS1C = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_), ADBE1C = c(NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), ADCT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ADI1C = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_)), .Names = c("group", "date", "AA1C", "AAPL1C", 
"ABT1C", "ABX1C", "ACE1C", "ACI1C", "ACS1C", "ADBE1C", "ADCT1C", 
"ADI1C"), row.names = c("Feb 2009", "Mar 2009", "Apr 2009", "May 2009", 
"Jun 2009", "Jul 2009", "Aug 2009", "Sep 2009", "Oct 2009", "Nov 2009"
), class = "data.frame")

score 6 · Accepted Answer

你可以试试这个。未经测试，因为您的示例不可重现。如果您想要更好的答案，请给我们一些 z.sfff.oi、z.sff.oig 和 z.sff.ret 的虚拟数据。您可以使用 dput() 为可重现的数据集生成代码。

A <- data.frame(Group = "oi", date = as.factor(index(z.ssf.oi),) as.data.frame(z.ssf.oi)))
B <- data.frame(Group = "oig", date = as.factor(index(z.ssf.oig)), as.data.frame(z.ssf.oig)))
C <- data.frame(Group = "ret", date = as.factor(index(z.ssf.ret)), as.data.frame(z.ssf.ret)))
Long <- melt(rbind(A, B, C), id.vars = c("Group", "date")))
cast(date ~ Group, data = Long)

r - 合并两个公共列上的多个数据框

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