在R中重塑数据

我有一个数据集显示在文章的底部。数据有四列，分别为SIC、AT95Group、AT95Mean和AT95Med。AT95Group列具有四个值，例如“00”、“01”、“11”和“10”。目前，对于每个SIC，AT95Group的每个值都有四行。我想重塑数据帧，使每个SIC只有一行。虽然之前我们为每个（SIC，AT95Group）对创建了两个名为mean和med的列，但我们希望创建4*2个列（4个用于组“00”、“11”、“01”、“10”），2个用于（“mean”和“med”）。八列类似于“00Mean”、“11Mean”、“00Med”、“11Med”等，每个SIC都有相应的值

我觉得这极难做到。有什么建议吗。谢谢

> dput(head(pp,20))
structure(list(SIC = c(1L, 1L, 1L, 10L, 10L, 10L, 10L, 12L, 12L, 
12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 15L), AT95Group = c("11", 
"10", "00", "11", "01", "00", "10", "01", "11", "10", "00", "11", 
"01", "00", "10", "11", "01", "10", "00", "01"), AT95Med = c(0.0691039117115276, 
0.0608649722972575, 0.0609974198491522, 0.215571816296268, 0.305308985848382, 
0.351312558091798, 0.352704719896703, 0.0459887720804718, 0.0304466181779069, 
0.0513875431555943, 0.0541431932578377, 0.0650920855876547, 0.143724642017362, 
0.156092793582293, 0.0976059673595903, 0.0116620184564053, 0.0188895210677074, 
0.0356836223212195, 0.0513040852859517, 0.0982448708035204), 
    AT95Mean = c(0.0691039117115276, 0.0608649722972575, 0.0609974198491522, 
    0.215571816296268, 0.305308985848382, 0.351312558091798, 
    0.352704719896703, 0.0459887720804718, 0.0304466181779069, 
    0.0513875431555943, 0.0541431932578377, 0.0650920855876547, 
    0.143724642017362, 0.156092793582293, 0.0976059673595903, 
    0.0116620184564053, 0.0188895210677074, 0.0356836223212195, 
    0.0513040852859517, 0.0982448708035204)), .Names = c("SIC", 
"AT95Group", "AT95Med", "AT95Mean"), row.names = c(241L, 236L, 
27L, 1126L, 1035L, 1030L, 664L, 1269L, 1259L, 1245L, 1244L, 3919L, 
4722L, 3329L, 3222L, 4886L, 4889L, 4951L, 4860L, 5108L), class = "data.frame")

---

尝试上述代码的尝试失败。不知道如何继续前进

pp <- unique(dacc1[,c("SIC","AT95Group","AT95Med","AT95Mean")])
xsic <- unique(pp[,"SIC"]);
xlist <- list(xsic,rep("AT95",length(xsic)));

---

pp我希望这个解决方案不要太神秘：

xsic <- unique(pp[,"SIC"]);
AT = c("00", "01", "10", "11")
d = data.frame(xsic=xsic);
for(i in 1:4) {
  subgroup = pp[ pp$AT95Group==AT[i],];
  d[[paste0(AT[i],"AT95Med")]] = subgroup$AT95Med[match(xsic,subgroup$SIC)];
  d[[paste0(AT[i],"AT95Mean")]] = subgroup$AT95Mean[match(xsic,subgroup$SIC)];
}

或者您可以使用“重塑”软件包：

对于记录，在
base
中还有一个
重塑
函数（好的，
stats
）：

请看我运行您提到的命令后得到的结果。我已经在编辑中发布了我的结果。我出错了。嗯。。。不确定。有一件事是你们在pp上运行melt，而不是pp1——这是有意的还是你们有可能重塑pp？因为我看到melt不包括默认组中的SIC，所以可以替换melt吗
xsic <- unique(pp[,"SIC"]);
AT = c("00", "01", "10", "11")
d = data.frame(xsic=xsic);
for(i in 1:4) {
  subgroup = pp[ pp$AT95Group==AT[i],];
  d[[paste0(AT[i],"AT95Med")]] = subgroup$AT95Med[match(xsic,subgroup$SIC)];
  d[[paste0(AT[i],"AT95Mean")]] = subgroup$AT95Mean[match(xsic,subgroup$SIC)];
}

xsic 00AT95Med 00AT95Mean  01AT95Med 01AT95Mean  10AT95Med 10AT95Mean  11AT95Med 11AT95Mean
  1 0.06099742 0.06099742         NA         NA 0.06086497 0.06086497 0.06910391 0.06910391
 10 0.35131256 0.35131256 0.30530899 0.30530899 0.35270472 0.35270472 0.21557182 0.21557182
 12 0.05414319 0.05414319 0.04598877 0.04598877 0.05138754 0.05138754 0.03044662 0.03044662
 13 0.15609279 0.15609279 0.14372464 0.14372464 0.09760597 0.09760597 0.06509209 0.06509209
 14 0.05130409 0.05130409 0.01888952 0.01888952 0.03568362 0.03568362 0.01166202 0.01166202
 15         NA         NA 0.09824487 0.09824487         NA         NA         NA         NA

install.packages("reshape")  # only run this once if you don't have it
require(reshape)
pp   #  this is what I called your table
molten<-melt(pp)  # this stretches the table out into variable/value pairs

# then modify the "variable" values so they reflect the group (and delete 'AT95')
molten$variable<-paste(gsub("[AT95]","",molten$variable),molten$AT95Group," ")

# then use cast (you can look up the documentation in ?reshape)
# but basically this gives you a crosstab of the SICs against the new variables
# the significant of 1,3,4 is it pulls out only the columns I want to cast
cast(molten[,c(1,3,4)], SIC ~ variable)

  SIC  Mean 00    Mean 01    Mean 10    Mean 11     Med 00     Med 01     Med 10     Med 11  
1   1 0.06099742         NA 0.06086497 0.06910391 0.06099742         NA 0.06086497 0.06910391
2  10 0.35131256 0.30530899 0.35270472 0.21557182 0.35131256 0.30530899 0.35270472 0.21557182
3  12 0.05414319 0.04598877 0.05138754 0.03044662 0.05414319 0.04598877 0.05138754 0.03044662
4  13 0.15609279 0.14372464 0.09760597 0.06509209 0.15609279 0.14372464 0.09760597 0.06509209
5  14 0.05130409 0.01888952 0.03568362 0.01166202 0.05130409 0.01888952 0.03568362 0.01166202
6  15         NA 0.09824487         NA         NA         NA 0.09824487         NA         NA

reshape(pp, direction = "wide", idvar = "SIC", 
      timevar = "AT95Group", v.names = c("AT95Med", "AT95Mean"))
#     SIC AT95Med.11 AT95Mean.11 AT95Med.10 AT95Mean.10 AT95Med.00 AT95Mean.00 AT95Med.01 AT95Mean.01
#241    1 0.06910391  0.06910391 0.06086497  0.06086497 0.06099742  0.06099742         NA          NA
#1126  10 0.21557182  0.21557182 0.35270472  0.35270472 0.35131256  0.35131256 0.30530899  0.30530899
#1269  12 0.03044662  0.03044662 0.05138754  0.05138754 0.05414319  0.05414319 0.04598877  0.04598877
#3919  13 0.06509209  0.06509209 0.09760597  0.09760597 0.15609279  0.15609279 0.14372464  0.14372464
#4886  14 0.01166202  0.01166202 0.03568362  0.03568362 0.05130409  0.05130409 0.01888952  0.01888952
#5108  15         NA          NA         NA          NA         NA          NA 0.09824487  0.09824487