我有一个数据集，如帖子底部所示。该数据有四列，分别称为SIC，AT95Group，AT95Mean，AT95Med。 AT95Group列具有四个值，例如“00”，“01”，“11”和“10”。目前，对于每个SIC，我们对AT95Group的每个值都有四行。我想以某种方式重塑数据帧，以便每个SIC只有一行。虽然之前我们为每个（SIC，AT95Group）对有两个名为mean和med的列，但我们想要创建基本上4 * 2列（4个用于组“00”，“11”，“01”，“10”）和2 for（“Mean”和“Med”）。八列将像“00Mean”，“11Mean”，“00Med”，“11Med”等，每个SIC具有相应的值。
我觉得这很难做到。请给我任何建议。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粗略失败。不确定如何继续前进。
pp <- unique(dacc1[,c("SIC","AT95Group","AT95Med","AT95Mean")])
xsic <- unique(pp[,"SIC"]);
xlist <- list(xsic,rep("AT95",length(xsic)));
编辑：
我在运行特洛伊的结果后得到的结果：
> pp1 <- head(pp,20)
SIC AT95Group AT95Med AT95Mean
241 1 11 0.06910391 0.06910391
236 1 10 0.06086497 0.06086497
27 1 00 0.06099742 0.06099742
1126 10 11 0.21557182 0.21557182
1035 10 01 0.30530899 0.30530899
1030 10 00 0.35131256 0.35131256
664 10 10 0.35270472 0.35270472
1269 12 01 0.04598877 0.04598877
1259 12 11 0.03044662 0.03044662
1245 12 10 0.05138754 0.05138754
1244 12 00 0.05414319 0.05414319
3919 13 11 0.06509209 0.06509209
4722 13 01 0.14372464 0.14372464
3329 13 00 0.15609279 0.15609279
3222 13 10 0.09760597 0.09760597
4886 14 11 0.01166202 0.01166202
4889 14 01 0.01888952 0.01888952
4951 14 10 0.03568362 0.03568362
4860 14 00 0.05130409 0.05130409
5108 15 01 0.09824487 0.09824487
> molten<-melt(pp);
Using AT95Group as id variables
molten$variable<-paste(gsub("[AT95]","",molten$variable),molten$AT95Group," ");
cast(molten[,c(1,3,4)], SIC ~ variable);
> cast(molten[,c(1,3,4)], SIC ~ variable);
Error in `[.data.frame`(molten, , c(1, 3, 4)) :
undefined columns selected
答案 0 :(得分：1)
我希望这个解决方案不会太神秘：
xsic <- unique(pp[,"SIC"]);
AT = c("00", "01", "10", "11")
d = data.frame(xsic=xsic);
for(i in 1:4) {
subgroup = pp[ pp$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)];
}
结果：
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
答案 1 :(得分：1)
或者你可以使用“reshape”包：
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)
给你：
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
答案 2 :(得分：1)
对于记录，reshape中还有一个base函数（嗯，stats）：
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