CODEWITHSUNDEEP
rdataframeaggregateapply
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Reputation: 49

R aggregate columns of a data frame

OK, apply is my nemesis, but I'm pretty sure it's involved with the answer here.

I have poverty data with three levels, state (name_1), county(name_2), and township(name_3). I need to do a naive downscale, where I assume that the average state income (income = e2004MeanY) is equal to 1) each county income and 2) each township income. 

> head(da)
                     name_1  name_2            name_3      e2004MeanY  acc_500k
0                Vung Dong Bac Lao Cai         Xi Mai Ca        637 539.67810
1                Vung Dong Bac Bac Kan  Bac Kan Township       2199 378.90057
2                Vung Dong Bac Bac Kan             Ba Be       1075 549.34222
3 Vung Dong Bang Song Cuu Long Long An          Can Duoc       2284  74.61940
4 Vung Dong Bang Song Cuu Long Long An         Can Giuoc       2256  96.18077
5 Vung Dong Bang Song Cuu Long Can Tho Vi Thanh Township       2136 262.74435

I've aggregated the data, so I have the means for each state:

> vnm1 <- aggregate(da[,-c(1:3)], da[,1, drop=F], mean, na.rm=TRUE)
> head(vnm1)
                        name_1 e2004MeanY acc_500k        alt     cost cropland
1            Vung Bac trung Bo   1680.296 497.8453 162.023675 375.4979 98.78586
2                Vung Dong Bac   1574.306 355.9818 327.662351 423.0005 98.66135
3 Vung Dong Bang Song Cuu Long   2031.346 269.4059   4.733111 186.6358 98.41601
4     Vung Dong bang song Hong   2416.989 118.4019  11.128992 150.1016 98.40423
5             Vung Dong Nam Bo   3350.440 205.7134 171.782189 233.0148 99.15330
6  Vung Duyen Hai Nam Trung Bo   1855.655 793.1942 235.375168 427.0307 97.12402

I have dataframes, vnm2 and vnm3, which are aggregated the same way as vnm1, except by name_2 and name_3, respectively:

vnm2 <- aggregate(da[,-c(1:3)], da[,2, drop=F], mean, na.rm=TRUE)
vnm3 <- na.omit(da[,-c(1:2)])

How do I get the vnm1$e2004MeanY values into vnm2 and vnm3?

Upvotes: 2

Views: 738

Answers (1)

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Reputation: 12411

I think that this code will work (even if it is not optimized) :

f2 <- function(i) {vnm1[which(vnm1[,1] ==da[min(which( da[,2] == vnm2[i,1])),1]),2]}
data.frame(cbind(vnm2,e2004MeanY=sapply(FUN=f2,1:length(vnm2[,1]))))

f3 <- function(i) {vnm1[which(vnm1[,1] ==da[min(which( da[,3] == vnm3[i,1])),1]),2]}
data.frame(cbind(vnm2,e2004MeanY=sapply(FUN=f3,1:length(vnm3[,1]))))

PS : It has been tested with a simple example.

Upvotes: 1

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