【发布时间】：2017-03-09 10:01:08
【问题描述】：
我还是 data.table 的新手。我的问题类似于this one 和this one。不同之处在于我想按组计算多个变量的加权平均值，但每个平均值使用多个权重。
考虑以下data.table（实际要大得多）：
library(data.table)
set.seed(123456)
mydata <- data.table(CLID = rep("CNK", 10),
ITNUM = rep(c("First", "Second", "First", "First", "Second"), 2),
SATS = rep(c("Always", "Amost always", "Sometimes", "Never", "Always"), 2),
ASSETS = rep(c("0-10", "11-25", "26-100", "101-200", "MORE THAN 200"), 2),
AVGVALUE1 = rnorm(10, 10, 2),
AVGVALUE2 = rnorm(10, 10, 2),
WGT1 = rnorm(10, 3, 1),
WGT2 = rnorm(10, 3, 1),
WGT3 = rnorm(10, 3, 1))
#I set the key of the table to the variables I want to group by,
#so the output is sorted
setkeyv(mydata, c("CLID", "ITNUM", "SATS", "ASSETS"))
我想要实现的是使用每个权重变量按ITNUM、SATS、ASSETS 定义的组计算AVGVALUE1 和AVGVALUE2（可能还有更多变量）的加权平均值WGT1、WGT2、WGT3（可能还有更多）。因此，对于我想计算加权平均值的每个变量，我将按组（或无论权重的数量是多少）获得三个加权平均值。
我可以为每个变量分别做，例如：
all.weights <- c("WGT1", "WGT2", "WGT3")
avg.var <- "AVGVALUE1"
split.vars <- c("ITNUM", "SATS", "ASSETS")
mydata[ , Map(f = weighted.mean, x = .(get(avg.var)), w = mget(all.weights),
na.rm = TRUE), by = c(key(mydata)[1], split.vars)]
我在by 中添加了第一个键变量，尽管它是一个常量，因为我想将它作为输出中的一列。我得到：
CLID ITNUM SATS ASSETS V1 V2 V3
1: CNK First Always 0-10 11.66824 11.66819 11.66829
2: CNK First Never 101-200 11.37378 12.21008 11.60182
3: CNK First Sometimes 26-100 12.43004 13.13450 12.01330
4: CNK Second Always MORE THAN 200 12.32265 11.81613 12.56786
5: CNK Second Amost always 11-25 10.76556 11.34669 10.52458
但是，对于实际的data.table，我有更多的列来计算加权平均值（以及要使用的权重更多），一一进行会相当麻烦。我想象的是一个函数，其中每个变量（AVGVALUE1、AVGVALUE2 等）的平均值是用每个权重变量（WGT1、WGT2、WGT3 等）计算的并将计算加权平均值的每个变量的输出添加到列表中。我想这个列表是最好的选择，因为如果所有估计都在同一个输出中，那么列数可能是无穷无尽的。所以是这样的：
[[1]]
CLID ITNUM SATS ASSETS V1 V2 V3
1: CNK First Always 0-10 11.66824 11.66819 11.66829
2: CNK First Never 101-200 11.37378 12.21008 11.60182
3: CNK First Sometimes 26-100 12.43004 13.13450 12.01330
4: CNK Second Always MORE THAN 200 12.32265 11.81613 12.56786
5: CNK Second Amost always 11-25 10.76556 11.34669 10.52458
[[2]]
CLID ITNUM SATS ASSETS V1 V2 V3
1: CNK First Always 0-10 9.132899 9.060045 9.197005
2: CNK First Never 101-200 12.896584 13.278680 13.000772
3: CNK First Sometimes 26-100 10.972260 11.215390 10.828431
4: CNK Second Always MORE THAN 200 11.704404 11.611072 11.749586
5: CNK Second Amost always 11-25 8.086409 8.225030 8.028928
到目前为止我尝试了什么：
-
使用
lapplyall.weights <- c("WGT1", "WGT2", "WGT3") avg.vars <- c("AVGVALUE1", "AVGVALUE2") split.vars <- c("ITNUM", "SATS", "ASSETS") lapply(mydata, function(i) { mydata[ , Map(f = weighted.mean, x = mget(avg.vars)[i], w = mget(all.weights), na.rm = TRUE), by = c(key(mydata)[1], split.vars)] }) Error in weighted.mean.default(x = dots[[1L]][[1L]], w = dots[[2L]][[1L]], : 'x' and 'w' must have the same length -
使用
mapplymyfun <- function(data, spl.v, avg.v, wgts) { data[ , Map(f = weighted.mean, x = mget(avg.v), w = mget(all.weights), na.rm = TRUE), by = c(key(data)[1], spl.v)] } mapply(FUN = myfun, data = mydata, spl.v = split.vars, avg.v = avg.vars, wgts = all.weights) Error: value for ‘AVGVALUE2’ not found
我试图将 mget(avg.v) 包装为一个列表 - .(mget(avg.v))，但随后又出现了另一个错误：
Error in mapply(FUN = f, ..., SIMPLIFY = FALSE) :
could not find function "."
有人可以帮忙吗？
【问题讨论】：
标签： r list data.table weighted-average