用data.table将R中的特定其他列乘以许多列? [英] Multiply many columns by a specific other column in R with data.table?
问题描述
我在 R 中有一个大型 data.table，其中有几列带有美元值.在另一列中，我有一个通货膨胀调整数.我试图弄清楚如何用它乘以通货膨胀调整列来更新我的每个货币列.假设我有数据:
I have a large data.table in R with several columns with dollar values. In a different column I have an inflation adjustment number. I am trying to figure out how to update each of my monetary columns with it multiplied by the inflation adjustment column. Suppose I have the data:
DT <- data.table(id=1:1000,year=round(runif(1000)*10),
inc1 = runif(1000), inc2 = runif(1000), inc3 = runif(1000),
deflator = rnorm(1000))
给出输出:
id year inc1 inc2 inc3 deflator
1: 1 8 0.4754808 0.6678110 0.41533976 -0.64126988
2: 2 2 0.6568746 0.7765634 0.70616373 0.39687915
3: 3 6 0.8192947 0.9236281 0.90002534 -0.69545700
4: 4 4 0.7781929 0.1624902 0.17565790 0.05263055
5: 5 7 0.6232520 0.8024975 0.86449836 0.70781887
---
996: 996 2 0.9676383 0.2238746 0.19822000 0.78564836
997: 997 9 0.9877410 0.5783748 0.57497438 -1.63365223
998: 998 8 0.2220570 0.6500632 0.19814932 1.00260174
999: 999 3 0.4793767 0.2830457 0.54835581 1.04168818
1000: 1000 8 0.2003476 0.6121637 0.02921505 0.34933690
实际上我有 inc1 - inc100，而不仅仅是三个变量，我想找出一种方法来执行此操作:
in reality I have inc1 - inc100, rather than just three variables and I want to figure out a way to perform this action:
DT[, inc1 := inc1 * deflator]
对于我的 100 个收入列中的每一个(上面的假数据中的 inc1、inc2、inc3).将来我将有 100 多个列，所以我想找出一种方法来循环操作列.有没有办法一次对所有收入列执行此操作?
for each of my 100 income columns (inc1, inc2, inc3 in the fake data above). I will have more than 100 columns in the future, so I would like to figure out a way to loop the action over the columns. Is there a way to do this for all the income columns at once?
我想做这样的事情:
inc_cols = c(inc1, inc2, inc3)
DT[, inc_cols := lapply(inc_cols,function(x)= x * deflator),]
或
DT[, inc_cols := lapply(.SD,function(x)= x * deflator),.SDcols = inc_cols]
但这些似乎都不起作用.我还尝试使用 get() 函数来明确 deflator 是引用列，例如:
but neither of these seem to work. I also tried using the get() function to make it clear deflator is a referencing a column, like:
DT[, inc_cols := lapply(.SD,function(x)= x * get(deflator)),.SDcols = inc_cols]
但没有运气.我还尝试通过以下方式循环变量:
but had no luck. I also tried to loop through the variables with something like:
for (var in inc_cols) {
print(var)
DT[, get(var) := get(var) *infAdj2010_mult]
}
返回
[1] "inc1"
Error in get(var) : object 'inc1' not found
我意识到这可能是一个直截了当的问题，我尝试在这里搜索其他问题以及各种在线指南和教程，但我找不到与我的具体问题匹配的示例.它类似于此 问题，但不完全是.
I realize this is probably a straight forward question and I have tried to search the other questions here and various online guides and tutorials, but I cannot find an example matching my specific problem. It is similar to this question, but not exactly.
感谢您的帮助！
推荐答案
你可以试试
DT[, (inc_cols) := lapply(.SD, function(x)
x * DT[['deflator']] ), .SDcols = inc_cols]
head(DT1,2)
# id year inc1 inc2 inc3 deflator
#1: 1 3 0.614838304 0.009796974 0.3236051 0.7735552
#2: 2 2 -0.001583579 -0.082289606 -0.1365115 -0.6644330
或者如果你需要一个循环
Or if you need a loop
for(inc in inc_cols){
nm1 <- as.symbol(inc)
DT[,(inc):= eval(nm1)*deflator]
}
head(DT,2)
# id year inc1 inc2 inc3 deflator
#1: 1 3 0.614838304 0.009796974 0.3236051 0.7735552
#2: 2 2 -0.001583579 -0.082289606 -0.1365115 -0.6644330
或者使用 set 的可能选项应该非常快，因为避免了 [.data.table 的开销(@Arun 建议)
Or a possible option using set which should be very fast as the overhead of [.data.table is avoided (suggested by @Arun)
indx <- grep('inc', colnames(DT))
for(j in indx){
set(DT, i=NULL, j=j, value=DT[[j]]*DT[['deflator']])
}
head(DT,2)
# id year inc1 inc2 inc3 deflator
#1: 1 3 0.614838304 0.009796974 0.3236051 0.7735552
#2: 2 2 -0.001583579 -0.082289606 -0.1365115 -0.6644330
在哪里
inc_cols <- grep('^inc', colnames(DT), value=TRUE)
数据
set.seed(24)
DT <- data.table(id=1:1000,year=round(runif(1000)*10),
inc1 = runif(1000), inc2 = runif(1000), inc3 = runif(1000),
deflator = rnorm(1000))
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