使用data.table聚合子总计和总计 [英] Aggregating sub totals and grand totals with data.table
问题描述
我在R中有一个 data.table
:
library(data.table)
set.seed(1)
DT = data.table(
group=sample(letters[1:2],100,replace=TRUE),
year=sample(2010:2012,100,replace=TRUE),
v=runif(100))
按组和年度将此数据汇总到摘要表中简单而优雅:
Aggregating this data into a summary table by group and year is simple and elegant:
table <- DT[,mean(v),by='group, year']
数据到汇总表,包括小计和总计,是一个更困难一点,并且很少优雅:
However, aggregating this data into a summary table, including subtotals and grand totals, is a little more difficult, and a lot less elegant:
library(plyr)
yearTot <- DT[,list(mean(v),year='Total'),by='group']
groupTot <- DT[,list(mean(v),group='Total'),by='year']
Tot <- DT[,list(mean(v), year='Total', group='Total')]
table <- rbind.fill(table,yearTot,groupTot,Tot)
table$group[table$group==1] <- 'Total'
table$year[table$year==1] <- 'Total'
这会产生:
table[order(table$group, table$year), ]
b $ b
有一个简单的方法用data.table指定小计和总计,例如plyr的 margins = TRUE
命令?我更喜欢使用data.table over plyr在我的数据集,因为它是一个非常大的数据集,我已经在data.table格式。
Is there a simple way to specify subtotals and grand totals with data.table, such as the margins=TRUE
command for plyr? I would prefer to use data.table over plyr on my dataset, as it is a very large dataset that I already have in the data.table format.
推荐答案
我不知道一个简单的方法。这里是一个实现的第一刺。我不知道plyr中的 margin = TRUE
是什么?
I'm not aware of a simple way. Here's a first stab at an implementation. I don't know margins=TRUE
in plyr, is this what that does?
crossby = function(DT, j, by) {
j = substitute(j)
ans = rbind(
DT[,eval(j),by],
DT[,list("Total",eval(j)),by=by[1]],
cbind("Total",DT[,eval(j),by=by[2]]),
list("Total","Total",DT[,eval(j)]),
use.names=FALSE
# 'use.names' argument added in data.table v1.8.0
)
setkeyv(ans,by)
ans
}
crossby(DT, mean(v), c("group","year"))
group year V1
[1,] a 2010 0.2926945
[2,] a 2011 0.4176346
[3,] a 2012 0.4227796
[4,] a Total 0.3901875
[5,] b 2010 0.5231845
[6,] b 2011 0.4997119
[7,] b 2012 0.4306871
[8,] b Total 0.4835788
[9,] Total 2010 0.4278093
[10,] Total 2011 0.4463616
[11,] Total 2012 0.4271160
[12,] Total Total 0.4350153
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