data.table生成多列并汇总 [英] data.table generate multiple columns and summarize them

问题描述

我正在尝试学习data.table语法。我掌握了大多数简单汇总的基础知识，但我没有掌握如何使用data.table从现有列中生成新列并进行汇总。

I am trying to learn data.table syntax. I have most of the basics of simple summarizations but I am not getting how to use data.table to generate new columns from an existing column and summarize.

这里是一个MWE示例在这里，我使用dplyr和基础工具通过对变量进行分组来从一个或多个汇总列：

Here's a MWE example where I use dplyr and base tools to make multiple columns from one and thn summarize by grouping variables:

当前输入

##    fact1 fact2 X0
## 1      b     2  9
## 2      a     2  6
## 3      b     1  7
## 4      c     2  3
## 5      a     1  8
## 6      a     1  4
## 7      a     1  5
## 8      a     1  1
## 9      b     1  2
## 10     b     2 10

基本+ dlyr代码

set.seed(10)
dat <- data.frame(
    fact1 = factor(sample(c('a', 'b', 'c'), 10, TRUE)), 
    fact2 = factor(sample(1:2, 10, TRUE)), 
    X0 = sample(1:10, 10)
)

add <- function(x, y) x + y
z <- sample(1:10, 6, FALSE)

library(dplyr)

z %>% 
    lapply(., add, dat[, 'X0']) %>%
    do.call(cbind, .) %>%
    cbind(dat, .) %>%
    data.frame() %>%
    group_by(fact1, fact2) %>%
    summarise_each(funs(sum))

所需的输出

## Source: local data frame [5 x 9]
## Groups: fact1
## 
##   fact1 fact2 X0 X1 X2 X3 X4 X5 X6
## 1     a     1 18 42 22 26 46 30 34
## 2     a     2  6 12  7  8 13  9 10
## 3     b     1  9 21 11 13 23 15 17
## 4     b     2 19 31 21 23 33 25 27
## 5     c     2  3  9  4  5 10  6  7

当我要一个data.table特定解决方案时认为看到基础和dplyr等解决方案很聪明，可能会使这个问题吸引更广泛的读者。

While I'm asking for a data.table specific solution I think seeing base and dplyr etc. solutions that are clever may make this question appeal to a broader reader.

推荐答案

可能会更好方式

library(data.table)
setDT(dat)[, paste0("X", 1:6):= lapply(z, add, X0),
           ][, lapply(.SD, sum), by = .(fact1, fact2)]

#    fact1 fact2 X0 X1 X2 X3 X4 X5 X6
# 1:     b     2 19 31 21 23 33 25 27
# 2:     a     2  6 12  7  8 13  9 10
# 3:     b     1  9 21 11 13 23 15 17
# 4:     c     2  3  9  4  5 10  6  7
# 5:     a     1 18 42 22 26 46 30 34

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