R用data.table总结多个列 [英] R summarizing multiple columns with data.table

问题描述

我试图使用data.table来加速处理由几个较小的合并data.frames组成的大型data.frame（300k x 60）。我是新的data.table。目前的代码如下

I'm trying to use data.table to speed up processing of a large data.frame (300k x 60) made of several smaller merged data.frames. I'm new to data.table. The code so far is as follows

library(data.table)
a = data.table(index=1:5,a=rnorm(5,10),b=rnorm(5,10),z=rnorm(5,10))
b = data.table(index=6:10,a=rnorm(5,10),b=rnorm(5,10),c=rnorm(5,10),d=rnorm(5,10))
dt = merge(a,b,by=intersect(names(a),names(b)),all=T)
dt$category = sample(letters[1:3],10,replace=T)

我想知道是否有更有效的方法来总结数据。

and I wondered if there was a more efficient way than the following to summarize the data.

summ = dt[i=T,j=list(a=sum(a,na.rm=T),b=sum(b,na.rm=T),c=sum(c,na.rm=T),
                     d=sum(d,na.rm=T),z=sum(z,na.rm=T)),by=category]

我真的不想手动键入所有50列计算和 eval（粘贴（...）

I don't really want to type all 50 column calculations by hand and a eval(paste(...)) seems clunky somehow.

我看了下面的例子，但似乎有点复杂的我的需要。感谢

I had a look at the example below but it seems a bit complicated for my needs. thanks

如何跨多个列汇总data.table

推荐答案

您可以使用简单的 lapply .SD

You can use a simple lapply statement with .SD

dt[, lapply(.SD, sum, na.rm=TRUE), by=category ]

   category index        a        b        z         c        d
1:        c    19 51.13289 48.49994 42.50884  9.535588 11.53253
2:        b     9 17.34860 20.35022 10.32514 11.764105 10.53127
3:        a    27 25.91616 31.12624  0.00000 29.197343 31.71285

---

如果只想对某些列进行汇总，可以添加 .SDcols 参数

#  note that .SDcols also allows reordering of the columns
dt[, lapply(.SD, sum, na.rm=TRUE), by=category, .SDcols=c("a", "c", "z") ] 

   category        a         c        z
1:        c 51.13289  9.535588 42.50884
2:        b 17.34860 11.764105 10.32514
3:        a 25.91616 29.197343  0.00000

---

不限于 sum ，您可以使用 lapply 的任何函数，包括匿名函数。 （即，它是一个常规 lapply 语句）。

---

This of course, is not limited to sum and you can use any function with lapply, including anonymous functions. (ie, it's a regular lapply statement).

最后，没有必要使用 i = T 和 j = ..> 。就个人而言，我认为这使得代码的可读性更差，但它只是样式偏好。

Lastly, there is no need to use i=T and j= <..>. Personally, I think that makes the code less readable, but it is just a style preference.

？。<。$ .SD 和？的

帮助部分下的其他几个特殊变量[。data.table] （在Arguments部分中，查看的信息 c>）。

You will find the documentation to .SDand several other special variables under the
help section of ?"[.data.table" (in the Arguments section, look under the info for by).

data.table FAQ 2.1

Also have a look at data.table FAQ 2.1

http： //datatable.r-forge.r-project.org/datatable-faq.pdf

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