使用 data.table 汇总多列 [英] Summarizing multiple columns with data.table
问题描述
我正在尝试使用 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 data.table 的新手.目前代码如下
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)
我想知道是否有比以下更有效的方法来汇总数据.
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]
我真的不想手动输入所有 50 列的计算,而且 eval(paste(...))
不知何故似乎很笨重.
I don't really want to type all 50 column calculations by hand and a eval(paste(...))
seems clunky somehow.
我查看了下面的示例,但对于我的需求来说似乎有点复杂.谢谢
I had a look at the example below but it seems a bit complicated for my needs. thanks
推荐答案
您可以使用带有 .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
如果您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
这当然不限于sum
,您可以使用lapply
的任何函数,包括匿名函数.(即,这是一个常规的 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,不需要使用 i=T
和 j= <..>
.我个人认为这会降低代码的可读性,但这只是一种风格偏好.
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.
参见 ?.SD
、?data.table
及其 .SDcols
参数,以及小插图 使用 .SD 进行数据分析.
See ?.SD
, ?data.table
and its .SDcols
argument, and the vignette Using .SD for Data Analysis.
也看看 data.table
常见问题解答 2.1.
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