相当于tidyr :: complete()的data.table [英] data.table equivalent of tidyr::complete()
问题描述
tidyr :: complete()
将行添加到 data.frame
中,以获取缺少的列值组合从数据。示例:
tidyr::complete()
adds rows to a data.frame
for combinations of column values that are missing from the data. Example:
library(dplyr)
library(tidyr)
df <- data.frame(person = c(1,2,2),
observation_id = c(1,1,2),
value = c(1,1,1))
df %>%
tidyr::complete(person,
observation_id,
fill = list(value=0))
收益率
# A tibble: 4 × 3
person observation_id value
<dbl> <dbl> <dbl>
1 1 1 1
2 1 2 0
3 2 1 1
4 2 2 1
其中 person == 1
和<$组合的值
df
中缺少的c $ c> observation_id == 2 的值为0。
where the value
of the combination person == 1
and observation_id == 2
that is missing in df
has been filled in with a value of 0.
在 data.table
中相当于什么?
推荐答案
我认为data.table的原理所包含的任务专用功能比在tidyverse中所发现的要少,因此需要一些额外的编码,例如:
I reckon that the philosophy of data.table entails fewer specially-named functions for tasks than you'll find in the tidyverse, so some extra coding is required, like:
res = setDT(df)[
CJ(person = person, observation_id = observation_id, unique=TRUE),
on=.(person, observation_id)
]
此后,您仍然必须手动处理缺失级别的值。我们可以使用 setnafill
有效地处理& data.table
的最新版本中的引用:
After this, you still have to manually handle the filling of values for missing levels. We can use setnafill
to handle this efficiently & by-reference in recent versions of data.table
:
setnafill(res, fill = 0, cols = 'value')
See @Jealie's answer regarding a feature that will sidestep this.
当然,必须输入三个列名真是太疯狂了在这里的时间。但另一方面,可以编写一个包装器:
Certainly, it's crazy that the column names have to be entered three times here. But on the other hand, one can write a wrapper:
completeDT <- function(DT, cols, defs = NULL){
mDT = do.call(CJ, c(DT[, ..cols], list(unique=TRUE)))
res = DT[mDT, on=names(mDT)]
if (length(defs))
res[, names(defs) := Map(replace, .SD, lapply(.SD, is.na), defs), .SDcols=names(defs)]
res[]
}
completeDT(setDT(df), cols = c("person", "observation_id"), defs = c(value = 0))
person observation_id value
1: 1 1 1
2: 1 2 0
3: 2 1 1
4: 2 2 1
作为避免在第一步中重复键入名称的快速方法,这是@thelatemail的想法:
As a quick way of avoiding typing the names three times for the first step, here's @thelatemail's idea:
vars <- c("person","observation_id")
df[do.call(CJ, c(mget(vars), unique=TRUE)), on=vars]
# or with magrittr...
c("person","observation_id") %>% df[do.call(CJ, c(mget(.), unique=TRUE)), on=.]
更新:由于@MichaelChirico& ;;现在您无需在CJ中两次输入名称。 @MattDowle,用于改进。
Update: now you don't need to enter names twice in CJ thanks to @MichaelChirico & @MattDowle for the improvement.
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