基于来自其他列的条件，将数值替换为NA
问题描述：
这与以下问题相关：
以下是数据：
DT <- data.table(a = sample(c("C","M","Y","K"), 100, rep=TRUE),
b = sample(c("A","S"), 100, rep=TRUE),
f = round(rnorm(n=100, mean=.90, sd=.08),digits = 2) ); DT
我想对以下功能进行优雅和简洁的重写：
I would like an elegant and succinct re-write for the following functions:
`%between%` <- function(x, vals) { x >= vals[1] & x <= vals[2]}
`%nbetween%` <- Negate(`%between%`)
和以下脚本用NA替换满足特定条件的某些值
and the following script to replace a certain values that meet certain conditions with NA
DT[a == "C" & b %in% c("A", "S") & f %nbetween% c(.85, .95), f := NA]
DT[a == "M" & b %in% c("A", "S") & f %nbetween% c(.85, .95), f := NA]
DT[a == "Y" & b %in% c("A", "S") & f %nbetween% c(.80, .90), f := NA]
DT[a == "K" & b %in% c("A", "S") & f %nbetween% c(.95, 1.10), f := NA]
答
如果你将你的函数向量化，那么你可以使它更优雅一些：
If you vectorize your function, then you can make it a little more elegant:
`%between%` <- function(x, vals, vals2) x >= vals & x <= vals2
`%nbetween%` <- Negate(`%between%`)
# This will get you a nice ranges table.
ranges<-data.table(a=c('C','M','Y','K'),low=c(0.85,0.85,0.80,0.95),high=c(0.95,0.95,0.90,1.10))
# Set the keys for an easy merge.
setkeyv(ranges,'a')
setkeyv(DT,'a')
# Merge and filter.
DT<-merge(DT,ranges,all.x=TRUE)[b %in% c('A','S') & `%nbetween%`(f,low,high),f:=NA ]
# A nice suggestion from the comments:
DT<-DT[ranges][b %in% c('A','S') & `%nbetween%`(f,low,high),f:=NA]
# a b f low high
# 1: C S 0.88 0.85 0.95
# 2: C S NA 0.85 0.95
# 3: C S 0.92 0.85 0.95
# 4: C A 0.94 0.85 0.95
# 5: C S NA 0.85 0.95
# 6: C S 0.90 0.85 0.95