Question

这与之前的问题有关，可以在以下网址找到：

Replace a numerical value by NA based on conditions from other columns:

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

我希望对以下功能进行优雅而简洁的重写：

`%between%` <- function(x, vals) { x >= vals[1] & x <= vals[2]}
`%nbetween%` <- Negate(`%between%`)

和以下脚本用NA

替换满足某些条件的某些值

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]

Answer 1

如果你对你的功能进行矢量化，那么你可以使它更优雅：

`%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

根据其他列的条件将数值替换为NA

1 个答案: