我正在寻找一种基于单个条件语句执行多个变量赋值的方法。 ifelse函数一次执行我想要的单个变量,但我希望能够基于单个条件执行一个语句块。
以下是一些简化的示例代码:
within(mydata, {
if (gender == "f") {
test1 <- 1
test2 <- 2
} else {
test1 <- 0
test2 <- 0
}
test3 <- gender
test4 <- ifelse(gender == "f", 1, 0)
test5 <- ifelse(gender == "f", 2, 0)
})
其中给出了以下输出:
workshop gender q1 q2 q3 q4 test5 test4 test3 test2 test1
1 1 f 1 1 5 1 2 1 f 2 1
2 2 f 2 1 4 1 2 1 f 2 1
3 1 f 2 2 4 3 2 1 f 2 1
4 2 f 3 1 NA 3 2 1 f 2 1
5 1 m 4 5 2 4 0 0 m 2 1
6 2 m 5 4 5 5 0 0 m 2 1
7 1 m 5 3 4 4 0 0 m 2 1
8 2 m 4 5 5 5 0 0 m 2 1
Warning message:
In if (gender == "f") { :
the condition has length > 1 and only the first element will be used
当我运行此代码时,正确分配了test4和test5,但是错误地分配了test1和test2,因为if语句仅返回第一行的值。有没有办法做我正在尝试使用test1和test2 - 基于单个条件为数据帧的每一行运行多个语句?
我知道我可以用ifelse完成相同的结果,但我希望能够将这些语句组合在一起,以便在阅读我的代码时清晰。
例如,我希望能够按行动对我所做的储蓄计算进行分组,如下所示:
a.lighting.all.3 <- within(a.lighting.all.3, {
if (measure.subcategory %in% c('HID to Linear Fluorescent Retrofit',
'Hardwired CFL', 'Induction Lighting',
'Screw-In CFL', 'Specialty Screw-In CFL',
'T12 to Premium T8/T5', 'T12 to Standard T8/T5',
'T8 to Premium T8', 'T12/T8 Delamping')) {
kw.nc.v <- (base.watts - ee.watts) / 1000 * (1 + dif) * df * quantity
kwh.v <- (base.watts - ee.watts) / 1000 * (1 + eif) * op.hrs * quantity
} else if (measure.subcategory == 'Traffic Signals') {
kw.nc.v <- (base.watts - ee.watts) / 1000 * quantity
kwh.v <- (base.watts - ee.watts) / 1000 * op.hrs * quantity
} else if (measure.subcategory == 'Exit Sign Retrofit') {
} else if (measure.subcategory %in% c('LED Channel Lights',
'Cold Cathode FL')) {
} else if (measure.subcategory %in% c('Daylighting Controls',
'Occupancy Sensors')) {
} else if (measure.subcategory == 'Lighting Power Density') {
} else if (measure.subcategory == 'LED Lighting') {
}
})
或者按度量分配参数集,例如:
a.lighting.all.3 <- within(a.lighting.all.3, {
switch(as.character(measure.subcategory),
"T8 to Premium T8" = {
op.hrs <- 4481
cf <- 0.93
},
"Cold Cathode FL" = {
op.hrs <- 6400
cf <- 1
},
"Exit Sign Retrofit" = {
op.hrs <- 8760
cf <- 1
},
"LED Channel Lights" = {
op.hrs <- 5110
cf <- 0.134
},
"Traffic Signals" = {
op.hrs <- ifelse(grepl("Green", measure), 3679, 4818)
df <- ifelse(grepl("Green", measure), 0.42, 0.55)
cf <- 1
},
"Daylighting Controls" = {
dsf <- esf <- 0.54 # daylight savings fraction
},
"Occupancy Sensors" = {
dsf <- 0.16 # demand savings fraction
esf <- 0.39 # energy savings fraction
},
"LED Lighting" = {
if (measure %in% c("Pedestrian NO countdown",
"Pedestrian W/ countdown")) {
cf <- 1
op.hrs <- ifelse(measure == "Pedestrian W/ countdown", 6483, 5432)
op.hrs.base <- 5432
df <- ifelse(measure == "Pedestrian W/ countdown", 0.74, 0.62)
df.base <- 0.62
} else if (measure %in% c("Refrigerated Case LED Lamps NO motion Sensors",
"Refrigerated Case LED Lamps W/ motion Sensors")) {
cf <- 1
dif <- 0.25
eif <- 0.25
op.hrs.base <- 8634
op.hrs <- ifelse(measure == "Refrigerated Case LED Lamps W/ motion Sensors",
6043, 8634)
}
}
)
})
有什么想法吗?
答案 0 :(得分:2)
d <- data.frame(workshop=rep(1:2,4),
gender=rep(c("f","m"),each=4))
我不知道这个答案是否会让您满意,但是:如果您使用plyr
来操作代码的块,您可以使用{{{{{{ 1}}陈述。
if
请注意,这会将您的数据按性别重新排列为块(在此示例中,它不会更改任何内容),这可能是不受欢迎的......
我没有在我的示例中包含其他变量,但它们将被正确地传播。
答案 1 :(得分:2)
用于时间和内存效率以及编码优雅的data.table解决方案
library(data.table)
DT <- as.data.table(d)
DT[, `:=`(paste0('test',1:5), list((1:0)[gender],
(c(2,0))[gender], gender, (1:0)[gender], (1:0)[gender])), with = F]
:=
将通过引用分配,如果LHS
参数是名称的字符向量(要创建),并且RHS是包含要使用的值的列表,则可以为多列工作。
此解决方案还利用gender
是因子变量的事实,我们可以使用基础整数值来引用重新编码。
您也可以执行类似
的操作setkey(|Dt, gender)
DT['f', test1 := 1]
DT['m', test1 := 0]
DT['f', test2 := 2]
DT['m', test2 := 0]
DT[,test3 := gender]
# etc
如果性别不是因素,则会发出警告,但仍然有效。