多个块命令的矢量化if-else

时间:2012-09-25 20:54:24

标签: r if-statement

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?

2 个答案:

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,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。