如何用R语言if/else if/else及data.table创建多条件汇总列

需求规则 #

• 4个Condition全为1时，赋值5
• 3个Condition为1时，赋值4
• Condition3和Condition4均为1时，赋值3
• 仅Condition1为1时，赋值2
• 仅Condition3为1时，赋值1
• 无符合条件时，赋值0

测试数据集 #

dt <- data.table(ID=c(1,2,3,4,5,6),
                 Condition1=c(1,0,1,1,0,0),
                 Condition2=c(0,0,0,1,0,0),
                 Condition3=c(0,1,1,1,0,1), 
                 Condition4=c(0,1,1,1,0,0))
str(dt)
# 输出：
#  $ ID        : num  1 2 3 4 5 6
#  $ Condition1: num  1 0 1 1 0 0
#  $ Condition2: num  0 0 0 1 0 0
#  $ Condition3: num  0 1 1 1 0 1
#  $ Condition4: num  0 1 1 1 0 0

期望结果 #

str(dt)
# 输出：
#  $ ID        : num  1 2 3 4 5 6
#  $ Condition1: num  1 0 1 1 0 0
#  $ Condition2: num  0 0 0 1 0 0
#  $ Condition3: num  0 1 1 1 0 1
#  $ Condition4: num  0 1 1 1 0 0
#  $ Summary   : num  2 3 4 5 0 1

错误代码分析 #

你尝试的if/else if/else代码存在两个核心问题：

1. 普通if/else是标量判断，无法处理data.table的向量列，会导致只返回一个值而非每行对应的值；
2. 代码中存在拼写错误：Condition32应为Condition2。

dt$Summary <- if(c(dt$Condition1 == 1 & dt$Condition2 == 1 & dt$Condition3 == 1 & dt$Condition4 == 1)){
  print("5")
} else if (c(dt$Condition1 == 1 & dt$Condition32 == 1 & dt$Condition4 == 1)){
  print("4")
} else if (c(dt$Condition3 == 1 & dt$Condition4 == 1)){
  print("3")
} else if (dt$Condition1==1){
  print("2")
} else if (dt$Condition3==1){
  print("1")
} else {
  "0"
}

正确的data.table解决方案 #

方法1：使用data.table原生:=结合嵌套fifelse #

fifelse是data.table提供的向量版ifelse，支持逐行判断：

dt[, Summary := fifelse(Condition1 == 1 & Condition2 == 1 & Condition3 == 1 & Condition4 == 1, 5,
                        fifelse(rowSums(.SD) == 3, 4,
                                fifelse(Condition3 == 1 & Condition4 == 1, 3,
                                        fifelse(Condition1 == 1 & Condition2 == 0 & Condition3 == 0 & Condition4 == 0, 2,
                                                fifelse(Condition3 == 1 & Condition1 == 0 & Condition2 == 0 & Condition4 == 0, 1, 0))))),
   .SDcols = Condition1:Condition4]

方法2：结合dplyr::case_when（兼容data.table） #

如果熟悉case_when的语法，可用于简化多条件逻辑，直接嵌入data.table的赋值操作：

library(dplyr)
dt[, Summary := case_when(
  Condition1 == 1 & Condition2 == 1 & Condition3 == 1 & Condition4 == 1 ~ 5,
  rowSums(.SD) == 3 ~ 4,
  Condition3 == 1 & Condition4 == 1 ~ 3,
  Condition1 == 1 & Condition2 == 0 & Condition3 == 0 & Condition4 == 0 ~ 2,
  Condition3 == 1 & Condition1 == 0 & Condition2 == 0 & Condition4 == 0 ~ 1,
  TRUE ~ 0
), .SDcols = Condition1:Condition4]

关键注意点 #

• 规则判断有优先级：比如"3个Condition为1"的逻辑要放在"Condition3和Condition4均为1"之前，避免被后者覆盖；
• 对于"仅某一个Condition为1"的情况，必须明确其他条件为0，防止和多条件场景冲突；
• .SDcols = Condition1:Condition4用于指定计算行和的列范围，适合列数较多的复杂数据集。

内容的提问来源于stack exchange，提问作者Svenja