在另一个data.frame（data.table）中查找一个data.frame的对应日期

由于这是我关于stackoverflow的第一个问题，我希望它满足所有要求。下面是一个可复制的例子。两个data.table（包含月度数据）和一个data.table（提供相应日期）

首先，我想检查dt_list1和dt_list2的日期是否在dt_Dates_的相应日期值的时间范围内（变量：in.period）

问题在于，比较必须满足以下几个条件：

• 如果是>存储<1或2，则应检查>日期<是否在>存储<1或2的>日期<的时间范围内
• 如果是>存储<3，则应检查>日期<是否在>区域城市<1的>日期<的时间范围内
• 如果是>地区面试官<1，则应检查>日期<是否在>地区日期<的时间范围内
• 如果是>地区面试官<2或3，则应检查>日期<是否在>地区城市<0的>日期<的时间范围内
• 对于>区域区域城市<1的>日期<是否在>日期<的时间范围内
• 对于剩余的>区域区域日期<是否在>日期<的时间范围内

库（data.table）
清单1
library(data.table)

list1 <- data.table(
  Month = rep(1, 500), 
  Region = sample(c("A", "B", "C"), 500, replace = T, prob = c(0.25, 0.25, 0.5)),
  Store = sample(seq(1:7), 500, replace = T), 
  Interviewer = sample(seq(1:9), 500, replace = T),
  Sale = sample(c(TRUE, FALSE), 500, replace = T, prob = c(0.25, 0.75)),
  Date = sample(seq(as.Date('2020/01/01'), as.Date('2020/01/13'), by="day"), 500, replace = T),
  Day = NA,
  Within.Period = NA,
)

list2 <- data.table(
  Month = rep(2, 600), 
  Region = sample(c("A", "B", "C"), 600, replace = T, prob = c(0.25, 0.25, 0.5)),
  Store = sample(seq(1:8), 600, replace = T), 
  Interviewer = sample(seq(1:10), 600, replace = T),
  Sale = sample(c(TRUE, FALSE), 600, replace = T, prob = c(0.25, 0.75)),
  Date = sample(seq(as.Date('2020/02/02'), as.Date('2020/02/14'), by="day"), 600, replace = T),
  Day = NA,
  Within.Period = NA
)

list1 <- list1[with(list1,
                    order(Region, Store, Interviewer, Sale, Date))]

list2 <- list1[with(list2,
                    order(Region, Store, Interviewer, Sale, Date))]

dates <- data.table(
  Region = c(rep(NA, 4), "A", "A", "B", "B", "C", "C", "C", "C"),
  City = c(rep(NA, 8), 0, 0, 1, 1),
  Store = c(1, 1, 2, 2, rep(NA, 8)),
  Month = rep(c(1,2), 6),
  Sale.Date = as.Date(c("02.01", "03.02", "03.01", "04.02", "03.01", "04.02", "06.01", "07.02", "09.01", "10.02", "09.01", "10.02"), format = "%d.%m"),
  Day.1 = as.Date(c("01.01", "02.02", "02.01", "03.02", "02.01", "03.02", "05.01", "06.02", "08.01", "09.02", "08.01", "09.02"), format = "%d.%m"),
  Day.2 = as.Date(c(rep(NA, 2),"03.01", "04.02", "03.01", "04.02", "06.01", "07.02", "09.01", "10.02", "09.01", "10.02"), format = "%d.%m"),
  Day.3 = as.Date(c(rep(NA, 4), "04.01", "05.02", "07.01", "08.02", "10.01", "11.02", "10.01", "11.02"), format = "%d.%m"),
  Day.4 = as.Date(c(rep(NA, 6), "08.01", "09.02", "11.01", "12.02", "11.01", "12.02"), format = "%d.%m"),
  Day.5 = as.Date(c(rep(NA, 10), "12.01","13.02"), format = "%d.%m")
)

dates_melted <- melt(dates, id.vars = c("Region", "City", "Store", "Month", "Sale.Date"), variable.name = "Day", value.name = "Date", na.rm = TRUE)
´´´

dt_list1$Within.Period <- with(dt_list1, Store == "3" & ifelse(Sale == FALSE, Date %in% dt_dates_melted$Dates[dt_dates_melted$Region == "C" & dt_dates_melted$City == 1], Date %in% dt_dates_melted$Sale.Dates[dt_dates_melted$Region == "C" & dt_dates_melted$City == 1]))
´´´

dt_list1$Within.Period <- with(dt_list1, Store %in% dt_dates_melted$Store & ifelse(Sale == FALSE, Date %in% dt_dates_melted$Dates[!is.na(dt_dates_melted$Store)], Date %in% dt_dates_melted$Sale.Dates[!is.na(dt_dates_melted$Store)]))

´´´