将数据框中的日期与其他数据框中的两个日期进行比较

Compare a Date in a data frame with two dates in other data frame

我一直在阅读类似的帖子,但我无法使任何解决方案适用于我的情况(可能是因为我是 R 的新手)。

我有一个包含多个参数的长数据集,其中一个是日期,另一个数据框的日期间隔对应于特定值。我试图做一个可重现的例子:

df = data.frame(date=c("2017/08/01 19:00:00","2017/08/01 19:10:00","2017/08/01 19:20:00","2017/08/01 19:30:00",
                   "2017/08/01 19:40:00","2017/08/01 19:50:00","2017/08/01 20:00:00","2017/08/01 20:10:00"),
            factor1=c(10,15,11,13,14,12,16,15))

df2 = data.frame(start=c("2017/08/01 19:00:00","2017/08/01 19:40:00"),
             end=c("2017/08/01 19:15:00","2017/08/01 20:05:00"), factor2=c("A","B"))

df$date <- as.POSIXct(df$date) 
df2$start <- as.POSIXct(df2$start)
df2$end  <- as.POSIXct(df2$end)

我想要的结果是这样的:

result = data.frame(date=c("2017/08/01 19:00:00","2017/08/01 19:10:00","2017/08/01 19:20:00","2017/08/01 19:30:00",
                   "2017/08/01 19:40:00","2017/08/01 19:50:00","2017/08/01 20:00:00","2017/08/01 20:10:00"),
            factor1=c(10,15,11,13,14,12,16,15),factor2=c("A","A","NA","NA","B","B","B","NA"))

我试过 ifelse:

ifelse(df$date >= df2$start & df$date <= df2$end,df2$factor2,"NA")

但是无法让它工作。

有什么建议吗?

我尝试在 sqldf 中使用 inner join,它似乎有效:

library(sqldf)
df3 = sqldf("select df.*, df2.factor2 from df inner join df2 where df.date >= df2.start and df.date <= df2.end")
result = merge(df, df3, by = "date", all.x = TRUE)

(请注意,我也尝试过使用 left outer join 而不是 inner join,但这给了我与 inner join 相同的结果......这一定是 sqldf)

这对您的样本数据同样有效:

result <- df
result$factor2 <- NA
for (i in seq_along(df$date)){
  p <- ifelse(length(grep("TRUE", (df$date[i] >= df2$start & df$date[i] <= df2$end)))!=0,
              grep("TRUE", (df$date[i] >= df2$start & df$date[i] <= df2$end)),
              NA)
  result$factor2[i] <- ifelse(!is.na(p),
                          as.character(df2$factor2[p]),
                          "NA")
  }
print(result)
#                 date factor1 factor2
#1 2017-08-01 19:00:00      10       A
#2 2017-08-01 19:10:00      15       A
#3 2017-08-01 19:20:00      11      NA
#4 2017-08-01 19:30:00      13      NA
#5 2017-08-01 19:40:00      14       B
#6 2017-08-01 19:50:00      12       B
#7 2017-08-01 20:00:00      16       B
#8 2017-08-01 20:10:00      15      NA