在R中的兩個數據幀中按組比較日期

Question

我有一個數據框，其中包含id的事件日期：

data.frame(id = c("a", "a", "a", "d", "d"),
           date = as.Date(c("2018-01-03", "2018-02-02", "2018-02-22", "2018-02-13", "2018-05-01")))

  id       date
1  a 2018-01-03
2  a 2018-02-02
3  a 2018-02-22
4  d 2018-02-13
5  d 2018-05-01

另一個包含id的開始和結束時段：

data.frame(id = c("a", "a", "d", "d", "d", "d"),
           start = as.Date(c("2018-01-15", "2018-01-30", "2018-03-01", "2018-02-01", "2018-04-02", "2018-03-19")),
           end = as.Date(c("2018-01-18", "2018-02-10", "2018-03-03", "2018-04-22", "2018-05-23", "2018-08-29")))

  id      start        end
1  a 2018-01-15 2018-01-18
2  a 2018-01-30 2018-02-10
3  d 2018-03-01 2018-03-03
4  d 2018-02-01 2018-04-22
5  d 2018-04-02 2018-05-23
6  d 2018-03-19 2018-08-29

對於每個id，我需要計算第一個數據幀中每個日期所屬的第二個數據幀的周期數。

我想要的數據框架是：

  id       date n
1  a 2018-01-03 0    # does not belong to any period
2  a 2018-02-02 1    # belongs to [2018-01-30,2018-02-10]
3  a 2018-02-22 0    # does not belong to any period
4  d 2018-02-13 1    # belongs to [2018-02-01,2018-04-22]
5  d 2018-05-01 2    # belongs to [2018-04-02,2018-05-23] and [2018-03-19,2018-08-29]

我的問題不是關於日期比較和總結結果。 我的問題是在每個id組中執行這些分析。 我想有一種方法可以使用split和/或apply系列，但我沒有找到。

我怎么能在基地R做？ 我在一個限制性的環境中工作，我只能訪問基地R.

Answer 1

基礎方法

temp <- subset( merge(df1, df2), date >= start & date <= end, select = "date" )
df1$n <- sapply( df1$date, function(x) length( temp$date[ temp$date == x ] ))

#   id       date n
# 1  a 2018-01-03 0
# 2  a 2018-02-02 1
# 3  a 2018-02-22 0
# 4  d 2018-02-13 1
# 5  d 2018-05-01 2

Answer 2

另一個基礎R方法：

dates <- data.frame(id = c("a", "a", "a", "d", "d"),
                    date = as.Date(c("2018-01-03", "2018-02-02", "2018-02-22", "2018-02-13", "2018-05-01")))
periods <- data.frame(id = c("a", "a", "d", "d", "d", "d"),
                      start = as.Date(c("2018-01-15", "2018-01-30", "2018-03-01", "2018-02-01", "2018-04-02", "2018-03-19")),
                      end = as.Date(c("2018-01-18", "2018-02-10", "2018-03-03", "2018-04-22", "2018-05-23", "2018-08-29")))

df <- transform(merge(dates, periods), belongs = date >= start & date <= end)

aggregate(belongs ~ date + id, data = df, sum)
#         date id belongs
# 1 2018-01-03  a       0
# 2 2018-02-02  a       1
# 3 2018-02-22  a       0
# 4 2018-02-13  d       1
# 5 2018-05-01  d       2

或者使用data.table ：

library(data.table)
dt <- as.data.table(merge(dates, periods))
dt[, .(n = sum(date >= start & date <= end)), by=c("id","date")]
#    id       date n
# 1:  a 2018-01-03 0
# 2:  a 2018-02-02 1
# 3:  a 2018-02-22 0
# 4:  d 2018-02-13 1
# 5:  d 2018-05-01 2