Question

我有一个包含事件日期的数据框，其ID为：

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

另外一个包含ID开头和结尾的时段：

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

对于每个id，我需要计算从第二个数据帧到第一个数据帧中每个日期所属的时间段数。

我想要的数据框是：

  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]

我的问题不是关于日期比较和结果求和。我的问题是关于在每个id组中执行这些分析。我猜有一种使用split和/或apply系列的方法，但是我没有找到方法。

如何在基准R中做到这一点？我在一个只能访问基本R的限制性环境中工作。

Answer 1

基本r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

另一种基本的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

在R中的两个数据框中按组比较日期

2 个答案: