r-确定一个月的哪一天是否在一个日期范围内，与年份无关

Question

如果我有一个开始日期和结束日期的时间范围，我可以很容易地确定特定日期是否在这个时间范围内。我们如何确定一个特定的月/日组合是否在一个时间范围内，与年份无关。

示例

我想知道七月一日(07-01(是否在一个时间范围内。

2020-01-30 - 2020-06-15  --> NO
2020-06-16 - 2021-03-20  --> YES
2013-04-26 - 2019-02-13  --> YES (multiple)

R代码示例

# set seed for sampling
set.seed(1)
# number of time ranges
cases <- 10
# time gaps in days
gaps <- sort(sample(x = 1:5000, size = cases, replace = TRUE))
# data frame with time ranges
df <- data.frame(dates_start = rev(Sys.Date() - gaps[2:cases] + 1),
                 dates_end   = rev(Sys.Date() - gaps[1:(cases-1)]))
df
#>   dates_start  dates_end
#> 1  2009-06-26 2010-01-19
#> 2  2010-01-20 2011-06-05
#> 3  2011-06-06 2011-06-20
#> 4  2011-06-21 2013-04-21
#> 5  2013-04-22 2016-02-17
#> 6  2016-02-18 2016-08-05
#> 7  2016-08-06 2018-05-11
#> 8  2018-05-12 2019-10-09
#> 9  2019-10-10 2021-10-25
# Is specific date in date range
df$date_in_range <- df$dates_start <= lubridate::ymd("2019-07-01") & 
                                      lubridate::ymd("2019-07-01") < df$dates_end
# specific day of a month in date range
# pseudo code
data.table::between(x = month_day("07-01"),
                    lower = dates_start,
                    upper = dates_end)
#> Error in month_day("07-01"): could not find function "month_day"
# expected output
df$monthday_in_range <- c(T, T, F, T, T, T, T, T, T)
df
#>   dates_start  dates_end date_in_range monthday_in_range
#> 1  2009-06-26 2010-01-19         FALSE              TRUE
#> 2  2010-01-20 2011-06-05         FALSE              TRUE
#> 3  2011-06-06 2011-06-20         FALSE             FALSE
#> 4  2011-06-21 2013-04-21         FALSE              TRUE
#> 5  2013-04-22 2016-02-17         FALSE              TRUE
#> 6  2016-02-18 2016-08-05         FALSE              TRUE
#> 7  2016-08-06 2018-05-11         FALSE              TRUE
#> 8  2018-05-12 2019-10-09          TRUE              TRUE
#> 9  2019-10-10 2021-10-25         FALSE              TRUE

Answer 1

更新2

dplyr/data.table独立函数

md_in_interval <- function(md, start, end) {
  # does the interval cover more than a full year? 
  # Then any date will fall in this interval and hence the result is TRUE
  helper <- (lubridate::year(end) - lubridate::year(start)) > 1
  
  # lubridate time interval
  interval <- lubridate::interval(dates_start, dates_end)
  
  # helper dates with month/day combination and start year
  my_date1 <- lubridate::mdy(paste0(md, lubridate::year(start)))
  # helper dates with month/day combination and end year
  my_date2 <- lubridate::mdy(paste0(md, lubridate::year(end)))
  
  # check if month/day combination falls within the interval
  out <- my_date1 %within% interval | 
    my_date2 %within% interval | 
    helper 
  
  return(out)
  
}

与数据一起使用。table

library(data.table)
dt <- data.table::as.data.table(df)
dt[, isin := md_in_interval("06-05", dates_start, dates_end)][]

更新

为了解决跨度超过一年的问题，我们可以使用一个辅助列：

df %>% 
  mutate(across(, ymd),
         helper = ifelse(year(dates_end) - year(dates_start) > 1, 1, 0),
         interval = interval(dates_start, dates_end)) %>% 
  mutate(my_date1 = mdy(paste0("07-01-",year(dates_start))),
         my_date2 = mdy(paste0("07-01-",year(dates_end)))) %>% 
  mutate(check = my_date1 %within% interval | my_date2 %within% interval | helper == 1) %>% 
  select(1,2,7)

  dates_start  dates_end check
1  2009-06-26 2010-01-19  TRUE
2  2010-01-20 2011-06-05  TRUE
3  2011-06-06 2011-06-20 FALSE
4  2011-06-21 2013-04-21  TRUE
5  2013-04-22 2016-02-17  TRUE
6  2016-02-18 2016-08-05  TRUE
7  2016-08-06 2018-05-11  TRUE
8  2018-05-12 2019-10-09  TRUE
9  2019-10-10 2021-10-25  TRUE

第一个答案：

我们可以使用lubridate。

1. 我们用interval创建一个区间，然后我们

2. 我们用%以内的%来检查一天是否在间隔中。

3. 在此之前，我们必须创建一个07-01元素的年月日。我们使用mdy(paste0("07-01-",year(dates_start)))

library(dplyr)
library(lubridate)
df %>% 
  mutate(across(, ymd),
         interval = interval(dates_start, dates_end)) %>% 
  mutate(my_date = mdy(paste0("07-01-",year(dates_start)))) %>% 
  mutate(check = my_date %within% interval)

  dates_start  dates_end                       interval    my_date check
1  2009-06-26 2010-01-19 2009-06-26 UTC--2010-01-19 UTC 2009-07-01  TRUE
2  2010-01-20 2011-06-05 2010-01-20 UTC--2011-06-05 UTC 2010-07-01  TRUE
3  2011-06-06 2011-06-20 2011-06-06 UTC--2011-06-20 UTC 2011-07-01 FALSE
4  2011-06-21 2013-04-21 2011-06-21 UTC--2013-04-21 UTC 2011-07-01  TRUE
5  2013-04-22 2016-02-17 2013-04-22 UTC--2016-02-17 UTC 2013-07-01  TRUE
6  2016-02-18 2016-08-05 2016-02-18 UTC--2016-08-05 UTC 2016-07-01  TRUE
7  2016-08-06 2018-05-11 2016-08-06 UTC--2018-05-11 UTC 2016-07-01 FALSE
8  2018-05-12 2019-10-09 2018-05-12 UTC--2019-10-09 UTC 2018-07-01  TRUE
9  2019-10-10 2021-10-25 2019-10-10 UTC--2021-10-25 UTC 2019-07-01 FALSE

Answer 2

您可以尝试

library(lubridate)
library(dplyr)
df %>%
  rowwise %>%
  mutate(monthday_in_range = 7 %in% month(seq(floor_date(dates_start, "month"), dates_end, by = "month")))
  dates_start dates_end  monthday_in_range
  <date>      <date>     <lgl>            
1 2009-06-26  2010-01-19 TRUE             
2 2010-01-20  2011-06-05 TRUE             
3 2011-06-06  2011-06-20 FALSE            
4 2011-06-21  2013-04-21 TRUE             
5 2013-04-22  2016-02-17 TRUE             
6 2016-02-18  2016-08-05 TRUE             
7 2016-08-06  2018-05-11 TRUE             
8 2018-05-12  2019-10-09 TRUE             
9 2019-10-10  2021-10-25 TRUE 

添加

df %>%
  rowwise %>%
  mutate(monthday_in_range = 7 %in% month(seq(ymd(paste0(substr(dates_start, 1, 8), "13")), dates_end, by = "month")))