我有一个大型数据集,其开始日期和结束日期有时在一个月内,但更常见的是跨度超过一个月或一年。最终,我想统计每个ID每个月的入住天数。
这里是示例数据:
ID = c(50:55)
ENTRY = as.Date(c("11/6/2011", "04/08/2012", "10/9/2012",
"23/10/2012", "15/11/2012", "23/11/2012"), "%d/%m/%Y")
EXIT = as.Date(c("11/7/2011", "06/09/2012", "24/9/2012",
"31/12/2012", "18/11/2012", "04/01/2013"), "%d/%m/%Y")
Occupancy <- data.frame(ID, ENTRY, EXIT)
ID ENTRY EXIT
50 2011-06-11 2011-07-11
51 2012-08-04 2012-09-06
52 2012-09-10 2012-09-24
53 2012-10-23 2012-12-31
54 2012-11-15 2012-11-18
55 2012-11-23 2013-01-04
这就是我想要创建的:
ID ENTRY EXIT
50 6/11/2011 6/30/2011
50 7/1/2011 7/11/2011
51 8/4/2012 8/31/2012
51 9/1/2012 9/6/2012
:
55 11/23/2012 11/30/2012
55 12/1/2012 12/31/2012
55 1/1/2013 1/4/2013
如有任何建议,我们将不胜感激!
最佳答案
希望这有帮助!
它将为您提供最终结果 - 即每个 ID 每月的入住天数。
ID = c(50:55)
ENTRY = as.Date(c("11/6/2011", "04/08/2012", "10/9/2012",
"23/10/2012", "15/11/2012", "23/11/2012"), "%d/%m/%Y")
EXIT = as.Date(c("11/7/2011", "06/09/2012", "24/9/2012",
"31/12/2012", "18/11/2012", "04/01/2013"), "%d/%m/%Y")
Occupancy <- data.frame(ID, ENTRY, EXIT)
library(zoo)
library(dplyr)
monthList <- mapply(function(x,y) as.yearmon(seq(x,y, "day")), ENTRY, EXIT)
OccupancyDf <- monthList %>% lapply(table) %>% lapply(as.list) %>% lapply(data.frame) %>% rbind_all()
OccupancyDf$ID <- Occupancy$ID
OccupancyDf[is.na(OccupancyDf)] <- 0
OccupancyDf
输出是:
Jun.2011 Jul.2011 Aug.2012 Sep.2012 Oct.2012 Nov.2012 Dec.2012 Jan.2013 ID
20 11 0 0 0 0 0 0 50
0 0 28 6 0 0 0 0 51
0 0 0 15 0 0 0 0 52
0 0 0 0 9 30 31 0 53
0 0 0 0 0 4 0 0 54
0 0 0 0 0 8 31 4 55
如果它解决了您的问题,请不要忘记告诉我们:)
关于r - 当范围变化时,按月从 df 中提取开始和结束日期,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/45443982/