获取 Data.table 中的日期差异

Question

我想知道如何获得date difference的two column在data.table使用lapply中data.table？

library(data.table)
  dt <- fread(" ID          Date        ME_Mes     DOB
 A     2017-02-20  0.0000 2016-08-19
             B      2017-02-06  2.3030 2016-03-11
             C     2017-03-20  0.4135 2016-08-19
             D      2017-03-06  0.0480 2016-10-09
             E     2017-04-20  2.4445 2016-05-04")
> dt
   ID       Date ME_Mes        DOB
1:  A 2017-02-20 0.0000 2016-08-19
2:  B 2017-02-06 2.3030 2016-03-11
3:  C 2017-03-20 0.4135 2016-08-19
4:  D 2017-03-06 0.0480 2016-10-09
5:  E 2017-04-20 2.4445 2016-05-04

###I'd like to calculate the difference in weeks for every ID by comparing the DOB-Date. 

我累了以下几点：

dt[,lapply(.SD, diff.Date), .SDcols = c(4,2), ID] # but did not work!

Answer 1

您可以使用difftime来获得以周为单位的差异。虽然，您需要将列转换为POSIXct.

如果您想保持列的类别不变，则可以这样做：

dt[, "DOB_Date" := difftime(strptime(dt$Date, format = "%Y-%m-%d"),
                        strptime(dt$DOB,  format = "%Y-%m-%d"), units = "weeks")]

dt
##    ID       Date ME_Mes        DOB       DOB_Date
## 1:  A 2017-02-20 0.0000 2016-08-19 26.43452 weeks
## 2:  B 2017-02-06 2.3030 2016-03-11 47.42857 weeks
## 3:  C 2017-03-20 0.4135 2016-08-19 30.42857 weeks
## 4:  D 2017-03-06 0.0480 2016-10-09 21.14881 weeks
## 5:  E 2017-04-20 2.4445 2016-05-04 50.14286 weeks

但是，正如@Frank建议的那样，最好先将日期列转换（“覆盖”）为POSIXct类。