如何写一个R函数来旋转最后n分钟

由于您知道如何在列周围进行pivot_wider，我们只需要构造一个类似于列表的东西，其条目是相关日期周围的数据的子集.

相关日期是那些被验证的日期，并且在df内有59个先前值.它们可以通过以下方式获得.在我的示例中，我使用了您的数据，并额外将日期设置为09:02.

library(dplyr)

df |>
  filter(
    `Verified?` == 1 &
      dttm - as.difftime(59, units = "mins") > min(dttm),
    .by = ID
  ) |>
  pull(dttm)

# [1] "2023-01-01 09:00:00 CET" "2023-01-01 09:02:00 CET"

对于这样的VerifiedDate，相关数据子集可以通过以下方式获得:

df |> filter(between(
  dttm,
  VerifiedDate - as.difftime(59, units = "mins"),
  VerifiedDate
))

使用purrr::map将其组合在一起会产生所需的帧列表.现在，你可以在每个帧上使用旋转来获得所需的输出.

purrr::map(df |>
             filter(
               `Verified?` == 1 &
                 dttm - as.difftime(59, units = "mins") > min(dttm),
               .by = ID
             ) |>
             pull(dttm)
           , function (VerifiedDate) {
             df |> filter(between(
               dttm,
               VerifiedDate - as.difftime(59, units = "mins"),
               VerifiedDate
             ))
           })

#[[1]]
# A tibble: 60 × 4
#      ID dttm                Measurement `Verified?`
#   <int> <dttm>                    <int>       <int>
# 1     1 2023-01-01 08:01:00          90           0

...

#[[2]]
# A tibble: 60 × 4
#      ID dttm                Measurement `Verified?`
#   <int> <dttm>                    <int>       <int>
# 1     1 2023-01-01 08:03:00          92           0

所用数据:

> dput(df)
structure(list(ID = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L), dttm = structure(c(1672556400, 1672556460, 
1672556520, 1672556580, 1672556640, 1672556700, 1672556760, 1672556820, 
1672556880, 1672556940, 1672557000, 1672557060, 1672557120, 1672557180, 
1672557240, 1672557300, 1672557360, 1672557420, 1672557480, 1672557540, 
1672557600, 1672557660, 1672557720, 1672557780, 1672557840, 1672557900, 
1672557960, 1672558020, 1672558080, 1672558140, 1672558200, 1672558260, 
1672558320, 1672558380, 1672558440, 1672558500, 1672558560, 1672558620, 
1672558680, 1672558740, 1672558800, 1672558860, 1672558920, 1672558980, 
1672559040, 1672559100, 1672559160, 1672559220, 1672559280, 1672559340, 
1672559400, 1672559460, 1672559520, 1672559580, 1672559640, 1672559700, 
1672559760, 1672559820, 1672559880, 1672559940, 1672560000, 1672560060, 
1672560120, 1672560180), class = c("POSIXct", "POSIXt"), tzone = ""), 
    Measurement = c(89L, 90L, 96L, 92L, 98L, 88L, 86L, 91L, 94L, 
    100L, 81L, 82L, 95L, 90L, 87L, 91L, 89L, 90L, 96L, 92L, 98L, 
    88L, 86L, 91L, 94L, 100L, 81L, 82L, 95L, 90L, 87L, 91L, 89L, 
    90L, 96L, 92L, 98L, 88L, 86L, 91L, 94L, 100L, 81L, 82L, 95L, 
    90L, 87L, 91L, 89L, 90L, 96L, 92L, 98L, 88L, 86L, 91L, 94L, 
    100L, 81L, 82L, 95L, 90L, 87L, 91L), `Verified?` = c(0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
    0L, 1L, 0L)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-64L))