如何使用r中“下一个”组的第一个值？

我将使用自联接来获取response下一组的第一个：

library(tidyverse)

# the OPs example data (long!)
zero_test <-
  structure(
    list(
      time = structure(
        c(
          1564468200,
          1564475400,
          1564484400,
          1564486200,
          1564493400,
          1564497000,
          1564498800,
          1564506000,
          1564509600,
          1564511400,
          1564518600,
          1564522200,
          1564524000,
          1564527600,
          1564531200
        ),
        class = c("POSIXct", "POSIXt"),
        tzone = "UTC"
      ),
      type = c(
        "current_std",
        "n2",
        "n2",
        "current_std",
        "n2",
        "-",
        "current_std",
        "-",
        "n2",
        "current_std",
        "n2",
        "-",
        "current_std",
        "-",
        "-"
      ),
      ben = c(
        2293951.5,
        12703.1,
        6392.7,
        1762512.6,
        10748.4,
        25468.3,
        1597679,
        24400.4,
        6019.4,
        1510760.2,
        10329.1,
        29292.6,
        1495942.8,
        61227.5,
        25379.5
      ),
      xyl = c(
        210975.6,
        4482,
        2910.8,
        127612.4,
        3792.6,
        10295.7,
        113439.1,
        10628.8,
        2064.3,
        107134.3,
        3764.1,
        10380.6,
        107353.6,
        23639.1,
        10317.4
      ),
      cym = c(
        546894.5,
        12202.6,
        8400.8,
        302091.6,
        11072.2,
        16349.2,
        291637.5,
        18891.8,
        6500.7,
        276997.5,
        10821.2,
        18672,
        274149.4,
        61379.2,
        19254.7
      ),
      isop = c(
        397288.2,
        0,
        0,
        239779.9,
        0,
        1364.8,
        199081.5,
        1511.2,
        0,
        179364,
        0,
        1318.4,
        174450.7,
        7137.5,
        9567
      ),
      macr = c(
        221195.8,
        0,
        0,
        138806.3,
        0,
        0,
        116644,
        0,
        0,
        108893.3,
        0,
        0,
        105689,
        4325.4,
        0
      ),
      pin = c(
        50795.3,
        0,
        0,
        28436,
        0,
        1020.1,
        26482.9,
        925.2,
        0,
        27394.1,
        0,
        989.7,
        24344.6,
        1414.7,
        736.3
      ),
      tmb = c(
        9314.5,
        0,
        0,
        5798,
        0,
        0,
        5136.4,
        2252.5,
        0,
        4542.9,
        0,
        0,
        4398.4,
        3794.4,
        2186.3
      ),
      tol = c(
        880567.1,
        7430.6,
        4225.5,
        569616.2,
        6091.8,
        65642.6,
        495780.5,
        52129.9,
        3226,
        456079.6,
        5874,
        34725.9,
        453944.8,
        56594.4,
        66148.1
      ),
      mvk = c(169036.8,
              0, 0, 108738, 0, 0, 56712.5, 0, 0, 79148.9, 0, 0, 64065, 0, 0),
      euc = c(
        12815.2,
        0,
        0,
        8012.6,
        0,
        0,
        5411.8,
        0,
        0,
        5839.9,
        0,
        491.7,
        5450.7,
        1990.8,
        500.7
      )
    ),
    class = c("spec_tbl_df", "tbl_df",
              "tbl", "data.frame"),
    row.names = c(NA,-15L),
    spec = structure(list(
      cols = list(
        time = structure(list(format = ""), class = c("collector_datetime",
                                                      "collector")),
        type = structure(list(), class = c("collector_character",
                                           "collector")),
        ben = structure(list(), class = c("collector_double",
                                          "collector")),
        xyl = structure(list(), class = c("collector_double",
                                          "collector")),
        cym = structure(list(), class = c("collector_double",
                                          "collector")),
        isop = structure(list(), class = c("collector_double",
                                           "collector")),
        macr = structure(list(), class = c("collector_double",
                                           "collector")),
        pin = structure(list(), class = c("collector_double",
                                          "collector")),
        tmb = structure(list(), class = c("collector_double",
                                          "collector")),
        tol = structure(list(), class = c("collector_double",
                                          "collector")),
        mvk = structure(list(), class = c("collector_double",
                                          "collector")),
        euc = structure(list(), class = c("collector_double",
                                          "collector"))
      ),
      default = structure(list(), class = c("collector_guess",
                                            "collector")),
      skip = 2
    ), class = "col_spec")
  )

temp1 <- zero_test %>% 
  gather(gas, response, -time,-type) %>%
  group_by(group = cumsum(type == "current_std"), gas) %>%
  mutate(X1= row_number()-1, #estimates the position of the sample within the group -1 removes std
         F1=1-(X1/n()), #relative factor influence of the cal in the current group
         F2=1-F1,
         first_response = first(response)) %>% 
  ungroup

conc_zero_test <- temp1 %>% 
  left_join(y = {temp1 %>%
                  mutate(group = group - 1) %>% 
                  select(gas, group, first_response_next = first_response) %>% 
                  distinct},
            by = c("gas", "group")) %>% 
  mutate(RRF = response / ((F1 * first_response) + (F2 * first_response_next)))

conc_zero_test
#> # A tibble: 150 x 11
#>    time                type  gas   response group    X1    F1    F2
#>    <dttm>              <chr> <chr>    <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 2019-07-30 06:30:00 curr… ben   2293952.     1     0 1     0    
#>  2 2019-07-30 08:30:00 n2    ben     12703.     1     1 0.667 0.333
#>  3 2019-07-30 11:00:00 n2    ben      6393.     1     2 0.333 0.667
#>  4 2019-07-30 11:30:00 curr… ben   1762513.     2     0 1     0    
#>  5 2019-07-30 13:30:00 n2    ben     10748.     2     1 0.667 0.333
#>  6 2019-07-30 14:30:00 -     ben     25468.     2     2 0.333 0.667
#>  7 2019-07-30 15:00:00 curr… ben   1597679      3     0 1     0    
#>  8 2019-07-30 17:00:00 -     ben     24400.     3     1 0.667 0.333
#>  9 2019-07-30 18:00:00 n2    ben      6019.     3     2 0.333 0.667
#> 10 2019-07-30 18:30:00 curr… ben   1510760.     4     0 1     0    
#> # … with 140 more rows, and 3 more variables: first_response <dbl>,
#> #   first_response_next <dbl>, RRF <dbl>

^{由reprex软件包（v0.3.0）创建于2020-08-16}