r - 按组比较特定条件下的连续行

Question

对于每个参与者和每个试验，我需要检查 CURRENT_ID 中的所有连续行，第一行在 A 列中的值为 0，最后一行在 B 列中的值为 0。如果这两个条件都满足，我希望新列 C 中的值为 0，如果不满足，我希望值为 1。

head(mydf, 10)

#> # A tibble: 10 x 6
#>        A     B participant trial CURRENT_ID     C
#>    <dbl> <dbl> <chr>       <dbl>      <dbl> <dbl>
#>  1     0     1 ppt01          45          3     0
#>  2     1     0 ppt01          45          4     0
#>  3     0     1 ppt01          45         10     0
#>  4     0     0 ppt01          45         11     0
#>  5     1     0 ppt01          45         12     0
#>  6     0     1 ppt01          87          2     0
#>  7     1     0 ppt01          87          3     0
#>  8     1     1 ppt01          87          4     1
#>  9     1     1 ppt01          87          5     1
#> 10     0     1 ppt01          34          6     0

我需要考虑每个参与者和试验的每一对连续行(基于 CURRENT_ID 的值是连续的)。在上面的示例中，第 8 行和第 9 行在新列 C 中的值为 1，因为第 8 行在 A 列中有 1(而不是 0)，而第 9 行在 B 列中有 1(而不是 0)。

这里是如何比较行的示例，参与者 ppt01 和试验 87

    A   B    participant   trial   CURRENT_ID      C

    0   1    ppt01         87      2               0
    1   0    ppt01         87      3               0

    1   0    ppt01         87      3               0
    1   1    ppt01         87      4               1

    1   1    ppt01         87      4               1
    1   1    ppt01         87      5               1

数据:

mydf <- structure(list(A = c(0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 
1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 
1, 1), B = c(1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 
0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1
), participant = c("ppt01", "ppt01", "ppt01", "ppt01", "ppt01", 
"ppt01", "ppt01", "ppt01", "ppt01", "ppt01", "ppt01", "ppt01", 
"ppt01", "ppt01", "ppt01", "ppt01", "ppt01", "ppt01", "ppt01", 
"ppt01", "ppt01", "ppt02", "ppt02", "ppt02", "ppt02", "ppt02", 
"ppt02", "ppt02", "ppt02", "ppt02", "ppt02", "ppt02", "ppt02", 
"ppt02", "ppt02", "ppt02", "ppt02"), trial = c(45, 45, 45, 45, 
45, 87, 87, 87, 87, 34, 34, 34, 34, 34, 34, 8, 8, 8, 8, 8, 8, 
87, 87, 87, 87, 55, 55, 55, 55, 55, 55, 22, 22, 22, 22, 22, 22
), CURRENT_ID = c(3, 4, 10, 11, 12, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
11, 5, 6, 9, 10, 11, 12, 2, 3, 4, 5, 5, 6, 9, 10, 11, 12, 2, 
3, 4, 10, 11, 12), C = c(0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 
1, 0, 1, 1)), class = c("spec_tbl_df", "tbl_df", "tbl", "data.frame"
), row.names = c(NA, -37L), spec = structure(list(cols = list(
    A = structure(list(), class = c("collector_double", "collector"
    )), B = structure(list(), class = c("collector_double", "collector"
    )), participant = structure(list(), class = c("collector_character", 
    "collector")), trial = structure(list(), class = c("collector_double", 
    "collector")), CURRENT_ID = structure(list(), class = c("collector_double", 
    "collector")), C = structure(list(), class = c("collector_double", 
    "collector"))), default = structure(list(), class = c("collector_guess", 
"collector")), skip = 1), class = "col_spec"))

Answer 1

如果您想将 AB 对分组到参与者试验组中，这应该可行:

d %>% group_by(participant, trial) %>% mutate(AB = ceiling(1:n()/2)) %>% group_by(participant, trial, AB) %>% mutate(newC = ifelse(length(A) == 1 | (A[1] == 0 & B[2] == 0), 0, 1))

我已将新列保留在其中，以便您了解这是如何完成的。

输出:

# A tibble: 15 x 8
       A     B participant trial CURRENT_ID     C    AB  newC
   <int> <int>       <chr> <int>      <int> <int> <dbl> <dbl>
 1     0     1       ppt01    45          3     0     1     0
 2     1     0       ppt01    45          4     0     1     0
 3     0     1       ppt01    45         10     0     2     0
 4     0     0       ppt01    45         11     0     2     0
 5     1     0       ppt01    45         12     0     3     0
 6     0     1       ppt01    87          2     0     1     0
 7     1     0       ppt01    87          3     0     1     0
 8     1     1       ppt01    87          4     1     2     1
 9     1     1       ppt01    87          5     1     2     1
10     0     1       ppt01    34          6     0     1     0
11     0     0       ppt01    34          7     0     1     0
12     0     0       ppt01    34          8     0     2     0
13     0     0       ppt01    34          9     0     2     0
14     0     0       ppt01    34         10     0     3     0
15     1     0       ppt01    34         11     0     3     0

否则，如最初所述:

require(dplyr)
d %>% group_by(participant, trial) %>% mutate(newC = ifelse(A[1] == 0 & B[n()] == 0, 0, 1))

输出:

Source: local data frame [15 x 7]
Groups: participant, trial [3]

# A tibble: 15 x 7
       A     B participant trial CURRENT_ID     C  newC
   <int> <int>       <chr> <int>      <int> <int> <dbl>
 1     0     1       ppt01    45          3     0     0
 2     1     0       ppt01    45          4     0     0
 3     0     1       ppt01    45         10     0     0
 4     0     0       ppt01    45         11     0     0
 5     1     0       ppt01    45         12     0     0
 6     0     1       ppt01    87          2     0     1
 7     1     0       ppt01    87          3     0     1
 8     1     1       ppt01    87          4     1     1
 9     1     1       ppt01    87          5     1     1
10     0     1       ppt01    34          6     0     0
11     0     0       ppt01    34          7     0     0
12     0     0       ppt01    34          8     0     0
13     0     0       ppt01    34          9     0     0
14     0     0       ppt01    34         10     0     0
15     1     0       ppt01    34         11     0     0

我使用 dput() 使用了您的数据子集:

d <- structure(
  list(
    A = c(0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 0L,
          0L, 0L, 0L, 0L, 1L),
    B = c(1L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L,
          1L, 0L, 0L, 0L, 0L, 0L),
    participant = c(
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01",
      "ppt01"
    ),
    trial = c(
      45L,
      45L,
      45L,
      45L,
      45L,
      87L,
      87L,
      87L,
      87L,
      34L,
      34L,
      34L,
      34L,
      34L,
      34L
    ),
    CURRENT_ID = c(3L, 4L, 10L, 11L, 12L, 2L, 3L, 4L, 5L, 6L,
                   7L, 8L, 9L, 10L, 11L),
    C = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
          1L, 0L, 0L, 0L, 0L, 0L, 0L)
  ),
  .Names = c("A", "B", "participant",
             "trial", "CURRENT_ID", "C"),
  class = "data.frame",
  row.names = c(NA,-15L)
)