如果第二行满足条件，则从每组中删除第一行

这是我的数据集的示例：

df=data.frame(id=c("9","9","9","5","5","5","4","4","4","4","4","20","20"),
  Date=c("11/29/2018","11/29/2018","11/29/2018","5/25/2018","2/13/2019","2/13/2019","6/7/2018",
    "6/15/2018","6/20/2018","8/17/2018","8/20/2018","12/25/2018","12/25/2018"), 
  Buyer= c("John","John","John","Maria","Maria","Maria","Sandy","Sandy","Sandy","Sandy","Sandy","Paul","Paul"))

我需要计算我已经完成的日期和数据集之间的差异，然后看起来像：

| id |    Date    | Buyer | diff |
|----|:----------:|------:|------|
| 9  | 11/29/2018 |  John | NA   |
| 9  | 11/29/2018 |  John | 0    |
| 9  | 11/29/2018 |  John | 0    |
| 5  | 5/25/2018  | Maria | -188 |
| 5  | 2/13/2019  | Maria | 264  |
| 5  | 2/13/2019  | Maria | 0    |
| 4  | 6/7/2018   | Sandy | -251 |
| 4  | 6/15/2018  | Sandy | 8    |
| 4  | 6/20/2018  | Sandy | 5    |
| 4  | 8/17/2018  | Sandy | 58   |
| 4  | 8/20/2018  | Sandy | 3    |
| 20 | 12/25/2018 | Paul  | 127  |
| 20 | 12/25/2018 | Paul  | 0    |

现在，如果每组“diff”列中第二行的值大于或等于 5，那么我需要删除每组的第一行。例如，对于 ID 为“5”的买家“Maria”，差异值 264 大于 5，因此我想删除该组中的第一行，即 ID 为“5”的买家“Maria”，日期为'5/25/2018'，差异为'-188'

下面是我的代码示例：

df1=df %>% group_by(Buyer,id) %>%
  mutate(diff = c(NA, diff(Date))) %>%
  filter(!(diff >=5 & row_number() == 1))

问题是上面的代码选择第一行而不是第二行，并且我不知道如何指定每个组的第二行，其中 diff 值应大于或等于 5。

我的预期输出应该如下所示：

| id |    Date    | Buyer | diff |
|----|:----------:|------:|------|
| 9  | 11/29/2018 |  John | NA   |
| 9  | 11/29/2018 |  John | 0    |
| 9  | 11/29/2018 |  John | 0    |
| 5  | 2/13/2019  | Maria | 264  |
| 5  | 2/13/2019  | Maria | 0    |
| 4  | 6/15/2018  | Sandy | 8    |
| 4  | 6/20/2018  | Sandy | 5    |
| 4  | 8/17/2018  | Sandy | 58   |
| 4  | 8/20/2018  | Sandy | 3    |
| 20 | 12/25/2018 | Paul  | 127  |
| 20 | 12/25/2018 | Paul  | 0    |

我认为您忘记提供diff列于df。我创建了一个名为diffs以免与功能冲突diff(). -

library(dplyr)

df1 %>% 
  group_by(id) %>% 
  mutate(diffs = c(NA, diff(as.Date(Date, format = "%m/%d/%Y")))) %>% 
  filter(
    n() == 1 |         # always keep if only one row in group
    row_number() > 1 | # always keep all row_number() > 1
    diffs[2] < 5       # keep 1st row only if 2nd row diffs < 5
  ) %>% 
  ungroup()

# A tibble: 11 x 4
   id    Date       Buyer diffs
   <chr> <chr>      <chr> <dbl>
 1 9     11/29/2018 John     NA
 2 9     11/29/2018 John      0
 3 9     11/29/2018 John      0
 4 5     2/13/2019  Maria   264
 5 5     2/13/2019  Maria     0
 6 4     6/15/2018  Sandy     8
 7 4     6/20/2018  Sandy     5
 8 4     8/17/2018  Sandy    58
 9 4     8/20/2018  Sandy     3
10 20    12/25/2018 Paul     NA
11 20    12/25/2018 Paul      0

Data -

I added stringsAsFactors = FALSE

df1 <- data.frame(id=c("9","9","9","5","5","5","4","4","4","4","4","20","20"),
  Date=c("11/29/2018","11/29/2018","11/29/2018","5/25/2018","2/13/2019","2/13/2019","6/7/2018",
    "6/15/2018","6/20/2018","8/17/2018","8/20/2018","12/25/2018","12/25/2018"), 
  Buyer= c("John","John","John","Maria","Maria","Maria","Sandy","Sandy","Sandy","Sandy","Sandy","Paul","Paul")
  , stringsAsFactors = F)