如何根据时间戳获取r中一周到另一周的差异

我试图通过创建一个新的列来检查客户是否每周都在购买，该列显示购买发生在随后的一周

初始数据 最终数据

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其中一个选项是为此使用

dplyr

您的预期输出表有点不正确，因为第一个时间戳与第周不匹配

library(dplyr)
df %>% 
  group_by(id) %>% 
  mutate(diff1 = week_no - lag(week_no)) %>% 
  filter(timestamp == max(timestamp))

# A tibble: 2 x 4
# Groups:   id [2]
  id    timestamp           week_no diff1
  <chr> <dttm>                <int> <int>
1 b9968 2016-08-23 17:46:44      34     1
2 4983f 2016-08-13 17:30:47      32     0

库（dplyr）
df%>%
分组依据（id）%>%
变异（diff1=周无-滞后（周无））%>%
过滤器（时间戳==最大值（时间戳））
#一个tibble:2x4
#组别:id[2]
id时间戳周号差异1
1 b9968 2016-08-23 17:46:44 34 1
24983F 2016-08-13 17:30:47 32 0

数据：

---

df非常感谢。这对我有用。我不明白为什么会有人投票反对这个答案。
id         timestamp           week_no  diff1    
b9968     2016-08-17 09:38:33     34     1        
4983f     2016-08-13 17:30:47     32     0

library(dplyr)
df %>% 
  group_by(id) %>% 
  mutate(diff1 = week_no - lag(week_no)) %>% 
  filter(timestamp == max(timestamp))

# A tibble: 2 x 4
# Groups:   id [2]
  id    timestamp           week_no diff1
  <chr> <dttm>                <int> <int>
1 b9968 2016-08-23 17:46:44      34     1
2 4983f 2016-08-13 17:30:47      32     0

df <- structure(list(id = c("b9968", "b9968", "b9968", "b9968", "4983f", 
                      "4983f"), 
               timestamp = structure(c(1471426713, 1471541603, 1471631120, 
                                       1471974404, 1471003283, 1471109447), 
                                     tzone = "UTC", class = c("POSIXct","POSIXt")), 
               week_no = c(33L, 33L, 33L, 34L, 32L, 32L)), 
          .Names = c("id", "timestamp", "week_no"), 
          row.names = c(NA, -6L), 
          class = "data.frame")