Question

我正在研究一个由旅行组成的数据集（变量：user_id, purpose, start_timeh, end_timeh。每次观察应该是一次旅行;但是由于数据错误，大约一半的旅行被分成了旅行段。在单次旅行的多次观察中（例如，旅行＃3被分成5段/具有不同旅行ID的观察）。

> head(df2)
  trip_id user_id duration_min purpose start_timeh end_timeh fix_needed
1  151203     abc         10.0       7       19:07     19:16          1
2  151204     abc          1.5       7       19:16     19:18          1
3  151206     abc          1.0       7       20:59     21:03          1
4  151207     abc          3.0       7       21:03     21:05          1
5  151208     abc          5.5       7       21:05     21:10          1
6  151210     abc          4.5       2       21:18     21:25          0
>

> dput(head(df2,4))
structure(list(trip_id = c(151203L, 151204L, 151206L, 151207L
), user_id = structure(c(1L, 1L, 1L, 1L), .Label = "abc", class = "factor"), 
    duration_min = c(10, 1.5, 1, 3), purpose = c(7L, 7L, 7L, 
    7L), start_timeh = structure(c(27L, 29L, 37L, 39L), .Label = c("0:08", 
    "15:50", "15:53", "15:55", "16:01", "16:10", "16:35", "17:04", 
    "17:08", "17:14", "17:25", "17:28", "17:32", "17:34", "17:48", 
    "17:54", "18:14", "18:17", "18:19", "18:28", "18:41", "18:44", 
    "18:47", "18:50", "18:54", "18:56", "19:07", "19:08", "19:16", 
    "19:18", "19:19", "19:23", "19:30", "19:59", "2:12", "2:25", 
    "20:59", "21:00", "21:03", "21:05", "21:18"), class = "factor"), 
    end_timeh = structure(c(28L, 29L, 36L, 37L), .Label = c("0:49", 
    "15:50", "15:53", "15:55", "16:01", "16:04", "16:12", "16:57", 
    "17:06", "17:08", "17:25", "17:32", "17:34", "17:52", "17:55", 
    "17:56", "18:14", "18:16", "18:19", "18:30", "18:44", "18:47", 
    "18:50", "18:54", "18:56", "18:58", "19:10", "19:16", "19:18", 
    "19:19", "19:27", "19:28", "19:32", "2:17", "20:06", "21:03", 
    "21:05", "21:10", "21:25", "21:39", "3:05"), class = "factor"), 
    fix_needed = c(1L, 1L, 1L, 1L)), .Names = c("trip_id", "user_id", 
"duration_min", "purpose", "start_timeh", "end_timeh", "fix_needed"
), row.names = c(NA, 4L), class = "data.frame")

我想根据三个标准组合这些旅行段：

相同的user_id
同样的旅行目的
（段i的开始时间）=（段i-1的结束时间）。

最终结果应如下所示：

旅行段合并为全程旅行。
全程的持续时间等于所有段的持续时间总和。
应从数据集中删除细分。

所以我跑了这个：

v = vector('numeric')
for (i in 2:nrow(df)) {
  if (as.numeric(df$start_timeh[i]) == as.numeric(df$end_timeh[i-1]) &&  df$user_id[i] == df$user_id[i-1] && df$purpose[i] == df$purpose[i-1]) 
  {
    df$duration_min[i]<-df$duration_min[i]+df$duration_min[i-1]
    v <- c(v,i-1)

  }
}
df <- df[-v,]

然而，结果并不像我预期的那样。很多细分都没有删除。

更新：创建此问题的时间戳出错。代码是正确的。

根据时间戳对行中的数据求和

0 个答案: