折叠从0到0的行 [英] Collapse rows from 0 to 0

问题描述

对于这样的数据集

    Incident.ID..                date           product
    INCFI0000029582     2014-09-25 08:39:45     foo
    INCFI0000029582     2014-09-25 08:39:48     bar 
    INCFI0000029582     2014-09-25 08:40:44     foo
    INCFI0000029582     2014-10-10 23:04:00     foo
    INCFI0000029587     2014-09-25 08:33:32     bar
    INCFI0000029587     2014-09-25 08:34:41     bar
    INCFI0000029587     2014-09-25 08:35:24     bar
    INCFI0000029587     2014-10-10 23:04:00     foo


df <- structure(list(Incident.ID.. = c("INCFI0000029582", "INCFI0000029582", 
"INCFI0000029582", "INCFI0000029582", "INCFI0000029587", "INCFI0000029587", 
"INCFI0000029587", "INCFI0000029587"), date = c("2014-09-25 08:39:45", 
"2014-09-25 08:39:48", "2014-09-25 08:40:44", "2014-10-10 23:04:00", 
"2014-09-25 08:33:32", "2014-09-25 08:34:41", "2014-09-25 08:35:24", 
"2014-10-10 23:04:00"), product = 
c("foo","bar","foo","foo","bar","bar","bar","foo")), 
class = "data.frame", row.names = c(NA, 
-8L))

我正在使用mutate函数按id计算时间的滚动差异，如下所示：

I am calculating the rolling difference in time by id using the mutate function as follows

library(dplyr)
library(lubridate)
df1 <- df %>%
  group_by(Incident.ID..) %>%
  mutate(diff = c(0, diff(ymd_hms(date))))

这将创建列 diff 作为按照

  Incident.ID..   date                 product    diff
  INCFI0000029582 2014-09-25 08:39:45  foo        0
  INCFI0000029582 2014-09-25 08:39:48  bar        3
  INCFI0000029582 2014-09-25 08:40:44  foo        56
  INCFI0000029582 2014-10-10 23:04:00  foo        1347796
  INCFI0000029587 2014-09-25 08:33:32  bar        0
  INCFI0000029587 2014-09-25 08:34:41  bar        69
  INCFI0000029587 2014-09-25 08:35:24  bar        43
  INCFI0000029587 2014-10-10 23:04:00  foo        1348116

现在我的目标将汇总/折叠从零到零的行，并使用预期的最终数据集

Now my goal is to aggregate/collapse rows from zero to zero, with the expected final dataset like this

 Incident.ID..     DateMin              DateMax              product
 INCFI0000029582   2014-09-25 08:39:45  2014-10-10 23:04:00  foo,bar,foo,foo
 INCFI0000029587   2014-09-25 08:33:32  2014-10-10 23:04:00  bar,bar,bar,foo

我不确定如何使用最小和最大日期列折叠如上所示的行，我需要帮助。

I am not sure how to collapse rows as shown above with a min and max date column , I need help. Thanks in advance.

推荐答案

group_by 属性保留在<$之后c $ c> mutate ，因此我们按小组进行总结以获得 min ， max 个日期，然后通过粘贴将元素合在一起折叠该产品（ toString 是 paste（。，crash =，））

The group_by attribute remains after the mutate, so we summarise by the group to get the min, max of 'the 'date' and collapse the 'product' by pasteing the elements together (toString is a convenient wrapper for paste(., collapse=", "))

df %>%
   group_by(Incident.ID..) %>%
   mutate(diff = c(0, diff(ymd_hms(date)))) %>% 
   summarise(DateMin = min(date), 
             DateMax = max(date), 
             product = toString(product))
# A tibble: 2 x 4
#  Incident.ID..   DateMin             DateMax             product           
#  <chr>           <chr>               <chr>               <chr>             
#1 INCFI0000029582 2014-09-25 08:39:45 2014-10-10 23:04:00 foo, bar, foo, foo
#2 INCFI0000029587 2014-09-25 08:33:32 2014-10-10 23:04:00 bar, bar, bar, foo

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