如何根据 R 中的（按时间顺序）时间差异将观察结果分组在一起

Question

我正在尝试根据它们在时间上发生的紧密程度将观察结果组合在一起。

data <- data.frame(date = c("2020-04-14 03:26:58", "2020-04-14 11:26:58", "2020-04-14 12:29:20", "2020-04-14 12:48:02",
                            "2020-04-15 13:01:09", "2020-04-15 13:16:21", "2020-04-15 13:51:06", "2020-04-16 13:59:11",
                            "2020-04-16 14:01:37", "2020-04-18 20:02:37", "2020-04-18 20:17:37"))

data$date <- as.POSIXct(data$date, format="%Y-%m-%d %H:%M:%S")

head(data, 11)
                  date
1  2020-04-14 03:26:58
2  2020-04-14 11:26:58
3  2020-04-14 12:29:20
4  2020-04-14 12:48:02
5  2020-04-15 13:01:09
6  2020-04-15 13:16:21
7  2020-04-15 13:51:06
8  2020-04-16 13:59:11
9  2020-04-16 14:01:37
10 2020-04-18 20:02:37
11 2020-04-18 20:17:37

 

我想根据观察结果是否发生在同一时间段内，将观察结果分配到离散组：

例如，规则可以是：如果行与其滞后行之间的时间差小于 2 小时，则将行组合在一起。

我尝试创建一个滞后变量并计算每行与其滞后行之间的时间差，但我不知道如何从中获得添加组。

# Create lagged date variable
data$lag <- lag(data$date)

# Calculate time difference between original and lagged variable
data$time_diff <- as.numeric(difftime(data$date, data$lag, unit = "hours"))

在这种情况下，所需的输出会将group 列添加到data，例如：

                  date                 lag   time_diff group
1  2020-04-14 03:26:58                <NA>          NA     A
2  2020-04-14 11:26:58 2020-04-14 03:26:58  8.00000000     B
3  2020-04-14 12:29:20 2020-04-14 11:26:58  1.03944444     B
4  2020-04-14 12:48:02 2020-04-14 12:29:20  0.31166667     B
5  2020-04-15 13:01:09 2020-04-14 12:48:02 24.21861111     C
6  2020-04-15 13:16:21 2020-04-15 13:01:09  0.25333333     C
7  2020-04-15 13:51:06 2020-04-15 13:16:21  0.57916667     C
8  2020-04-16 13:59:11 2020-04-15 13:51:06 24.13472222     D
9  2020-04-16 14:01:37 2020-04-16 13:59:11  0.04055556     D
10 2020-04-18 20:02:37 2020-04-16 14:01:37 54.01666667     E
11 2020-04-18 20:17:37 2020-04-18 20:02:37  0.25000000     E

Answer 1

一个data.table 选项：

setDT(data)
data[, diff_hours := as.numeric(difftime(date, shift(date, fill = date[1])), unit = "hours")]
data[, group := LETTERS[cumsum(diff_hours >= 2) + 1L]]

#                    date  diff_hours group
#  1: 2020-04-14 03:26:58  0.00000000     A
#  2: 2020-04-14 11:26:58  8.00000000     B
#  3: 2020-04-14 12:29:20  1.03944444     B
#  4: 2020-04-14 12:48:02  0.31166667     B
#  5: 2020-04-15 13:01:09 24.21861111     C
#  6: 2020-04-15 13:16:21  0.25333333     C
#  7: 2020-04-15 13:51:06  0.57916667     C
#  8: 2020-04-16 13:59:11 24.13472222     D
#  9: 2020-04-16 14:01:37  0.04055556     D
# 10: 2020-04-18 20:02:37 54.01666667     E
# 11: 2020-04-18 20:17:37  0.25000000     E