我试图通过使用r中的时间列来匹配两个文件。因此，我选择chron-time来实现这一点。但当我尝试将"时间"列转换为chron时间时，我收到了警告消息，"在convert.dates(dates.，format=format[[1]]，origin.=origin.(中：331个月超出了设置为NA的范围"我的数据如下，
Year Month Day Rain_mm Time chrontime
1 2019 1 1 0.6 01/01/2019 01:10:00 (01/01/19 01:10:00)
2 2019 1 2 0.0 02/01/2019 01:10:00 (02/01/19 01:10:00)
3 2019 1 3 0.0 03/01/2019 01:10:00 (03/01/19 01:10:00)
4 2019 1 4 0.0 04/01/2019 01:10:00 (04/01/19 01:10:00)
5 2019 1 5 0.0 05/01/2019 01:10:00 (05/01/19 01:10:00)
6 2019 1 6 0.0 06/01/2019 01:10:00 (06/01/19 01:10:00)
7 2019 1 7 3.4 07/01/2019 01:10:00 (07/01/19 01:10:00)
8 2019 1 8 5.8 08/01/2019 01:10:00 (08/01/19 01:10:00)
9 2019 1 9 0.4 09/01/2019 01:10:00 (09/01/19 01:10:00)
10 2019 1 10 0.0 10/01/2019 01:10:00 (10/01/19 01:10:00)
11 2019 1 11 0.2 11/01/2019 01:10:00 (11/01/19 01:10:00)
12 2019 1 12 2.8 12/01/2019 01:10:00 (12/01/19 01:10:00)
13 2019 1 13 2.6 13/01/2019 01:10:00 (NA NA)
14 2019 1 14 2.2 14/01/2019 01:10:00 (NA NA)
15 2019 1 15 3.2 15/01/2019 01:10:00 (NA NA)
16 2019 1 16 6.2 16/01/2019 01:10:00 (NA NA)
17 2019 1 17 12.6 17/01/2019 01:10:00 (NA NA)
18 2019 1 18 0.0 18/01/2019 01:10:00 (NA NA)
19 2019 1 19 0.0 19/01/2019 01:10:00 (NA NA)
20 2019 1 20 0.0 20/01/2019 01:10:00 (NA NA)
21 2019 1 21 7.4 21/01/2019 01:10:00 (NA NA)
22 2019 1 22 0.2 22/01/2019 01:10:00 (NA NA)
23 2019 1 23 0.0 23/01/2019 01:10:00 (NA NA)
24 2019 1 24 0.0 24/01/2019 01:10:00 (NA NA)
25 2019 1 25 0.0 25/01/2019 01:10:00 (NA NA)
26 2019 1 26 0.6 26/01/2019 01:10:00 (NA NA)
27 2019 1 27 7.6 27/01/2019 01:10:00 (NA NA)
28 2019 1 28 1.6 28/01/2019 01:10:00 (NA NA)
29 2019 1 29 0.0 29/01/2019 01:10:00 (NA NA)
30 2019 1 30 0.0 30/01/2019 01:10:00 (NA NA)
31 2019 1 31 0.0 31/01/2019 01:10:00 (NA NA)
32 2019 2 1 0.0 01/02/2019 01:10:00 (01/02/19 01:10:00)
33 2019 2 2 0.6 02/02/2019 01:10:00 (02/02/19 01:10:00)
34 2019 2 3 0.0 03/02/2019 01:10:00 (03/02/19 01:10:00)
35 2019 2 4 1.0 04/02/2019 01:10:00 (04/02/19 01:10:00)
36 2019 2 5 0.2 05/02/2019 01:10:00 (05/02/19 01:10:00)
37 2019 2 6 3.6 06/02/2019 01:10:00 (06/02/19 01:10:00)
38 2019 2 7 1.8 07/02/2019 01:10:00 (07/02/19 01:10:00)
39 2019 2 8 3.0 08/02/2019 01:10:00 (08/02/19 01:10:00)
40 2019 2 9 6.8 09/02/2019 01:10:00 (09/02/19 01:10:00)
41 2019 2 10 3.4 10/02/2019 01:10:00 (10/02/19 01:10:00)
42 2019 2 11 0.6 11/02/2019 01:10:00 (11/02/19 01:10:00)
43 2019 2 12 0.0 12/02/2019 01:10:00 (12/02/19 01:10:00)
44 2019 2 13 0.0 13/02/2019 01:10:00 (NA NA)
45 2019 2 14 0.0 14/02/2019 01:10:00 (NA NA)
46 2019 2 15 0.0 15/02/2019 01:10:00 (NA NA)
......
我的代码是：
Dts <- with(DMIdata, paste(substring(Time, 1,2), substring(Time,4,5), substring(Time, 9, 10), sep='/'))
hrs <- with(DMIdata, substring(Time, 13, 20))
DMIdata$chrontime <- chron(Dts,hrs)
我想知道，为什么13日之后的所有日期都被设定为NA，这是一种长期的转变？如何改进我的代码使其发挥作用？
谢谢你的帮助！
library(chron)
substring的问题是订单chron希望Date是?chron中指定的特定format
格式-日期格式可以是字符"的任何排列；d"m〃；，或"；y"；由分隔符(可能为空(定界，例如"；m/d/y"d-m-y"ymd"；，均有效；格式也可以是单词"的排列；天"月份；以及"；年；(带有非空分隔符(，它产生月份名称，例如"；年月日；产生"；1992年4月20日"day mon year"；产生"；1992年4月20日"；。
默认情况下，如果我们查看用法，它是mdy
chron(日期，时间，格式=c(日期="m/d/y"，时间="h:m:s"(，out.format，原点。(
而OP的Dts以d/m/y为单位。我们可以在这里指定format
chron(Dts,hrs, format = c(dates = "d/m/y", times = "h:m:s"))
#[1] (01/01/19 01:10:00) (02/01/19 01:10:00) (03/01/19 01:10:00) (04/01/19 01:10:00) (05/01/19 01:10:00) (06/01/19 01:10:00)
#[7] (07/01/19 01:10:00) (08/01/19 01:10:00) (09/01/19 01:10:00) (10/01/19 01:10:00) (11/01/19 01:10:00) (12/01/19 01:10:00)
#[13] (13/01/19 01:10:00) (14/01/19 01:10:00) (15/01/19 01:10:00) (16/01/19 01:10:00) (17/01/19 01:10:00) (18/01/19 01:10:00)
#[19] (19/01/19 01:10:00) (20/01/19 01:10:00) (21/01/19 01:10:00) (22/01/19 01:10:00) (23/01/19 01:10:00) (24/01/19 01:10:00)
#[25] (25/01/19 01:10:00) (26/01/19 01:10:00) (27/01/19 01:10:00) (28/01/19 01:10:00) (29/01/19 01:10:00) (30/01/19 01:10:00)
#[31] (31/01/19 01:10:00) (01/02/19 01:10:00) (02/02/19 01:10:00) (03/02/19 01:10:00) (04/02/19 01:10:00) (05/02/19 01:10:00)
#[37] (06/02/19 01:10:00) (07/02/19 01:10:00) (08/02/19 01:10:00) (09/02/19 01:10:00) (10/02/19 01:10:00) (11/02/19 01:10:00)
#[43] (12/02/19 01:10:00) (13/02/19 01:10:00) (14/02/19 01:10:00) (15/02/19 01:10:00)
数据
DMIdata <- structure(list(Year = c(2019L, 2019L, 2019L, 2019L, 2019L, 2019L,
2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L,
2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L,
2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L,
2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L,
2019L, 2019L, 2019L, 2019L), Month = c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), Day = c(1L, 2L, 3L, 4L, 5L,
6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L), Rain_mm = c(0.6, 0, 0, 0, 0, 0, 3.4, 5.8, 0.4, 0, 0.2,
2.8, 2.6, 2.2, 3.2, 6.2, 12.6, 0, 0, 0, 7.4, 0.2, 0, 0, 0, 0.6,
7.6, 1.6, 0, 0, 0, 0, 0.6, 0, 1, 0.2, 3.6, 1.8, 3, 6.8, 3.4,
0.6, 0, 0, 0, 0), Time = c("01/01/2019 01:10:00", "02/01/2019 01:10:00",
"03/01/2019 01:10:00", "04/01/2019 01:10:00", "05/01/2019 01:10:00",
"06/01/2019 01:10:00", "07/01/2019 01:10:00", "08/01/2019 01:10:00",
"09/01/2019 01:10:00", "10/01/2019 01:10:00", "11/01/2019 01:10:00",
"12/01/2019 01:10:00", "13/01/2019 01:10:00", "14/01/2019 01:10:00",
"15/01/2019 01:10:00", "16/01/2019 01:10:00", "17/01/2019 01:10:00",
"18/01/2019 01:10:00", "19/01/2019 01:10:00", "20/01/2019 01:10:00",
"21/01/2019 01:10:00", "22/01/2019 01:10:00", "23/01/2019 01:10:00",
"24/01/2019 01:10:00", "25/01/2019 01:10:00", "26/01/2019 01:10:00",
"27/01/2019 01:10:00", "28/01/2019 01:10:00", "29/01/2019 01:10:00",
"30/01/2019 01:10:00", "31/01/2019 01:10:00", "01/02/2019 01:10:00",
"02/02/2019 01:10:00", "03/02/2019 01:10:00", "04/02/2019 01:10:00",
"05/02/2019 01:10:00", "06/02/2019 01:10:00", "07/02/2019 01:10:00",
"08/02/2019 01:10:00", "09/02/2019 01:10:00", "10/02/2019 01:10:00",
"11/02/2019 01:10:00", "12/02/2019 01:10:00", "13/02/2019 01:10:00",
"14/02/2019 01:10:00", "15/02/2019 01:10:00")), class = "data.frame", row.names = c("1",
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13",
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24",
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35",
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46"
))