在 R 中跨多个日期（POSIXt 格式）按特定时间删除行答案

【问题标题】：Remove Rows By Specific Hours Across Multiple Dates (POSIXt format) in R在 R 中跨多个日期（POSIXt 格式）按特定时间删除行
【发布时间】：2018-03-03 00:54:28
【问题描述】：

我有一个数据框，需要删除所有日期的小时 0:00、1:00、2:00、3:00、4:00、5:00、6:00 的行，只剩下 17每天的数字而不是 24。然后我需要从这 17 个值中计算每天的最大值，但我坚持摆脱我不需要的 7 个小时。这是我已经尝试过的

library(dplyr)
library (lubridate)
df <- maximums %>% filter(!grepl("0:00", maximums$date))

任何想法如何摆脱 7 小时？

> class(maximums$date)
[1] "POSIXct" "POSIXt" 
 > class(maximums$X8.hour.running.ozone)
[1] "numeric"
 date                               X8.hour.running.ozone
1    2015-01-01 07:00:00           0.028938958
2    2015-01-01 08:00:00           0.028889583
3    2015-01-01 09:00:00           0.029101042
4    2015-01-01 10:00:00           0.029714583
5    2015-01-01 11:00:00           0.030435000
6    2015-01-01 12:00:00           0.031142500
7    2015-01-01 13:00:00           0.032040208
8    2015-01-01 14:00:00           0.032310625
9    2015-01-01 15:00:00           0.031541875
10   2015-01-01 16:00:00           0.030727708
11   2015-01-01 17:00:00           0.029294583
12   2015-01-01 18:00:00           0.029521497
13   2015-01-01 19:00:00           0.029260455
14   2015-01-01 20:00:00           0.028565455
15   2015-01-01 21:00:00           0.028091705
16   2015-01-01 22:00:00           0.027990038
17   2015-01-01 23:00:00           0.028562330
18   2015-01-02 00:00:00           0.029188788
19   2015-01-02 01:00:00           0.030586705
20   2015-01-02 02:00:00           0.030149167
21   2015-01-02 03:00:00           0.030019583
22   2015-01-02 04:00:00           0.030131667
23   2015-01-02 05:00:00           0.029914583
24   2015-01-02 06:00:00           0.029825208
25   2015-01-02 07:00:00           0.030125833
26   2015-01-02 08:00:00           0.030182083
27   2015-01-02 09:00:00           0.029968333
28   2015-01-02 10:00:00           0.029895833
29   2015-01-02 11:00:00           0.030017500
30   2015-01-02 12:00:00           0.030468125
31   2015-01-02 13:00:00           0.030865000
32   2015-01-02 14:00:00           0.030941458
33   2015-01-02 15:00:00           0.030991875
34   2015-01-02 16:00:00           0.031401875
35   2015-01-02 17:00:00           0.032022997
36   2015-01-02 18:00:00           0.032019372
37   2015-01-02 19:00:00           0.032063122
38   2015-01-02 20:00:00           0.031818747
39   2015-01-02 21:00:00           0.031460413
40   2015-01-02 22:00:00           0.031113955
41   2015-01-02 23:00:00           0.029953955
42   2015-01-03 00:00:00           0.028782497
43   2015-01-03 01:00:00           0.027288667
44   2015-01-03 02:00:00           0.026244375
45   2015-01-03 03:00:00           0.025112917
46   2015-01-03 04:00:00           0.024015417
47   2015-01-03 05:00:00           0.022908542
48   2015-01-03 06:00:00           0.022458958
49   2015-01-03 07:00:00           0.022889583
50   2015-01-03 08:00:00           0.022612500
51   2015-01-03 09:00:00           0.023327917

理想情况下我想返回：

   date                               X8.hour.running.ozone
1    2015-01-01 07:00:00           0.028938958
2    2015-01-01 08:00:00           0.028889583
3    2015-01-01 09:00:00           0.029101042
4    2015-01-01 10:00:00           0.029714583
5    2015-01-01 11:00:00           0.030435000
6    2015-01-01 12:00:00           0.031142500
7    2015-01-01 13:00:00           0.032040208
8    2015-01-01 14:00:00           0.032310625
9    2015-01-01 15:00:00           0.031541875
10   2015-01-01 16:00:00           0.030727708
11   2015-01-01 17:00:00           0.029294583
12   2015-01-01 18:00:00           0.029521497
13   2015-01-01 19:00:00           0.029260455
14   2015-01-01 20:00:00           0.028565455
15   2015-01-01 21:00:00           0.028091705
16   2015-01-01 22:00:00           0.027990038
17   2015-01-01 23:00:00           0.028562330
18   2015-01-02 07:00:00           0.030125833
19   2015-01-02 08:00:00           0.030182083
20   2015-01-02 09:00:00           0.029968333
21   2015-01-02 10:00:00           0.029895833
22   2015-01-02 11:00:00           0.030017500
23   2015-01-02 12:00:00           0.030468125
24   2015-01-02 13:00:00           0.030865000
25   2015-01-02 14:00:00           0.030941458
26   2015-01-02 15:00:00           0.030991875
27   2015-01-02 16:00:00           0.031401875
28   2015-01-02 17:00:00           0.032022997
29   2015-01-02 18:00:00           0.032019372
30   2015-01-02 19:00:00           0.032063122
31   2015-01-02 20:00:00           0.031818747
32   2015-01-02 21:00:00           0.031460413
33   2015-01-02 22:00:00           0.031113955
34   2015-01-02 23:00:00           0.029953955
35   2015-01-03 07:00:00           0.022889583
36   2015-01-03 08:00:00           0.022612500
37   2015-01-03 09:00:00           0.023327917

【问题讨论】：

标签： r datetime posixct openair ozone

【解决方案1】：

如果你只是想删除这些时间，你可以这样：

library(lubridate)
library(dplyr)
library(readr)

df %>%
  type_convert() %>% 
  as_tibble() %>% 
  filter(hour(date) > 6)

# A tibble: 37 x 2
   date                running.ozone
   <dttm>                      <dbl>
 1 2015-01-01 07:00:00        0.0289
 2 2015-01-01 08:00:00        0.0289
 3 2015-01-01 09:00:00        0.0291
 4 2015-01-01 10:00:00        0.0297
 5 2015-01-01 11:00:00        0.0304
 6 2015-01-01 12:00:00        0.0311
 7 2015-01-01 13:00:00        0.0320
 8 2015-01-01 14:00:00        0.0323
 9 2015-01-01 15:00:00        0.0315
10 2015-01-01 16:00:00        0.0307
# ... with 27 more rows

数据：

df <- structure(list(date = c(
  "2015-01-01 07:00:00", "2015-01-01 08:00:00",
  "2015-01-01 09:00:00", "2015-01-01 10:00:00", "2015-01-01 11:00:00",
  "2015-01-01 12:00:00", "2015-01-01 13:00:00", "2015-01-01 14:00:00",
  "2015-01-01 15:00:00", "2015-01-01 16:00:00", "2015-01-01 17:00:00",
  "2015-01-01 18:00:00", "2015-01-01 19:00:00", "2015-01-01 20:00:00",
  "2015-01-01 21:00:00", "2015-01-01 22:00:00", "2015-01-01 23:00:00",
  "2015-01-02 00:00:00", "2015-01-02 01:00:00", "2015-01-02 02:00:00",
  "2015-01-02 03:00:00", "2015-01-02 04:00:00", "2015-01-02 05:00:00",
  "2015-01-02 06:00:00", "2015-01-02 07:00:00", "2015-01-02 08:00:00",
  "2015-01-02 09:00:00", "2015-01-02 10:00:00", "2015-01-02 11:00:00",
  "2015-01-02 12:00:00", "2015-01-02 13:00:00", "2015-01-02 14:00:00",
  "2015-01-02 15:00:00", "2015-01-02 16:00:00", "2015-01-02 17:00:00",
  "2015-01-02 18:00:00", "2015-01-02 19:00:00", "2015-01-02 20:00:00",
  "2015-01-02 21:00:00", "2015-01-02 22:00:00", "2015-01-02 23:00:00",
  "2015-01-03 00:00:00", "2015-01-03 01:00:00", "2015-01-03 02:00:00",
  "2015-01-03 03:00:00", "2015-01-03 04:00:00", "2015-01-03 05:00:00",
  "2015-01-03 06:00:00", "2015-01-03 07:00:00", "2015-01-03 08:00:00",
  "2015-01-03 09:00:00"
), running.ozone = c(
  0.028938958, 0.028889583,
  0.029101042, 0.029714583, 0.030435, 0.0311425, 0.032040208, 0.032310625,
  0.031541875, 0.030727708, 0.029294583, 0.029521497, 0.029260455,
  0.028565455, 0.028091705, 0.027990038, 0.02856233, 0.029188788,
  0.030586705, 0.030149167, 0.030019583, 0.030131667, 0.029914583,
  0.029825208, 0.030125833, 0.030182083, 0.029968333, 0.029895833,
  0.0300175, 0.030468125, 0.030865, 0.030941458, 0.030991875, 0.031401875,
  0.032022997, 0.032019372, 0.032063122, 0.031818747, 0.031460413,
  0.031113955, 0.029953955, 0.028782497, 0.027288667, 0.026244375,
  0.025112917, 0.024015417, 0.022908542, 0.022458958, 0.022889583,
  0.0226125, 0.023327917
)), class = "data.frame", row.names = c(
  NA,
  -51L
), .Names = c("date", "running.ozone"))

【讨论】：