如何在R中的特定时间之后和另一个时间之前提取时间？答案

【问题标题】：How to extract time after a particular time and before another time in R?如何在R中的特定时间之后和另一个时间之前提取时间？
【发布时间】：2023-03-26 19:50:01
【问题描述】：

我的问题之前可能有人问过。我搜索了，但我找不到。感谢您的回答或参考以前的帖子。我有两个数据集。我的数据集（DF1 和 DF2）包括我想要的变量（V1 和 V2）的日期、时间和值。日期和时间列都属于因子类。这是我的 DF1，包括 V1：

#DF1
Date        Time         V1
6/2/2019  0:00:00        0
6/2/2019  0:01:00        24
.
..
6/2/2019  23:59:00       56
6/3/2019  0:00:00        78
6/3/2019  0:01:00        24
.
..
6/3/2019  23:59:00       32
6/4/2019  0:00:00        14
6/4/2019  0:01:00        62
.
..
6/4/2019  23:59:00       103

然后，这是我的数据 (DF2)，其中包括变量 2 (V2)。

#DF2
Date        Time         V2    
6/2/2019  0:00:00        2
6/2/2019  0:01:00        33
.
..
6/2/2019  23:59:00       12
6/3/2019  0:00:00        14
6/3/2019  0:01:00        56
.
..
6/3/2019  23:59:00       67
6/4/2019  0:00:00        94
6/4/2019  0:01:00        43
.
..
6/4/2019  23:59:00       156

首先，我必须根据 DateTime 变量（即日期和时间的组合）组合这两个数据集。所以，我使用了以下代码。

# I used the following to change the date class for DF1 and DF2.
DF1$Date <- as.Date(DF1$Date , "%d/%m/%Y")
DF2$Date <- as.Date(DF2$Date , "%d/%m/%Y")

#Then, I merged Date and Time in each dataset in a variable called "Datetime"
DF1$Datetime <- paste(DF1$Date , DF1$Time)
DF2$Datetime <- paste(DF2$Date , DF2$Time)

#Then, I changed the type of Datetime variable as follows:
DF1$Datetime <- as.POSIXct(DF1$Datetime, format = "%Y-%m-%d %H:%M:%S")
DF2$Datetime <- as.POSIXct(DF2$Datetime, format = "%Y-%m-%d %H:%M:%S")

#After that, I merged the datasets DF1 and DF2 by Datetime variable:
My_DF <- merge(DF1, DF2, by = "Datetime")

现在，我需要提取 My_DF 的子集以及“9:00:00”之后和“22:00:00”之前的时间（记录）。例如，输出应包括但不限于我的数据中 7 天的所有 9:01:00 记录。所以，我尝试了以下方法，但它不起作用：

New_DF <- subset(My_DF, My_DF$Time > "09:00:00" & My_DF$Time < "22:00:00")

New_DF（我想要的输出）应该是：

Date        Time         V1         V2    
6/2/2019  9:01:00        ..         ..
6/3/2019  9:01:00        ..         ..
6/4/2019  9:01:00        ..         ..
6/2/2019  9:02:00        ..         ..
6/3/2019  9:02:00        ..         ..
6/4/2019  9:02:00        ..         ..
..
6/2/2019  21:59:00       ..         ..
6/3/2019  21:59:00       ..         ..
6/3/2019  21:59:00       ..         ..

【问题讨论】：

标签： r

【解决方案1】：

这是一种方法。由于未提供数据，因此不得不创建一些数据

> # create data as factors
> dates <- as.factor(paste0('6/', 2:8, '/2019'))
> times <- as.factor(format(as.POSIXct(seq(0, 86400-60, by = 60), 
+                            origin = '1970-1-1',
+                            tz = 'UTC'), 
+                 format = '%H:%M:%S')
+ )
> 
> # create data.frame (tibble)
> tib <- tibble(date = rep(dates, each = 1440),
+               time = rep(times, times = 7)
+ )
> 
> # select data after converting factors to characters
> # (try to avoid the use of factors except for categorical data)
> sel <- filter(tib,
+               as.character(time) >= '10:00:00' &
+                 as.character(time) <= '22:00:00'
+ )
> 
> glimpse(tib)
Observations: 10,080
Variables: 2
$ date <fct> 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6...
$ time <fct> 00:00:00, 00:01:00, 00:02:00, 00:03:00, 00:04:00, 00:05:00, 00:06:00, 00:07:00, 00:08:00, 0...
> glimpse(sel)
Observations: 5,047
Variables: 2
$ date <fct> 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/2019, 6/2/201...
$ time <fct> 10:00:00, 10:01:00, 10:02:00, 10:03:00, 10:04:00, 10:05:00, 10:06:00, 10:07:00, 10:08:00, 10:09:00, 10:10:0...
>

【讨论】：

【解决方案2】：

您可以根据一天中的小时对数据进行子集化：

#merge two datasets
New_DF <- merge(transform(df1, 
                datetime = as.POSIXct(paste(Date, Time), format = "%d/%m/%Y %T")), 
                transform(df2, 
                datetime = as.POSIXct(paste(Date, Time), format = "%d/%m/%Y %T")), 
                by = "datetime")
#Select relevant columns
New_DF <- New_DF[c("datetime", "V1", "V2")]
#Extract hour of the day
New_DF$hour <- as.integer(format(New_DF$datetime, "%H"))
#Subset the data based on hour
New_DF[New_DF$hour >= 9 & New_DF$hour < 22, ]

或者使用tidyverse和lubridate

library(tidyverse)
library(lubridate)

inner_join(df1 %>%
            unite(Datetime, Date, Time, sep = " ") %>%
            mutate(Datetime = mdy_hms(Datetime)), 
           df2 %>%
            unite(Datetime, Date, Time, sep = " ") %>%
            mutate(Datetime = mdy_hms(Datetime)), by = "Datetime") %>%
 filter(hour(Datetime) >= 9 & hour(Datetime) < 22)

【讨论】：