当一个 Dataframe 的时间戳在另一个 Dataframe 的datetime间隔之间时合并 Dataframe

bzzcjhmw 于 2023-05-20 发布在其他

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我有两个 Dataframe 的时间数据在POSIXct格式和相应的位置，我需要匹配。一个数据集具有在一系列30分钟的箱中的时间，沿着位置数据。

location   datetimes        date       shark
SS04   2018-03-20 08:00:00 2018-03-20     A
Absent 2018-03-20 08:30:00 2018-03-20     A
Absent 2018-03-20 09:00:00 2018-03-20     A
Absent 2018-03-20 09:30:00 2018-03-20     A
SS04   2018-03-20 10:00:00 2018-03-20     A
Absent 2018-03-20 10:30:00 2018-03-20     A

第二数据集具有每2分钟记录的时间数据。

shark       depth     temperature   datetime       date
A            49.5        26.2   20/03/2018 08:00 20/03/2018
A            49.5        25.3   20/03/2018 08:02 20/03/2018
A            53.0        24.2   20/03/2018 08:04 20/03/2018
A            39.5        26.5   20/03/2018 08:28 20/03/2018
A            43.0        26.2   20/03/2018 09:10 20/03/2018
A            44.5        26.5   20/03/2018 10:34 20/03/2018

我需要根据位置数据将第一个数据集的时间仓（datetime）与第二个数据集中的时间数据（datetime）进行匹配，以便第二个数据集中与第一个数据集中的仓相对应的所有数据都具有分配给30分钟内所有值的位置值。
我想我可以使用data.table，但我对如何处理这个问题没有信心。
理想情况下，我希望创建一个这样的数据集，将第一个数据集的位置添加到第二个数据集，基于第一个数据集的相应时间箱。

shark depth temperature   datetime    date      location
A     49.5  26.2   20/03/2018 08:00 20/03/2018    SS04
A     49.5  25.3   20/03/2018 08:02 20/03/2018    SS04
A     53.0  24.2   20/03/2018 08:04 20/03/2018    SS04
A     39.5  26.5   20/03/2018 08:32 20/03/2018    Absent
A     43.0  26.2   20/03/2018 09:10 20/03/2018    Absent
A     44.5  26.5   20/03/2018 10:18 20/03/2018    SS04

来源：https://stackoverflow.com/questions/56632825/merge-dataframes-when-timestamp-of-one-is-between-another-ones-datetime-interva

2条答案

按热度按时间

uxhixvfz1#

data30min$datetimesE <- data30min$datetimes + 30 * 60 #in_seconds

library(sqldf)

sqldf('select d2.*,d30.location
           from data2min d2
           left join data30min d30
             on d2.datetime between d30.datetimes and d30.datetimesE
      ')

#>   shark depth temperature            datetime       date location
#> 1     A  49.5        26.2 2018-03-20 08:00:00 20/03/2018     SS04
#> 2     A  49.5        25.3 2018-03-20 08:02:00 20/03/2018     SS04
#> 3     A  53.0        24.2 2018-03-20 08:04:00 20/03/2018     SS04
#> 4     A  39.5        26.5 2018-03-20 08:28:00 20/03/2018     SS04
#> 5     A  43.0        26.2 2018-03-20 09:10:00 20/03/2018   Absent
#> 6     A  44.5        26.5 2018-03-20 10:34:00 20/03/2018   Absent

数据：

data2min <- structure(list(shark = c("A", "A", "A", "A", "A", "A"), depth = c(49.5, 
49.5, 53, 39.5, 43, 44.5), temperature = c(26.2, 25.3, 24.2, 
26.5, 26.2, 26.5), datetime = structure(c(1521547200, 1521547320, 
1521547440, 1521548880, 1521551400, 1521556440), class = c("POSIXct", 
"POSIXt"), tzone = ""), date = c("20/03/2018", "20/03/2018", 
"20/03/2018", "20/03/2018", "20/03/2018", "20/03/2018")), row.names = c(NA, 
-6L), class = "data.frame")

data30min <- structure(list(location = c("SS04", "Absent", "Absent", "Absent", 
"SS04", "Absent"), datetimes = structure(c(1521547200, 1521549000, 
1521550800, 1521552600, 1521554400, 1521556200), class = c("POSIXct", 
"POSIXt"), tzone = ""), date = c("2018-03-20", "2018-03-20", 
"2018-03-20", "2018-03-20", "2018-03-20", "2018-03-20"), shark = c("A", 
"A", "A", "A", "A", "A"), datetimesE = structure(c(1521549000, 
1521550800, 1521552600, 1521554400, 1521556200, 1521558000), class = c("POSIXct", 
"POSIXt"))), row.names = c(NA, -6L), class = "data.frame")

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g9icjywg2#

使用data.table非等联接

样本数据

library( data.table)

DT1 <- fread('
location   datetimes        date       shark
SS04   "2018-03-20 08:00:00" 2018-03-20     A
Absent "2018-03-20 08:30:00" 2018-03-20     A
Absent "2018-03-20 09:00:00" 2018-03-20     A
Absent "2018-03-20 09:30:00" 2018-03-20     A
SS04   "2018-03-20 10:00:00" 2018-03-20     A
Absent "2018-03-20 10:30:00" 2018-03-20     A')

DT2 <- fread('
shark       depth     temperature   datetime       date
A            49.5        26.2   "20/03/2018 08:00" 20/03/2018
A            49.5        25.3   "20/03/2018 08:02" 20/03/2018
A            53.0        24.2   "20/03/2018 08:04" 20/03/2018
A            39.5        26.5   "20/03/2018 08:28" 20/03/2018
A            43.0        26.2   "20/03/2018 09:10" 20/03/2018
A            44.5        26.5   "20/03/2018 10:34" 20/03/2018
')

DT1[, `:=`( datetimes = as.POSIXct( datetimes, format = "%Y-%m-%d %H:%M:%S" ))]
DT2[, `:=`( datetime = as.POSIXct( datetime, format = "%d/%m/%Y %H:%M" ) )]

编码

DT2[ copy(DT1)[, end := datetimes + lubridate::minutes(30)], location := i.location, 
     on = .( datetime >= datetimes, datetime < end)][]

输出

#    shark depth temperature            datetime       date location
# 1:     A  49.5        26.2 2018-03-20 08:00:00 20/03/2018     SS04
# 2:     A  49.5        25.3 2018-03-20 08:02:00 20/03/2018     SS04
# 3:     A  53.0        24.2 2018-03-20 08:04:00 20/03/2018     SS04
# 4:     A  39.5        26.5 2018-03-20 08:28:00 20/03/2018     SS04
# 5:     A  43.0        26.2 2018-03-20 09:10:00 20/03/2018   Absent
# 6:     A  44.5        26.5 2018-03-20 10:34:00 20/03/2018   Absent

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我来回答

当一个 Dataframe 的时间戳在另一个 Dataframe 的datetime间隔之间时合并 Dataframe

2条答案

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