我有两个带有 POSIXct 格式时间数据的数据框和一个我需要匹配的相应位置。一个数据集包含一系列 30 分钟的时间段以及位置数据。
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
第二个数据集每2分钟记录一次时间数据。
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中的时间 bin (datetimes) 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的所有数据对应于第一个数据集中的一个 bin在 30 分钟内分配给所有值的位置值。
我想我可以使用 data.table 但我对如何处理这个没有信心。
理想情况下，我想创建一个这样的数据集，根据第一个数据集的相应时间仓，将第一个数据集的位置添加到第二个数据集。
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
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
资料：
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")
使用 data.table 非相等连接
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" ) )]
代码
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