我有一个文件列表（“x”），每十分钟就有一次温度。每个 ID 都是列表中的一个单独条目，并具有一组关联的温度。这是一个示例：
head(x)
$165.212
ID Date Time DateTime Temp
165.212 2023-07-18 10:31:00 2023-07-18 10:31:00 20.37
164.212 2023-07-18 10:41:00 2023-07-18 11:35:00 23.4
164.212 2023-07-18 10:51:00 2023-07-18 11:35:00 23.8
Lux Fx Sex Sp TimeOfDay Hour
3060 164.212 M WT 10.58416667 2024-07-18 11:00:00
1287 164.212 M WT 10.75083333 2024-07-18 11:00:00
1128 164.212 M WT 10.91750000 2024-07-18 11:00:00
$164.314
ID Date Time DateTime Temp
164.314 2023-07-18 10:31:00 2023-07-18 11:35:00 32.5
164.314 2023-07-18 10:41:00 2023-07-18 11:35:00 33.2
164.314 2023-07-18 10:51:00 2023-07-18 11:35:00 22.8
Lux Fx Sex Sp TimeOfDay Hour
3060 164.314 M WT 10.58416667 2024-07-18 11:00:00
1287 164.314 M WT 10.75083333 2024-07-18 11:00:00
2700 164.314 M WT 10.91750000 2024-07-18 11:00:00
我想创建一个 for 循环，获取列表中的每个条目并计算该 ID 号的每小时和每日平均温度，最好是一个包含 ID、平均每小时温度和日期/时间的新列表。
我创建了一个列（“小时”），将小时四舍五入到最接近的小时，我想根据这些值将数据聚合到组中。
这是我正在使用的代码，但我不明白为什么它不起作用。我知道我需要指定我正在制作一个新列表。
for (each in x) {
hour_t$ = x %>%
group_by(Hour) %>%
summarise(AvgTemperature = mean(Temp, na.rm = TRUE))
}
示例数据（最佳猜测）：
list(`165.212` = structure(list(ID = c("165.212", "164.212",
"164.212"), Date = structure(c(19556, 19556, 19556), class = "Date"),
Time = c("10:31:00", "10:41:00", "10:51:00"), DateTime = structure(c(1689676260,
1689680100, 1689680100), class = c("POSIXct", "POSIXt"), tzone = "UTC"),
Temp = c(20.37, 23.4, 23.8), Lux = c(3060L, 1287L, 1128L),
Fx = c(164.212, 164.212, 164.212), Sex = c("M", "M", "M"),
Sp = c("WT", "WT", "WT"), TimeOfDay = c("10.58416667 2024-07-18",
"10.75083333 2024-07-18", "10.91750000 2024-07-18"), Hour = c("11:00:00",
"11:00:00", "11:00:00")), row.names = c(NA, -3L), class = "data.frame"),
`164.314` = structure(list(ID = c("164.314", "164.314", "164.314"
), Date = structure(c(19556, 19556, 19556), class = "Date"),
Time = c("10:31:00", "10:41:00", "10:51:00"), DateTime = structure(c(1689680100,
1689680100, 1689680100), class = c("POSIXct", "POSIXt"
), tzone = "UTC"), Temp = c(32.5, 33.2, 22.8), Lux = c(3060L,
1287L, 2700L), Fx = c(164.314, 164.314, 164.314), Sex = c("M",
"M", "M"), Sp = c("WT", "WT", "WT"), TimeOfDay = c("10.58416667 2024-07-18",
"10.75083333 2024-07-18", "10.91750000 2024-07-18"),
Hour = c("11:00:00", "11:00:00", "11:00:00")), row.names = c(NA,
-3L), class = "data.frame"))
这会给你想要的结果吗@Liz M.？
library(tidyverse)
data_list <- list(`165.212` = structure(list(ID = c("165.212", "164.212",
"164.212"), Date = structure(c(19556, 19556, 19556), class = "Date"),
Time = c("10:31:00", "10:41:00", "10:51:00"), DateTime = structure(c(1689676260,
1689680100, 1689680100), class = c("POSIXct", "POSIXt"), tzone = "UTC"),
Temp = c(20.37, 23.4, 23.8), Lux = c(3060L, 1287L, 1128L),
Fx = c(164.212, 164.212, 164.212), Sex = c("M", "M", "M"),
Sp = c("WT", "WT", "WT"), TimeOfDay = c("10.58416667 2024-07-18",
"10.75083333 2024-07-18", "10.91750000 2024-07-18"), Hour = c("11:00:00",
"11:00:00", "11:00:00")), row.names = c(NA, -3L), class = "data.frame"),
`164.314` = structure(list(ID = c("164.314", "164.314", "164.314"
), Date = structure(c(19556, 19556, 19556), class = "Date"),
Time = c("10:31:00", "10:41:00", "10:51:00"), DateTime = structure(c(1689680100,
1689680100, 1689680100), class = c("POSIXct", "POSIXt"
), tzone = "UTC"), Temp = c(32.5, 33.2, 22.8), Lux = c(3060L,
1287L, 2700L), Fx = c(164.314, 164.314, 164.314), Sex = c("M",
"M", "M"), Sp = c("WT", "WT", "WT"), TimeOfDay = c("10.58416667 2024-07-18",
"10.75083333 2024-07-18", "10.91750000 2024-07-18"),
Hour = c("11:00:00", "11:00:00", "11:00:00")), row.names = c(NA,
-3L), class = "data.frame"))
new_data_list <- map(data_list, .f = ~.x %>% group_by(ID, Hour) %>%
summarise(AvgTemperature = mean(Temp, na.rm = TRUE)))
#> `summarise()` has grouped output by 'ID'. You can override using the `.groups`
#> argument.
#> `summarise()` has grouped output by 'ID'. You can override using the `.groups`
#> argument.
new_data_list
#> $`165.212`
#> # A tibble: 2 × 3
#> # Groups: ID [2]
#> ID Hour AvgTemperature
#> <chr> <chr> <dbl>
#> 1 164.212 11:00:00 23.6
#> 2 165.212 11:00:00 20.4
#>
#> $`164.314`
#> # A tibble: 1 × 3
#> # Groups: ID [1]
#> ID Hour AvgTemperature
#> <chr> <chr> <dbl>
#> 1 164.314 11:00:00 29.5
创建于 2024-07-03，使用 reprex v2.1.0
如果没有，请在下面评论，我们可以相应调整。