Encontre a temperatura média de um intervalo de data e hora para cada dia no dataframe

Aqui estão duas variações. O primeiro filtra os dados para horários de 13h (13h em 24h) a 4h59min59s e depois resume para fornecer uma linha por data.

library(dplyr); library(lubridate)
df |>
  filter(hour(datetime) %in% 13:16) |>
  summarize(avg_temp = mean(temp), .by = date)

# A tibble: 1 × 2
  date                avg_temp
  <dttm>                 <dbl>
1 2019-06-01 00:00:00     82.6

Ou poderíamos manter todas as linhas e adicionar uma nova coluna que apenas faça referência aos horários das 13h às 17h para aquela data.

df |>
  mutate(avg_temp = mean(temp[hour(datetime) %in% 13:16]), .by = date)

   name    date                time   datetime             temp avg_temp
   <chr>   <dttm>              <time> <dttm>              <dbl>    <dbl>
 1 waldorf 2019-06-01 00:00:00 00:00  2019-06-01 00:00:00  72.9     82.6
 2 waldorf 2019-06-01 00:00:00 01:00  2019-06-01 01:00:00  70.6     82.6
 3 waldorf 2019-06-01 00:00:00 02:00  2019-06-01 02:00:00  69.7     82.6
 4 waldorf 2019-06-01 00:00:00 03:00  2019-06-01 03:00:00  69.6     82.6
 5 waldorf 2019-06-01 00:00:00 04:00  2019-06-01 04:00:00  68       82.6
 6 waldorf 2019-06-01 00:00:00 05:00  2019-06-01 05:00:00  68.1     82.6
 7 waldorf 2019-06-01 00:00:00 06:00  2019-06-01 06:00:00  67.9     82.6
 8 waldorf 2019-06-01 00:00:00 07:00  2019-06-01 07:00:00  67.8     82.6
 9 waldorf 2019-06-01 00:00:00 08:00  2019-06-01 08:00:00  69.6     82.6
10 waldorf 2019-06-01 00:00:00 09:00  2019-06-01 09:00:00  71.9     82.6
# ℹ 14 more rows

Uma linha na base R.

> aggregate(temp ~ date, dat, mean, subset=format(datetime, '%H') %in% 13:16)
        date     temp
1 2019-06-01 82.60000
2 2019-06-02 75.23326

Dados:

> dput(dat)
structure(list(name = c("waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf"), date = structure(c(1559347200, 1559347200, 
1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 
1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 
1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 
1559347200, 1559347200, 1559347200, 1559347200, 1559433600, 1559433600, 
1559433600, 1559433600, 1559433600, 1559433600, 1559433600, 1559433600, 
1559433600, 1559433600, 1559433600, 1559433600, 1559433600, 1559433600, 
1559433600, 1559433600, 1559433600, 1559433600, 1559433600, 1559433600, 
1559433600, 1559433600, 1559433600, 1559433600), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), time = structure(c(0, 3600, 7200, 10800, 14400, 18000, 
21600, 25200, 28800, 32400, 36000, 39600, 43200, 46800, 50400, 
54000, 57600, 61200, 64800, 68400, 72000, 75600, 79200, 82800, 
0, 3600, 7200, 10800, 14400, 18000, 21600, 25200, 28800, 32400, 
36000, 39600, 43200, 46800, 50400, 54000, 57600, 61200, 64800, 
68400, 72000, 75600, 79200, 82800), class = c("hms", "difftime"
), units = "secs"), datetime = structure(c(1559347200, 1559350800, 
1559354400, 1559358000, 1559361600, 1559365200, 1559368800, 1559372400, 
1559376000, 1559379600, 1559383200, 1559386800, 1559390400, 1559394000, 
1559397600, 1559401200, 1559404800, 1559408400, 1559412000, 1559415600, 
1559419200, 1559422800, 1559426400, 1559430000, 1559433600, 1559437200, 
1559440800, 1559444400, 1559448000, 1559451600, 1559455200, 1559458800, 
1559462400, 1559466000, 1559469600, 1559473200, 1559476800, 1559480400, 
1559484000, 1559487600, 1559491200, 1559494800, 1559498400, 1559502000, 
1559505600, 1559509200, 1559512800, 1559516400), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), temp = c(72.9, 70.6, 69.7, 69.6, 68, 68.1, 67.9, 
67.8, 69.6, 71.9, 75.6, 78.3, 80.1, 80.8, 82.8, 83.5, 83.3, 82.9, 
81.5, 79.4, 77.6, 72.4, 70.6, 69.8, 79.1696243973915, 71.9027052666293, 
69.2034403611906, 68.2508759198477, 69.7428444263292, 80.7097340616398, 
79.9461756611709, 74.5525326303905, 69.4499952176819, 71.9371872948017, 
72.6230055170134, 71.5147781700827, 71.6798864101525, 69.8887843630277, 
72.7993230648804, 83.3064043627353, 74.9385100279702, 83.040720809577, 
73.2019899271429, 68.1022546513006, 80.9702613738598, 71.5576161674224, 
70.9758715190925, 71.06971974