library(tidyverse)
library(agrometR)
d <- dir("data/rds", full.names = TRUE) |>
map_df(readRDS)
d |>
nrow() |>
scales::comma()
d |>
summarise(across(.cols = fecha_hora, .fns = list(min = min, max = max)))
d |> count(station_id) |> count()
dr <- d |>
group_by(station_id) |>
summarise(across(.cols = fecha_hora, .fns = list(min = min, max = max))) |>
left_join(estaciones_agromet, by = c("station_id" = "ema"))
dr
p <- ggplot(dr) +
geom_segment(aes(
y = as.character(station_id),
yend = as.character(station_id),
x = fecha_hora_min,
xend = fecha_hora_max,
color = institucion
)) +
scale_y_discrete(breaks = NULL) +
scale_color_viridis_d(begin = 0.1, end = 0.9)
p
p + facet_wrap(vars(institucion))
p + facet_wrap(vars(region))
# estaciones_agromet |>
# filter(region == "Magallanes")
# d |>
# filter(fecha_hora == min(fecha_hora))
d |>
filter(station_id == 11) |>
select(-station_id) |>
gather(key, value, -fecha_hora) |>
ggplot(aes(fecha_hora, value)) +
geom_line() +
geom_smooth() +
facet_wrap(vars(key), scales = "free")
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