In jbkunst/agrometR: For downloading meteorological data from the API of agromet.

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(agrometR)

Datos de estaciones

data("estaciones_agromet", package = "agrometR")

estaciones_agromet

Get data

library(dplyr)

set.seed(123456)

stations <- estaciones_agromet |> 
  pull(ema) |> 
  sample(6)

stations

days_to_plot <- 120

date_time_start <- format(Sys.Date() - days_to_plot*24*60*60/100000, "%Y-%m-%d")
date_time_start

date_time_end <- format(Sys.Date(), "%Y-%m-%d")
date_time_end

data_stations <- get_agro_data(
  stations_id = stations, 
  date_start = date_time_start,
  date_end = date_time_end,
  verbose = TRUE  
  )

glimpse(data_stations)

data_stations |> 
  count(station_id)

Plotting

library(ggplot2)

p <- ggplot(data_stations, aes(fecha_hora, temp_promedio_aire, color = factor(station_id), group = station_id)) +
  geom_line(alpha = 0.5) +
  geom_smooth(se = FALSE) +
  scale_color_viridis_d(option = "magma", begin = 0.1, end = 0.9) +
  theme_minimal()

p

p +
  facet_wrap(vars(station_id))

Grouping `fecha_hora`

library(lubridate)

data_stations_daily <- data_stations |> 
  mutate(fecha_hora = floor_date(fecha_hora, "day")) |> 
  group_by(station_id, fecha_hora) |> 
  summarise(
    across(.cols = c(temp_promedio_aire, humed_rel_promedio), .fns = mean, na.rm = TRUE),
    precipitacion_horaria = sum(precipitacion_horaria, na.rm = TRUE),
    .groups = "drop"
  )

glimpse(data_stations_daily)


ggplot(mapping = aes(fecha_hora, temp_promedio_aire, color = factor(station_id), group = station_id)) +
  geom_smooth(data = data_stations, se = FALSE) +
  geom_line(data = data_stations_daily, alpha = .3, size = 2) +
  scale_color_viridis_d(option = "magma", begin = 0.1, end = 0.9) +
  theme_minimal() +
  facet_wrap(vars(station_id))