# use eval = NOT_CRAN in the chunks connecting to API, to avoid errors or warnings in CRAN checks NOT_CRAN <- identical(tolower(Sys.getenv("NOT_CRAN")), "true") knitr::opts_chunk$set( collapse = TRUE, comment = "#>", purl = NOT_CRAN ) # env keyring withr::local_options(list("keyring_backend" = "env"))
library(meteospain) library(dplyr) library(ggplot2) library(ggforce) library(units) library(sf)
MeteoGalicia service offers the data of the galician automatic meteorological stations network. This network is supported and assessed by the Xunta de Galicia and the data should be trustworthy.
MeteoGalicia API offers data at different temporal resolutions:
In both, "daily" and "monthly", a start_date
(and optionally an end_date
) arguments must be provided,
indicating the period from which retrieve the data.
MeteoGalicia API allows specifying stations code to narrow the data retrieved. So, a character vector of
station codes can be supplied in the stations
argument.
# last measure for all stations api_options <- meteogalicia_options() api_options # current day, only some stations api_options <- meteogalicia_options( resolution = 'current_day', stations = c('10157', '14000', '10045') ) api_options # daily, all stations api_options <- meteogalicia_options( resolution = 'daily', start_date = as.Date('2020-04-25'), end_date = as.Date('2020-05-25') ) api_options # monthly, some stations api_options <- meteogalicia_options( resolution = 'monthly', start_date = as.Date('2020-04-01'), end_date = as.Date('2020-08-01'), stations = c('10157', '14000', '10045') ) api_options
Accessing station metadata for MeteoGalicia is simple:
get_stations_info_from('meteogalicia')
api_options <- meteogalicia_options( resolution = 'monthly', start_date = as.Date('2020-01-01'), end_date = as.Date('2020-12-31') ) galicia_2020 <- get_meteo_from('meteogalicia', options = api_options) galicia_2020
Visually:
galicia_2020 |> units::drop_units() |> mutate(month = lubridate::month(timestamp, label = TRUE)) |> ggplot() + geom_sf(aes(colour = max_temperature)) + facet_wrap(vars(month), ncol = 4) + scale_colour_viridis_c() galicia_2020 |> mutate(month = lubridate::month(timestamp, label = TRUE)) |> ggplot() + geom_histogram(aes(x = precipitation)) + facet_wrap(vars(month), ncol = 4)
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