Since the last release, this package has been integrated into rOpenSpain, a community of R enthusiasts whose ultimate goal is to create high-quality R packages for data mining public Spanish open sources.
From version 1.0.0 onward, we have introduced some improvements and (breaking) changes on the package, in order to provide a smoother interaction with the AEMET API service.
To be able to download data from AEMET you will need a free API key which you can get at https://opendata.aemet.es/centrodedescargas/obtencionAPIKey
Once that you have your API Key, you can use any of the following methods:
aemet_api_key()
This is the recommended option. Just type:
aemet_api_key("YOUR_API_KEY", install = TRUE)
Using install = TRUE
ensures that the API key is stored on your local computer
and it would be reloaded every time you load the library. From now on you can
forget about API keys!
This is a temporary alternative. You can set your API key as an environment variable
Sys.setenv(AEMET_API_KEY = "YOUR_API_KEY")
Note that this is only valid for the current session. You would need to re-run this command each time you restart your session.
.Renviron
fileThis stores your API key permanently on your machine. You can start editing your
.Renviron
running this command:
usethis::edit_r_environ()
Now you can add the following line to you .Renviron
file:
AEMET_API_KEY = YOUR_API_KEY
tidyverse
formatFrom v1.0.0 onward, climaemet provides its results in tibble format. Also, the functions try to guess the correct format of the fields (i.e. something as a Date/Hour now is an hour, numbers are parsed as double, etc.).
See how a tibble is displayed:
# See a tibble in action aemet_last_obs("9434") #> # A tibble: 23 x 25 #> idema lon fint prec alt vmax vv dv lat dmax ubi pres hr stdvv ts #> <chr> <dbl> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 9434 -1.00 2022-02-22 16:00:00 0 249 14.9 11.2 313 41.7 305 ZARAGOZA~ 996. 20 1.4 20.7 #> 2 9434 -1.00 2022-02-22 17:00:00 0 249 13.9 6.7 316 41.7 310 ZARAGOZA~ 996. 17 1.4 17.6 #> 3 9434 -1.00 2022-02-22 18:00:00 0 249 8.8 5.6 300 41.7 300 ZARAGOZA~ 996. 18 0.9 14.7 #> 4 9434 -1.00 2022-02-22 19:00:00 0 249 9.2 5.2 305 41.7 305 ZARAGOZA~ 996. 21 0.5 13.3 #> 5 9434 -1.00 2022-02-22 20:00:00 0 249 8.6 6.3 280 41.7 275 ZARAGOZA~ 997. 33 0.6 12 #> 6 9434 -1.00 2022-02-22 21:00:00 0 249 10.4 8.4 297 41.7 303 ZARAGOZA~ 997. 39 0.9 12 #> 7 9434 -1.00 2022-02-22 22:00:00 0 249 10.4 5.9 293 41.7 290 ZARAGOZA~ 997 31 0.7 10.3 #> 8 9434 -1.00 2022-02-22 23:00:00 0 249 9 2.3 324 41.7 275 ZARAGOZA~ 997. 25 0.8 9.1 #> 9 9434 -1.00 2022-02-23 00:00:00 0 249 5 3.6 306 41.7 308 ZARAGOZA~ 997. 26 0.5 7.7 #> 10 9434 -1.00 2022-02-23 01:00:00 0 249 8 6.2 299 41.7 300 ZARAGOZA~ 996. 28 0.5 7.6 #> # ... with 13 more rows, and 10 more variables: pres_nmar <dbl>, tamin <dbl>, ta <dbl>, tamax <dbl>, #> # tpr <dbl>, stddv <dbl>, inso <dbl>, tss5cm <dbl>, pacutp <dbl>, tss20cm <dbl>
Note that when possible, data representing dates and numbers are converted to the right format.
sf
Another major change in v1.0.0 is the ability of return information on
spatial sf
format, using return_sf = TRUE
. The coordinate reference system
(CRS) used is EPSG 4326, that correspond to the World Geodetic System
(WGS) and return coordinates in latitude/longitude (unprojected coordinates):
# You would need to install `sf` if not installed yet # run install.packages("sf") for installation library(ggplot2) library(dplyr) all_stations <- aemet_last_obs(return_sf = TRUE) # Last hour all_last <- all_stations %>% filter(fint == all_stations[["fint"]][1]) last_hour <- max(all_last$fint) ggplot(all_last) + geom_sf(aes(col = ta), shape = 19, size = 2 ) + labs( title = "Temperature in Spain", subtitle = last_hour, color = "Max temp.\n(celsius)", caption = "Source: AEMET" ) + scale_colour_gradientn( colours = hcl.colors(5, "RdBu", rev = TRUE), guide = "legend", n.breaks = 7 ) + theme_bw() + theme( panel.border = element_blank(), plot.title = element_text(size = 23, face = "bold"), plot.subtitle = element_text(size = 16, face = "italic"), plot.caption = element_text(size = 15), legend.text = element_text(size = 15), legend.title = element_text(size = 15) )
Other enhancements included on the v1.0.0:
get_metadata_aemet()
.ggclimat_walter_lieth()
. This function is now the default for
climatogram_*
functions (experimental). Old behavior can be reproduced
with options ggplot2 = FALSE
.verbose
and ...
). Now it is
possible to pass colors to the plotting functions.climaemet::climaemet_9434_climatogram
,
climaemet::climaemet_9434_temp
, climaemet::climaemet_9434_wind
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