Authors

• José Manuel Cazorla-Artiles
• Christian González-Martel

Key features

• Retrieve all the data available in the Canary Islands Statistics Institute API.
• Supports searching and downloading data.
• Supports grep-like style search*.
• Supports Most Recent Value queries.

Authors

• Carlos J. Gil Bellosta
• Carlos Neira
• Diego Paniagua Sánchez
• Fiorella Mori Peláez
• Jorge López Pérez
• José Luis Cañadas Reche

Key features

• Retrieve and process microdata provided by Spanish statistical agencies.

Authors

• Rafael Menéndez

Key features

• Retrieve and process morbidity microdata provided by Spanish statistical agencies.
• Provides functions for basic manipulation (filtering, extract diagnoses, reduce data and compute prevalences).

Authors

• Carlos J. Gil Bellosta
• Nuno Carvalho

Key features

• Find maps in the (pre-downloaded) Siane repository, i.e. searching by map year or administrative level using siane_map().
• Bind numerical data to polygons using siane_merge().
• Compatible with IGN maps and INE data.

Authors

• Diego Hernangómez

Key features

• Easy mapping of boundaries of Spain (nation-wide, autonomous communities, provinces, municipalities).
• Use of WMS/WMTS image tiles (Google Maps-like) on either static and interactive maps (with {leaflet}) provided by Spanish public organisms.
• Translates names of autonomous communities and provinces across languages (Spanish, English, Catalan, ...) and into standardized codes (ISO, NUTS, INE...).

Quick demo

library(mapSpain)
library(ggplot2)
galicia <- esp_get_munic_siane(region = "Galicia") |>
  transform(
    Provincia = esp_dict_translate(
      ine.prov.name, "es"
    )
  )
ggplot(galicia) +
  geom_sf(aes(fill = Provincia), color = "grey70") +
  labs(title = "Provincias de Galicia") +
  scale_fill_discrete(
    type = hcl.colors(4, "Blues")
  ) +
  theme_bw()

Authors

• Francisco Goerlich
• Pedro J. Pérez

Key features

• Datasets of historical municipality boundaries from 2002 to 2021.

Authors

• Ángel Delgado Panadero
• Iñaki Úcar
• Diego Hernangómez

Key features

• Takes advantage of INSPIRE Directive.
• Retrieves cadastral spatial data of buildings, parcels and specific cadastral references.
• Get data by bounding box (WFS service) or by municipality (ATOM service).
• Retrieval of imagery via tiles available on the Cadastre.

Quick demo

library(CatastRo)
library(ggplot2)
burgo_osma <- catr_atom_get_buildings(
  "Burgo de Osma"
) |> sf::st_transform(4326)
ggplot(burgo_osma) +
  geom_sf(aes(fill = currentUse), col = NA) +
  scale_fill_viridis_d(na.translate = FALSE) +
  theme_minimal() +
  coord_sf(
    xlim = c(-3.0752, -3.0679),
    ylim = c(41.5831, 41.5884)
  ) +
  labs(
    title = "El Burgo de Osma, Soria",
    fill = "Use of the building"
  )

Authors

• Diego Hernangómez

Key features

• Takes advantage of INSPIRE Directive.
• Retrieves cadastral spatial data of buildings, parcels and specific cadastral references.
• Get data by bounding box (WFS service).

Quick demo

library(CatastRoNav)
library(ggplot2)
olite <- c(-1.646812, 42.814528, -1.638036, 42.820320)
olite_bu <- catrnav_wfs_get_buildings_bbox(
  olite,
  srs = 4326
)
ggplot(olite_bu) +
  geom_sf(aes(fill = value), color = NA) +
  scale_fill_viridis_b(
    show.limits = TRUE,
    breaks = seq(0, 30, 5)
  ) +
  theme_minimal() +
  labs(
    title = "Olite, Navarre",
    subtitle = "Height of buldings",
    fill = "meters"
  )

Authors

• Carlos J. Gil Bellosta
• Luz Frías

Key features

• Access to CartoCiudad API, which provides mapping and other related services for Spain.
• Services: geocoding, reverse geocoding, routes, maps...
• Unlimited and free (no quota limits, no registration procedures).

Quick demo

library(caRtociudad)
soria <- cartociudad_geocode("ayuntamiento soria")
soria_map <- cartociudad_get_map(
  c(soria$lat, soria$lng), 0.3)
ggmap::ggmap(soria_map)

Authors

• Lluís Revilla Sancho

Key features

• Retrieve data from Boletín Oficial del Estado (BOE).
• Retrieve data from Boletín Oficial del Registro Mercantil del Estado (BORME).
• Main function retrieve_sumario() to retrieve summaries by date.
• Additional functions to obtain URLs and download publications.

Quick demo

library(BOE)
library(ggplot2)
sumario <- retrieve_sumario(as.Date("2022-05-06")) |>
  transform(dpt = sub("MINISTERIO", "M.", departament)) |>
  transform(dpt = stringr::str_trunc(dpt, 20))
ggplot(sumario) +
  aes(forcats::fct_infreq(dpt)) +
  geom_bar() +
  coord_flip() +
  theme_minimal() +
  labs(
    title = "Publicaciones por departamento",
    subtitle = "BOE del 6 de mayo de 2022",
    caption = "Fuente: BOE",
    x = NULL
  )

Authors

• Héctor Meleiro

Key features

• Retrieve election data at municipality level.
• Retrieve election data at polling station level.
• Retrieve election candidates data.
• Provides datasets with administrative codes for autonomous communities, provinces, and municipalities, as well as median income data for census tracts.

Quick demo

library(infoelectoral)
library(dplyr)
library(ggplot2)
df <- municipios("congreso", anno="1982", mes="10") |>
  group_by(siglas) |>
  summarise(votos = sum(votos)) |>
  mutate(seats = round(votos / sum(votos) * 350)) |>
  filter(seats >= 10)
df <- ggparliament::parliament_data(
  df, type="semicircle", 7, df$seats)
ggplot(df) +
  aes(x, y, colour = siglas) +
  ggparliament::geom_parliament_seats() + 
  ggparliament::theme_ggparliament() +
  scale_color_manual(values=c(
    "#3399FF", "#3399FF", "#009900", "#0000EB",
    "#F10000", "#F10000", "#F10000", "#FFA500"
  )) +
  theme(legend.position = 'bottom')

Authors

• Lluís Revilla Sancho

Key features

• Retrieve senators data since 1977.
• Retrieve summaries, commissions, documents, initiatives...

Quick demo

library(senadoRES)
library(dplyr)
library(ggplot2)
df <- senadores() |>
  group_by(legislatura) |>
  count(sex) |>
  filter(!is.na(sex)) |>
  mutate(ratio = n/sum(n)) |>
  filter(sex != "male")
ggplot(df) +
  aes(legislatura, ratio) +
  geom_line() +
  geom_hline(yintercept=0.5, linetype=2, col="red") +
  scale_y_continuous(
    labels = scales::percent_format(accuracy = 1)) +
  theme_bw() +
  labs(
    title = "Ratio of women",
    x = "Legislatura",
    y = "% of women"
  )

Authors

• Jorge Cimentada
• Jorge López

Key features

• Retrieve data from datos.gob.es, the open-data initiative from the Spanish Government.
• Currently, supports CSV format and 11 publishers (see publishers_available).
• The identifier of a web-based search can be directly provided to openes_load().
• R-based search via openes_keywords().

Authors

• Diego Hernangómez

Key features

• API package that helps to retrieve data from Banco de España. ~14.000 time series available. Specific series can be search by keyword.
• Includes macroeconomic data from the Statistical Bulletin, key summary indicators, exchange rates and interest rates.
• Helper functions to retrieve some of the most relevant indicators via bde_ind_* functions.
• Specific color palettes and theme for {ggplot2}.

Quick demo

library(tidyBdE)
library(ggplot2)
euribor_month <- bde_ind_euribor_12m_monthly() |>
  subset(Date > "2010-01-01")
ggplot(euribor_month) +
  aes(Date, Euribor_12M_Monthly) +
  geom_line(colour = bde_vivid_pal()(1)) +
  scale_y_continuous(
    labels = scales::number_format(suffix = "%")
  ) +
  theme_bde() +
  labs(
    title = "Euribor 12 months",
    subtitle = "Monthly data",
    caption = "Source: BdE"
  )

Authors

• Manuel Pizarro
• Diego Hernangómez
• Gema Fernández-Avilés

Key features

• Retrieve climatic information registered by the AEMET stations (wind speed, temperature, air pressure...).
• Optional spatial information in sf format.
• Create scientific graphs (climate charts, trend analysis of climate time series, temperature and precipitation anomalies maps, “warming stripes” graphics, climatograms, etc.).

Quick demo

library(climaemet)
library(ggplot2)
temp2020 <- aemet_daily_period(
  "8416",
  start = 2020, end = 2020
)
ggplot(temp2020) +
  geom_col(aes(fecha, tmed, fill = tmed)) +
  scale_fill_gradientn(
    colours = hcl.colors(20, "RdBu", rev = TRUE),
    labels = scales::label_number(suffix = "º")
  ) +
  guides(fill = guide_colorsteps()) +
  theme_minimal() +
  labs(
    title = "Valencia, Spain",
    subtitle = "AEMET Station Id: 8416",
    fill = "Avg. daily temp.",
    y = "Celsius degrees",
    x = "date"
  )

Authors

• Jose V. Die
• Jose R. Caro

Key features

• Dataset of air quality measurements in Spain from 2001 to 2018.
• Measurements of several pollutants: As B(a)P Cd Ni Pb PM10 PM2.5.
• Dataset of measurement stations.

Quick demo

library(dplyr)
library(ggplot2)
selection <- airqualityES::stations |>
  filter(station_name == "Barcelona (Sants)")
df <- airqualityES::airqES |>
  filter(grepl(selection$id, station_id)) |>
  filter(pollutant == "PM10") |>
  mutate(pm10 = rowMeans(
    across(starts_with("D")), na.rm=TRUE)) |>
  mutate(date = as.Date(paste(year, month, 1, sep="-")))
ggplot(df) +
  aes(date, pm10) +
  geom_line() +
  geom_smooth() +
  theme_bw() +
  labs(
    title = "Montly average of PM10",
    subtitle = "Measurement at Barcelona (Sants)"
  )