Installation
You can install the development version of
MobilityDataPT from GitHub with:
# install.packages("remotes")
remotes::install_github("U-Shift/MobilityDataPT")Key functions
1. Administrative Boundaries & Postal Codes
Access Eurostat GISCO postal code datasets and spatial coordinates for Portugal or other EU countries:
# Download and access full postal code database for Portugal
db <- MobilityDataPT::postal_code_database(cntr_id = "PT", year = 2024, crs = 4326)
db |>
dplyr::select(POSTCODE, LAU_NAME, Shape) |>
dplyr::sample_n(5)
#> Simple feature collection with 5 features and 2 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -9.097305 ymin: 38.62705 xmax: -8.624415 ymax: 41.70859
#> Geodetic CRS: WGS 84
#> POSTCODE
#> 1 3800-376
#> 2 4900-861
#> 3 4450-770
#> 4 2695-725
#> 5 2835-530
#> LAU_NAME
#> 1 Esgueira
#> 2 União das freguesias de Viana do Castelo (Santa Maria Maior e Monserrate) e Meadela
#> 3 União das freguesias de Matosinhos e Leça da Palmeira
#> 4 União das freguesias de Santa Iria de Azoia, São João da Talha e Bobadela
#> 5 Santo António da Charneca
#> Shape
#> 1 POINT (-8.624415 40.66091)
#> 2 POINT (-8.807337 41.70859)
#> 3 POINT (-8.701731 41.19593)
#> 4 POINT (-9.097305 38.82328)
#> 5 POINT (-9.013116 38.62705)
# Get spatial coordinates for specific postal codes
coords <- MobilityDataPT::get_postal_code_coordinates(c("1000-001", "2800-001"))
coords
#> Simple feature collection with 2 features and 1 field
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -9.160344 ymin: 38.68097 xmax: -9.13881 ymax: 38.73317
#> Geodetic CRS: WGS 84
#> POSTCODE Shape
#> 663558 2800-001 POINT (-9.160344 38.68097)
#> 675430 1000-001 POINT (-9.13881 38.73317)2. Census Origin-Destination (OD) Data
Retrieve INE Census 2021 Origin-Destination data for home-to-work and home-to-study mobility flows:
# Fetch available region filtering options
regions <- MobilityDataPT::census_od_regions()
#> DataExtracao: 2026-08-27T12:20:20.423+01:00
#> DataUltimoAtualizacao: 2022-11-23
head(regions)
#> id name
#> 1 PT Portugal
#> 2 1 Continente
#> 3 11 Norte
#> 4 111 Alto Minho
#> 5 1601 Arcos de Valdevez
#> 6 160101 Aboim das Choças
# Fetch OD mobility records for a specific region ID (e.g., "PT" or "0603")
od_data <- MobilityDataPT::census_od(id = "PT")
#> IndicadorDsg: População residente empregada ou estudante (N.º) por Local de residência à data dos Censos [2021] (NUTS - 2013), Sexo, Condição perante o trabalho e Local de trabalho ou estudo; Decenal - INE, Recenseamento da população e habitação - Censos 2021
#> MetaInfUrl: https://www.ine.pt/bddXplorer/htdocs/minfo.jsp?var_cd=0011702&lingua=PT
#> DataExtracao: 2026-08-27T12:20:21.982+01:00
#> DataUltimoAtualizacao: 2022-11-23
head(od_data)
#> geocod geodsg dim_3 dim_3_t dim_4 dim_4_t dim_5 dim_5_t
#> 1 PT Portugal 2 M 2 Estudante 40511 Vila Velha de Ródão
#> 2 PT Portugal 2 M 2 Estudante 44401 Santa Cruz da Graciosa
#> 3 PT Portugal T HM 2 Estudante 44401 Santa Cruz da Graciosa
#> 4 PT Portugal 1 H 2 Estudante 40404 Freixo de Espada à Cinta
#> 5 PT Portugal 1 H 2 Estudante 40412 Vinhais
#> 6 PT Portugal 1 H 2 Estudante 44202 Nordeste
#> ind_string valor Periodo
#> 1 1 1 2011
#> 2 1 1 2011
#> 3 1 1 2011
#> 4 2 2 2011
#> 5 2 2 2011
#> 6 2 2 20113. Road & Itinerary Toll Costs
Calculate expected toll costs across vehicle classes (C1, C2, C3, C4) for spatial route itineraries using the Infraestruturas de Portugal API service:
sf_itinerary <- sf::st_read(system.file("extdata/samples",
"tool_itinerary_25AbrilBridge.gpkg",
package = "MobilityDataPT"
), quiet = TRUE)
# Calculate toll costs
tolls <- MobilityDataPT::tools_for_itinerary(sf_itinerary)
tolls
#> $C1
#> [1] 2.25
#>
#> $C2
#> [1] 4.85
#>
#> $C3
#> [1] 6.55
#>
#> $C4
#> [1] 8.45