aopdata

Download data from the Access to Opportunities Project (AOP)

https://github.com/ipeagit/aopdata

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Keywords

data r transport transport-accessibility transport-planning
Last synced: 6 months ago · JSON representation

Repository

Download data from the Access to Opportunities Project (AOP)

Basic Info
Statistics
  • Stars: 14
  • Watchers: 5
  • Forks: 4
  • Open Issues: 1
  • Releases: 11
Topics
data r transport transport-accessibility transport-planning
Created about 5 years ago · Last pushed about 1 year ago
Metadata Files
Readme

README.md

aopdata: Data from the Access to Opportunities Project

CRAN/METACRAN Version CRAN/METACRAN Total downloads Codecov test coverage cmd check status <!-- badges: end -->

aopdata is an R package to download data from the Access to Opportunities Project (AOP). The AOP is a research initiative led by the Institute for Applied Economic Research (Ipea) with the aim to study transport access to opportunities in Brazilian cities.

The aopdata package brings annual estimates of access to employment, health, education and social protection services by transport mode at a fine spatial resolution for the 20 largest cities in Brazil. The package also brings data on the spatial distribution of population by sex, race, income and age, as well as the distribution of jobs, schools, health care facilities and social assistance reference centers.

Data for 2017, 2018 and 2019 are already available, and cover accessibility estimates by car and active transport modes (walking and cycling) for the 20 largest cities in the country, and by public transport for over 9 major cities. More information on the AOP website.

Installation

```R

From CRAN

install.packages("aopdata") library(aopdata)

or use the development version with latest features

utils::remove.packages('aopdata') devtools::install_github("ipeaGIT/aopdata", subdir = "r-package") library(aopdata)

```

Overview of the package

The aopdata package includes five core functions.

  • read_population() - Download population data
  • read_landuse() - Download landuse data
  • read_access() - Download accessibility estimates
  • aopdata_dictionary() - Opens aopdata data dictionary on a web browser
  • read_grid() - Download the H3 hexagonal spatial grid

For a detailed explanations of these functions, check the vignettes: - Mapping urban accessibility - Mapping population data - Mapping land use data - Analyzing inequality in access to opportunities

Basic Usage

Data dictionary

The dictionary of data columns is presented in the documentation of each function. However, you can also open the data dictionary on a web browser by running:

```{R}

for English

aopdata_dictionary(lang = 'en')

for Portuguese

aopdata_dictionary(lang = 'pt') ```

Accessibility estimates

The read_access() function downloads accessibility estimates for a given city, mode and year. For the sake of convenience, this function will also automatically download the population and land use data for the cities selected. Note that accessibility estimates are available for peak and off-peak periods for public_transportand car modes.

```{r}

Download accessibility, population and land use data

cur <- readaccess( city = 'Curitiba', mode = 'publictransport', peak = TRUE, year = 2019 ) ```

You many also set the parameter geometry = TRUE so that functions return a spatial sf object with the geometries of the H3 spatial grid.

```{r}

Download accessibility, population and land use data

cur <- readaccess( city = 'Curitiba', mode = 'publictransport', peak = TRUE, year = 2019, geometry = TRUE ) ```

Population and land use data

In case you are only interested in using the population and land use data generated by the Access to Opportunities Project, you can download these data sets separately. Please note that the population available comes from the latest Brazilian 2010 census, while land use data cna be downloaded for 2017, 2018 or 2019.

```{r}

Land use data

lufor <- readlanduse( city = 'Fortaleza', year = 2019, geometry = TRUE )

Population data

popfor <- readpopulation( city = 'Fortaleza', year = 2010, geometry = TRUE ) ```

Read only spatial grid data

In case you would like to download only the H3 spatial grid of cities in the AOP project, you can use the read_grid() function.

```{R} h3for <- readgrid(city = 'Fortaleza')

```

Note

In all of the functions above, note that:

  • The city parameter can also be a 3-letter abbreviation of the city. R df <- read_access(city = 'cur', mode = 'public_transport', year = 2019) df <- read_grid(city = 'for')
  • You may also download the data for all cities of the project at once using city = 'all': ```{R} all <- read_landuse(city = 'all', year = 2019)

```

Acknowledgement ipea

The R package aopdata is developed by a team at the Institute for Applied Economic Research (Ipea), Brazil.

Citation

If you use this package in your own work, please cite it as one of the publications below:

Population and land use data

  • Pereira, Rafael H. M. et al. (2022) Distribuição espacial de características sociodemográficas e localização de empregos e serviços públicos das vinte maiores cidades do Brasil. Texto para Discussão 2772. Ipea - Instituto de Pesquisa Econômica Aplicada. Available at http://repositorio.ipea.gov.br/handle/11058/11225

Accessibility data

  • Pereira, Rafael H. M. et al. (2022) Estimativas de acessibilidade a empregos e serviços públicos via transporte ativo, público e privado nas 20 maiores cidades do Brasil em 2017, 2018, 2019. Texto para Discussão. Ipea - Instituto de Pesquisa Econômica Aplicada.

Owner

  • Name: IpeaDIRUR
  • Login: ipeaGIT
  • Kind: organization

GitHub Events

Total
  • Release event: 1
  • Watch event: 1
  • Push event: 14
  • Create event: 1
Last Year
  • Release event: 1
  • Watch event: 1
  • Push event: 14
  • Create event: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 54
  • Total pull requests: 3
  • Average time to close issues: about 2 months
  • Average time to close pull requests: 2 days
  • Total issue authors: 8
  • Total pull request authors: 3
  • Average comments per issue: 1.15
  • Average comments per pull request: 0.0
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 2.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • rafapereirabr (45)
  • kauebraga (2)
  • dhersz (2)
  • elisa-fink (1)
  • beatrizmilz (1)
  • joaoparga (1)
  • Joaobazzo (1)
  • igorlaltuf (1)
Pull Request Authors
  • Joaobazzo (1)
  • diegobt86 (1)
  • mvpsaraiva (1)
Top Labels
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priority (6) help wanted (4)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 426 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 11
  • Total maintainers: 1
cran.r-project.org: aopdata

Data from the 'Access to Opportunities Project (AOP)'

  • Versions: 11
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 426 Last month
Rankings
Forks count: 12.8%
Stargazers count: 21.1%
Average: 25.1%
Downloads: 26.4%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Maintainers (1)
Last synced: 7 months ago

Dependencies

r-package/DESCRIPTION cran
  • R >= 3.5.0 depends
  • checkmate * imports
  • curl * imports
  • data.table * imports
  • httr >= 1.4.1 imports
  • sf >= 0.9 imports
  • utils * imports
  • covr * suggests
  • dplyr >= 0.8 suggests
  • ggplot2 >= 3.3.1 suggests
  • knitr * suggests
  • rmarkdown >= 2.6 suggests
  • scales * suggests
  • testthat * suggests
  • units * suggests
.github/workflows/R-CMD-CHECK.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/upload-artifact main composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
.github/workflows/R-CMD-check-CRAN.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/upload-artifact main composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
.github/workflows/pkgdown.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite
.github/workflows/test-coverage.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • r-lib/actions/setup-r v1 composite