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Provides tools to discover, download, and cite datasets from Insper Cidades, hosted on the Insper Dataverse repository. Lists datasets and their logical resources, downloads data directly into R, link
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一分鐘完成驗證R package for discovering, downloading, and citing curated datasets from Insper Cidades, hosted on Insper's Dataverse.
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取自儲存庫 README
正在載入完整 README。
檢視完整 README ↗inspercidados gives R users direct access to datasets from Insper
Cidades, hosted on Insper
Dataverse. Insper Cidades
is a multidisciplinary research center at Insper. The package wraps
dataverse so you can
find, download, and cite datasets in a few short commands.
The stable version of the package is available on CRAN.
install.packages("inspercidados")
The development version of the package is available on R-universe.
install.packages(
"inspercidados",
repos = c(
"https://inspercidades.r-universe.dev",
"https://cloud.r-project.org"
)
)
| Function | Purpose |
|---|---|
list_datasets() | List or search available datasets |
list_resources() | List logical resources within a dataset |
get_dataset() | Download a dataset into R |
query_dataset() | Query a parquet dataset without loading it into R |
get_dataverse() | Inspect or download any Insper Dataverse deposit |
cite_dataset() | Generate a citation for a dataset |
open_project() | Open the study repository behind a dataset |
list_datasets() returns a tibble of every dataset in the registry. The
registry is read from GitHub once per session, so datasets added after a
release appear without reinstalling. Offline, the package uses the copy
it shipped with.
library(inspercidados)
list_datasets()
#> # A tibble: 23 × 11
#> alias title description theme region project access is_spatial formats
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <lgl> <chr>
#> 1 itbi_sp Impo… "Registros… Habi… São P… itbi downl… FALSE csv, p…
#> 2 iptu_sp IPTU… "Dados do … Habi… São P… densid… downl… TRUE geojso…
#> 3 alvaras_sp Alva… "Informaçõ… Habi… São P… alvaras downl… TRUE geojso…
#> 4 alvaras_sp_… Alva… "Agregação… Habi… São P… alvaras downl… TRUE geojso…
#> 5 censo_setor… Popu… "Dados pro… Habi… São P… densid… downl… TRUE geojso…
#> 6 iptu_vertic… Grad… "Dados dem… Habi… São P… densid… downl… TRUE geojso…
#> 7 densidade_i… Dens… "Cruzament… Habi… São P… densid… downl… TRUE geojso…
#> 8 geoses_sp Índi… "Índice so… Mult… São P… geoses downl… TRUE geojso…
#> 9 mortalidade… Indi… "Indicador… Saúde São P… mortal… downl… TRUE geojso…
#> 10 ilhas_calor… Medi… "Estatísti… Clim… Rio d… mare downl… TRUE geojso…
#> # ℹ 13 more rows
#> # ℹ 2 more variables: keywords <chr>, doi <chr>
Search by alias, title, description, theme, region, or keywords.
list_datasets("Mobilidade")
#> # A tibble: 12 × 11
#> alias title description theme region project access is_spatial formats
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <lgl> <chr>
#> 1 geoses_sp Índi… Índice soc… Mult… São P… geoses downl… TRUE geojso…
#> 2 pemob_anual Pesq… Base anual… Mobi… Brasil pemob downl… FALSE parque…
#> 3 pemob_harmo… Pesq… Base anual… Mobi… Brasil pemob downl… FALSE parque…
#> 4 embarques_h… Emba… Embarques … Mobi… Brasil motiva downl… FALSE csv, p…
#> 5 embarques_d… Emba… Total de e… Mobi… Brasil motiva downl… FALSE parque…
#> 6 embarques_m… Médi… Média de e… Mobi… Brasil motiva downl… FALSE rds, t…
#> 7 embarques_i… Emba… Embarques … Mobi… Brasil motiva downl… FALSE parque…
#> 8 linhas_moti… Linh… Tabela de … Mobi… Brasil motiva downl… FALSE rds, t…
#> 9 estacoes_mo… Linh… Tabela de … Mobi… Brasil motiva downl… FALSE rds, t…
#> 10 faixa_azul_… Trec… Localizaçã… Mobi… São P… faixa_… downl… TRUE geojso…
#> 11 sinistros_sp Sini… Sinistros … Mobi… São P… faixa_… downl… FALSE parque…
#> 12 sinistros_v… Sini… Localizaçã… Mobi… São P… faixa_… downl… TRUE geojso…
#> # ℹ 2 more variables: keywords <chr>, doi <chr>
The Alvarás study has two separate deposits:
2004–2021 is
alvaras_sp_2004_2021, and
2010–2024 is alvaras_sp. Both
are available through get_dataset().
Pass a short alias to download a registered dataset.
# By alias
embarques <- get_dataset("embarques_mensais")
# Filter by year in multi-year datasets
pemob_2023 <- get_dataset("pemob_anual", year = 2023)
# Select a logical resource and format
pontos <- get_dataset(
"qualidade_ar_mare",
resource = "pontos",
format = "gpkg"
)
list_resources() shows the logical datasets and formats inside a
registered deposit.
list_resources("qualidade_ar_mare")
#> # A tibble: 2 × 6
#> resource title is_spatial years formats default
#> <chr> <chr> <lgl> <chr> <chr> <lgl>
#> 1 dados Medições de qualidade do ar FALSE <NA> parque… TRUE
#> 2 pontos Pontos das medições de qualidade do… TRUE <NA> geojso… FALSE
Set docs = TRUE to return the data alongside its documentation. For
datasets with a dictionary workbook, docs contains that workbook.
result <- get_dataset("iptu_sp", docs = TRUE)
result$data
result$docs
query_dataset() opens a registered parquet resource as a lazy table.
Build a query with dplyr, then call collect() to bring the result into
R. This needs the optional duckdb, DBI, dbplyr, and dplyr
packages.
itbi <- query_dataset("itbi_sp")
itbi |>
dplyr::select(data_de_transacao) |>
head(5) |>
dplyr::collect()
For resources split into annual files, year selects one year. With no
year, the query includes all available years.
cite_dataset() fetches metadata from Dataverse and returns a citation
in plain text, BibTeX, or RIS.
cite_dataset("embarques_mensais")
cite_dataset("embarques_mensais", format = "bibtex")
cite_dataset("embarques_mensais", format = "ris")
Most datasets come from a research study whose pipeline lives in its own
repository. open_project() prints the study, lists its datasets, and
opens the repository.
open_project("faixa_azul")
To learn more about the package, check https://inspercidades.github.io/inspercidados/