Download all pRycollection datasets

You can get all available datasets at once in a .csv format from the Zenodo repository. Make sure you have the frictionless r package installed before proceeding.

#install.package("frictionless")
library(frictionless)

# Read data from datapackage.json

pRydata <- frictionless::read_package(
  "https://zenodo.org/records/16744968/files/datapackage.json"
)
pRydata
#> A Data Package with 6 resources:
#> • py_creditcoops
#> • py_deathcauses
#> • py_weather
#> • py_weekly_crime
#> • py_temperature
#> • py_streetcrime
#> Use `unclass()` to print the Data Package as a list.

Calling the variable pRydata gives you all datasets. Select the data you are interested in as follow and print the first six rows of the py_temperature data.

py_temperature <- read_resource(pRydata, "py_temperature")
head(py_temperature)
#> # A tibble: 6 × 6
#>   country  ISO   city     week      avg_temp holiday
#>   <chr>    <chr> <fct>    <chr>        <dbl>   <dbl>
#> 1 Paraguay PY    Asuncion 1/4/2016      27.8       0
#> 2 Paraguay PY    Asuncion 1/11/2016     30.3       0
#> 3 Paraguay PY    Asuncion 1/18/2016     29.9       0
#> 4 Paraguay PY    Asuncion 1/25/2016     27.3       1
#> 5 Paraguay PY    Asuncion 2/1/2016      26.6       0
#> 6 Paraguay PY    Asuncion 2/8/2016      30.1       0

All datasets have additional metadata, but stored in a separate json file. If you are interested in the schema type the following two lines of code:

temp_schema <- pRydata |>
  get_schema("py_temperature")
str(temp_schema)
#> List of 1
#>  $ fields:List of 6
#>   ..$ :List of 3
#>   .. ..$ name       : chr "country"
#>   .. ..$ type       : chr "string"
#>   .. ..$ description: chr "Country name"
#>   ..$ :List of 3
#>   .. ..$ name       : chr "ISO"
#>   .. ..$ type       : chr "string"
#>   .. ..$ description: chr "ISO code"
#>   ..$ :List of 4
#>   .. ..$ name       : chr "city"
#>   .. ..$ type       : chr "string"
#>   .. ..$ constraints:List of 1
#>   .. .. ..$ enum: chr [1:5] "Asuncion" "Capiata" "Ciudad del Este" "Luque" ...
#>   .. ..$ description: chr "City name."
#>   ..$ :List of 3
#>   .. ..$ name       : chr "week"
#>   .. ..$ type       : chr "string"
#>   .. ..$ description: chr "Date as week."
#>   ..$ :List of 3
#>   .. ..$ name       : chr "avg_temp"
#>   .. ..$ type       : chr "number"
#>   .. ..$ description: chr "Average temperature of the week."
#>   ..$ :List of 3
#>   .. ..$ name       : chr "holiday"
#>   .. ..$ type       : chr "number"
#>   .. ..$ description: chr "Dummy variable if the week has a holiday."

If you use the package or any dataset from this package, please cite the package or dataset.

citation("pRycollection")
#> To cite pRycollection in publications please use:
#> 
#>   Schneider A (2025). _pRycollection: Diverse datasets from Paraguay_.
#>   R package version 0.0.1,
#>   <https://github.com/schneiderpy/pRycollection/>.
#> 
#> Please also cite the related data package:
#> 
#>   Schneider A (2025). "pRydata: Diverse datasets from Paraguay."
#>   doi:10.5281/zenodo.16729963
#>   <https://doi.org/10.5281/zenodo.16729963>.
#> 
#> To see these entries in BibTeX format, use 'print(<citation>,
#> bibtex=TRUE)', 'toBibtex(.)', or set
#> 'options(citation.bibtex.max=999)'.

Andreas Schneider