| Type: | Package |
| Title: | Import 'REDATAM' Files |
| Version: | 2.1.2 |
| Imports: | data.table, janitor, stringi, stringr, tibble |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Depends: | R(≥ 3.5.0) |
| Description: | Import 'REDATAM' formats into R via the 'Open REDATAM' C++ library. The full context of this project and details about the implementation are available in <doi:10.1017/dap.2025.4> (Open Access). |
| License: | Apache License (≥ 2) |
| URL: | https://github.com/litalbarkai/open-redatam |
| BugReports: | https://github.com/litalbarkai/open-redatam/issues |
| RoxygenNote: | 7.3.2 |
| Encoding: | UTF-8 |
| NeedsCompilation: | yes |
| VignetteBuilder: | knitr |
| LinkingTo: | cpp11 |
| Config/testthat/edition: | 3 |
| Packaged: | 2025-04-17 15:25:20 UTC; pacha |
| Author: | Mauricio Vargas Sepulveda
 [aut, cre],
Lital Barkai [aut],
Ivan Krylov [ctb],
Arseny Kapoulkine [ctb] ('pugixml' C++ library),
Oriental Republic of Uruguay [dtc] (Aggregated census data from 2011) |
| Maintainer: | Mauricio Vargas Sepulveda <m.sepulveda@mail.utoronto.ca> |
| Repository: | CRAN |
| Date/Publication: | 2025-04-17 15:40:02 UTC |
redatam: Import 'REDATAM' Files
Description
Import 'REDATAM' formats into R via the 'Open REDATAM' C++ library. The full context of this project and details about the implementation are available in doi:10.1017/dap.2025.4 (Open Access).
Author(s)
Maintainer: Mauricio Vargas Sepulveda m.sepulveda@mail.utoronto.ca (ORCID)
Authors:
Lital Barkai
Other contributors:
Ivan Krylov [contributor]
Arseny Kapoulkine ('pugixml' C++ library) [contributor]
Oriental Republic of Uruguay (Aggregated census data from 2011) [data contributor]
See Also
Useful links:
Report bugs at https://github.com/litalbarkai/open-redatam/issues
Read REDATAM dictionary
Description
Read a DIC or DICX dictionary file directly into R.
Usage
read_redatam(dictionary)
Arguments
dictionary |
A character string with the path to the dictionary file. It allows relative paths. |
Value
A list of tibbles, each one representing a table with the census entities (or levels) and their attributes (or variables).
Examples
# Read a dictionary file (Uruguay 2011, aggregated)
zip <- system.file("extdata", "uru2011mini.zip", package = "redatam")
dout <- paste(tempdir(), "uru2011mini", sep = "/")
unzip(zip, exdir = dout)
read_redatam(paste(dout, "uru2011mini.dic", sep = "/"))
# or equivalently
read_redatam(paste(dout, "uru2011mini.dicx", sep = "/"))