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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# statcodelists <img src="man/figures/logo.png" align="right" />
<!-- badges: start -->
[](https://cran.r-project.org/package=statcodelists)
[](https://cran.r-project.org/package=statcodelists)
[](https://cran.r-project.org/package=iotables)
[](https://github.com/antaldaniel/statcodelists)
[](https://creativecommons.org/publicdomain/zero/1.0/)
[](https://dataobservatory.eu/)
[](https://doi.org/10.5281/zenodo.6751783)
<!-- badges: end -->
The goal of `statcodelists` is to promote the reuse and exchange of statistical information and related metadata with making the internationally standardized SDMX code lists available for the R user. SDMX has been published as an ISO International Standard (ISO 17369). The metadata definitions, including the codelists are updated regularly according to the standard. The authoritative version of the code lists made available in this package is <https://sdmx.org/?page_id=3215/>.
## Installation
You can install `statcodelists` from CRAN:
```{r, eval=FALSE}
install.packages("statcodelists")
```
or install the development version of `statcodelists` like so:
``` r
devtools::install_github("antaldaniel/statcodelists")
```
Cross-domain concepts in the SDMX framework describe concepts relevant to many, if not all, statistical domains. SDMX recommends using these concepts whenever feasible in SDMX structures and messages to promote the reuse and exchange of statistical information and related metadata between organisations.
Code lists are predefined sets of terms from which some statistical coded concepts take their values. SDMX cross-domain code lists are used to support cross-domain concepts. The use of common code lists will help users to work even more efficiently, easing the maintenance of and reducing the need for mapping systems and interfaces delivering data and metadata to them. Therefore, a choice over code lists has a great impact on the efficiency of data sharing.
`statcodelists` helps the use of the latest codelist in your R workflow.
```{r codebooks}
library(statcodelists)
data("codebooks")
```
```{r printcodebooks, echo=FALSE, results='asis'}
knitr::kable(codebooks)
```
## Example: Codelist Frequency
```{r cl_freq}
data("CL_FREQ")
```
```{r printfreq, echo=FALSE, results='asis'}
knitr::kable(CL_FREQ)
```
Further recommended code values for expressing general statistical concepts like `not applicable`, etc., can be found in section `Generic codes` of the [Guidelines for the creation and management of SDMX Cross-Domain Code Lists](https://sdmx.org/?page_id=4345).
For further codelists used by reliable statistical agency but not harmonized on SDMX level please consult the [SDMX Global Registry](https://registry.sdmx.org/) [Codelists](https://registry.sdmx.org/items/codelist.html) page.
The creator of this package is not affiliated with SDMX, and this package was has not been endorsed by SDMX.
## Code of Conduct
Please note that the `statcodelists` project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.