https://github.com/JDOsborne1/megametadata
Metadata and data dictionary linking tools for R
https://github.com/JDOsborne1/megametadata
Last synced: 5 months ago
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Metadata and data dictionary linking tools for R
- Host: GitHub
- URL: https://github.com/JDOsborne1/megametadata
- Owner: JDOsborne1
- License: other
- Created: 2019-04-10T08:55:17.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-03-29T16:36:43.000Z (about 5 years ago)
- Last Synced: 2024-08-13T07:15:34.725Z (8 months ago)
- Language: R
- Size: 68.4 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 10
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE.md
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- jimsghstars - JDOsborne1/megametadata - Metadata and data dictionary linking tools for R (R)
README
---
output: github_document
---```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# megametadata[](https://travis-ci.com/JDOsborne1/meta-monster)
[](https://codecov.io/gh/JDOsborne1/meta-monster?branch=master)### Metadata and data dictionary linking tools for R
Designed to be a set of tools for working with the metadata of certain, "core" clean files. Once the ETL steps are complete, it is fairly common to end up with a single data structure for each level of resolution with all the variables needed at that resolution.
One useful thing would be to make the system easy to interact with outside of R, and make it easy for a layperson to understand if needed too.
Enter YAML: A structured language which is both human and machine readable. Since it allows for nested hierarchical variables, without any enforcement on rectangularity, it should be the perfect mix of interactive and automated.
## Installation
You can install the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("JDOsborne1/meta-monster")
```