https://github.com/christophergandrud/dpmr
Data Package Manager for R
https://github.com/christophergandrud/dpmr
Last synced: 4 months ago
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Data Package Manager for R
- Host: GitHub
- URL: https://github.com/christophergandrud/dpmr
- Owner: christophergandrud
- License: gpl-3.0
- Created: 2014-08-03T11:10:04.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2017-07-14T05:23:27.000Z (almost 8 years ago)
- Last Synced: 2024-08-13T07:14:18.084Z (8 months ago)
- Language: R
- Homepage: http://christophergandrud.github.io/dpmr/
- Size: 173 KB
- Stars: 56
- Watchers: 9
- Forks: 6
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
Data Package Manager for R
====
Version: 0.1.9 [](http://cran.r-project.org/package=dpmr)
[](https://travis-ci.org/christophergandrud/dpmr)
## Description
The R package for creating and installing data packages that follow the
[Open Knowledge Foundation](https://okfn.org/)'s
[Data Package Protocol](http://dataprotocols.org/data-packages/).
**dpmr** has three core functions:
- `datapackage_init`: initialises a new data package from an R data frame and
(optionally) a meta data list.
- `datapackage_install`: installs a data package either stored locally or
remotely, e.g. on GitHub.
- `datapackage_info:` reads a data package's metadata (stored in its
*[datapackage.json](http://dataprotocols.org/data-packages/)*
file) into the R Console and (optionally) as a list.
## Examples
### Create Data Packages
To initiate a barebones data package in the current working directory called
`My_Data_Package` use:
```r
# Create fake data
A <- B <- C <- sample(1:20, size = 20, replace = TRUE)
ID <- sort(rep('a', 20))
Data <- data.frame(ID, A, B, C)
datapackage_init(df = Data, package_name = 'My_Data_Package')
```
This will create a data package with barebones metadata in a
*[datapackage.json](http://dataprotocols.org/data-packages/)*
file. You can then edit this by hand.
Alternatively, you can also create a list with the metadata in R and have this
included with the data package:
```r
meta_list <- list(name = 'My_Data_Package',
title = 'A fake data package',
last_updated = Sys.Date(),
version = '0.1',
license = data.frame(type = 'PDDL-1.0',
url = 'http://opendatacommons.org/licenses/pddl/'),
sources = data.frame(name = 'Fake',
web = 'No URL, its fake.'))
datapackage_init(df = Data, meta = meta_list)
```
Note if you don't include the `resources` fields in your metadata list, then
they will automatically be added. These fields identify the data files' paths
and data `schema`.
### Installing Data Packages
#### Locally
To load a data package called [gdp](https://github.com/datasets/gdp) stored in
the current working directory use:
```r
gdp_data <- datapackage_install(path = 'gdp/')
```
#### From the web
You can install a package stored remotely using its URL. In this example
we directly download the gdp data package from GitHub using the URL for its
zip file:
```r
URL <- 'https://github.com/datasets/gdp/archive/master.zip'
gdp_data <- datapackage_install(path = URL)
```
## Get Data Package Metadata
Use `datapackage_info` to read a data package's metadata into R:
```r
# Print information when working directory is a data package
datapackage_info()
```
## To-do for *v0.2*
- [ ] `datapackage_update` for updating a data package's data and metadata.
- [ ] Specify data variable descriptions in meta list.
- [ ] Load inline data from the *datapackage.json* file.
- [ ] Load data from a GitHub repo using GitHub usernames and repos.
- [ ] Integrate [Octopub API](https://octopub.io/api#/datasets).
---
Licensed under
[GPL-3](LICENSE.md)