Parse and manipulate structured data and metadata in a tabular format.
Metatab is a data format that allows structured metadata -- the sort you'd normally store in JSON, YAML or XML -- to be stored and edited in tabular forms like CSV or Excel. Metatab files look exactly like you'd expect, so they are very easy for non-technical users to read and edit, using tools they already have. Metatab is an excellent format for creating, storing and transmitting metadata. For more information about metatab, visit http://metatab.org.
This repository has a Python module and executable. For a Javascript version, see the metatab-js repository.
Metatab is a tabular format that allows storing metadata for demographics, health and research datasets in a tabular format. The tabular format is much easier for data creators to write and for data consumers to read, and it allows a complete data packages to be stored in a single Excel file.
Install the package from PiPy with:
$ pip install metatabOr, install the master branch from github with:
$ pip install https://github.com/CivicKnowledge/metatab-py.gitThen test parsing using a remote file with:
$ metatab -j https://raw.githubusercontent.com/CivicKnowledge/metatab-py/master/test-data/example1.csvRun metatab -h to get other program options.
The test-data directory has test files that also serve as examples to parse. You can either clone the repo and parse them from the files, or from the Github page for the file, click on the raw button to get raw view of the flie, then copy the URL.
See Getting Started for an initial tutorial, or the other guides in the docs directory on Github