Visualize relational data, on the fly! GNoT combines powerful JS visualizations to data in a PostgreSQL (also Redshift, Vertica, Greenplum, etc.), or MySQL database.

1. Visualizing Jeopardy data with GNoT
2. More examples

1. Python (2.7+, 3.x supported)
2. werkzeug and jinja2 (available in PIP)
3. ML SVM module also requires sklearn (available in PIP). Sklearn requires numpy and scipy.

1. Install werkzeug python library (werkzeug.pocoo.org), and other required libraries. Alternatively use Anaconda.
2. Move .gnot_config to user home directory and edit the parameters.
3. Start the webserver (python webserver.py) from gnot directory.

If you have trouble accessing, see #2

1. A module consists of two files: modules/mymodule.py, templates/mymodule.html
2. Requires an entry in modules/modules.json (with the details of the fields required and supported by mymodule)
3. Look at explore_calendar module for ideas.
4. Make sure mymodule.html extends layout.html (as in explore_calendar.html) to follow uniform templates and load standard .js libraries automatically.

GNoT builds on (and thus heavily benefits from) JS visualization libraries such as D3, NVD3, Crossfilter, DC, Rickshaw, VisualSearch, etc.