DataViz

DataViz helps you to create plots quickly. You declare what information (the data source) to display and how to display it (the plot type and style). DataViz tries to be as close as possible to the Vega-Lite visualization grammar. Available backends for plotting are matplotlib and bokeh.

Installation

Install via pip:

$ pip install dataviz

Example

To display a plot in Jupyter notebook:

import dataviz as dv

spec = {
    "width": 600,
    "height": 300,

    "data": {
        "values": [
            {"time": "2021-01-01", "value": 28},
            {"time": "2021-01-02", "value": 55},
            {"time": "2021-01-03", "value": 43},
            {"time": "2021-01-04", "value": 91},
            {"time": "2021-01-05", "value": 81},
            {"time": "2021-01-06", "value": 53},
        ]
    },
    "mark": "line",
    "encoding": {
        "x": {"field": "time", "type": "temporal"},
        "y": {"field": "value", "type": "quantitative"},
        "color": {"value": "red"},
    }
}

fig = dv.figure(spec, 'matplotlib')
fig.show()

This will produce the following plot:

Contribute

• Issue Tracker: https://gitlab.com/librecube/lib/python-dataviz/-/issues
• Source Code: https://gitlab.com/librecube/lib/python-dataviz

To learn more on how to successfully contribute please read the contributing information in the LibreCube guidelines.

Support

If you are having issues, please let us know. Reach us at Matrix or via Email.

License

The project is licensed under the MIT license. See the LICENSE file for details.