A Python Voilà simplification library
Project description
Python library to simplify the creation of impactful Voilà dashboards.
The online documentation for the vois library is available here
The PDF documentation for the vois library is available here
The source repository is available here
The vois library contains:
package vois: helper functions for tasks not directly related to ipyvuetify (manage geojson files, create an interactive map to display custom geojson, simplify visualization of hierarchical data in Plotly, create custom SVG visualizations, etc.)
package vois/vuetify: classes to simplify the development of GUIs using ipyvuetify (each source file contains a wrapper to simplify the usage of a ipyvuetify widget)
License
VOIS library is released under a EUPL Version 1.2 license.
Setup
The vois library can be installed using this command:
pip install vois
Tutorial
The tutorial section of the documentation available here provides a step by step example for the construction of a dashboard to display EUROSTAT data on Energy Consumption in Europe.
These are the links to all the steps of the example dashboard deployed and published by Hugginface Spaces:
Step.1: Creation of the dashboard structure using the app class
Step.2: Use Pandas to read the input CSVs and display the DataFrame as a table
Step.3: Add the filtering controls to the dashboard to select countries and sector
Step.4: Add the Plotly Bar Chart View
Step.5: Add the SVG Static Map View
Step.6: Add the Dynamic Map View
Step.7: Add the functions for downloading chart, table and map
Step.8: Manage the parameters passsed in the URL and open external URLs
Step.9: Add an interactive AnimatedPieChart in SVG to select the consumption sector
Step.Final.Dark: Dark version of the final dashboard
An example multi-page dashboard can be viewed at this link: Example multi-page dashboard
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