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survey-dashboard

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survey-dashboard

A Dashboard displaying survey data in an interactive way and allow for interactive exploration.

  • 0.1.0
  • PyPI
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Maintainers
2

Survey dashboard

A dashboard to display survey data in an interactive way.

Overview

This repository contains a dashboard using Panel and Bokeh, developed to display data from HMC surveys in an interactive exploratory way. It is designed such that the code for the interactive visualizations might be reused for other projects. Example of a deployed version can be found here

Some impressions: dashboard_overview dashboard_methods Dashboard_survey_data_explorer

Installation

After downloading the git repository you can install the software either with pip or poetry. We recommend setting it up in a separate python virtual environment.

pip install survey_dashboard

or

poetry install .

Usage

After installation you can start the app, i.e the panel server/bokeh server.

panel serve --port 50006 survey_dashboard/ 

If you have given the dashboard a specific layout like the layout specific to HMC, which is on the hmc_specific branch, you might have to link to to a specific template.

panel serve --port 50006 survey_dashboard/ --static-dirs en_files=./survey_dashboard/hmc_layout/static/en_files

  • Navigate to http://localhost:50006/ in your browser.

Deployment

To embed the dashboard into any website, first you have to host a bokeh server with this application somewhere and then you can embed it with bokehs sever_document function see

Do steps under usage above, but for a public exposed URL, or what ever is used for deployment. The Language verison of the dashboard can be set with the environment variable: 'L

Add the code from 'script' to you website:

from bokeh.embed import server_document
script = server_document("url_to_running_server")
script

See LICENSE.

Main used libraries and dependencies

The following libraries are used directly (i.e. not only transitively) in this project:

Acknowledgements

HMC Logo    FZJ Logo

This project was developed at the Institute for Materials Data Science and Informatics (IAS-9) of the Jülich Research Center and funded by the Helmholtz Metadata Collaboration (HMC), an incubator-platform of the Helmholtz Association within the framework of the Information and Data Science strategic initiative.

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