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data exploration using graph representations and dashboards, as well as meta data extraction, cleaning, and transformation

Project description

GraphXplore: Visual exploration and easy preprocessing of data

unittest workflow Documentation Status

drawing

About

GraphXplore is a tool for visually exploring, cleaning and transforming your data, as well as defining and sharing metadata and mappings with others. You can access GraphXplore as a Python package, or use its graphical user interface application. The app can either be run as a local webserver or a standalone desktop app. GraphXplore does not require advanced knowledge about statistics or data science and the app can be used without prior coding/scripting skills. The tool was designed with the application to the medical research domain in mind, but can be generally used with any data source.

Installation

  • Python package: Install from PyPi with pip install graphxplore, or checkout versions at the PyPI GraphXplore project site
    • Alternatively, you can clone this repository, checkout a specific commit and use that version via sys.path, pip install -e or conda develop
  • Desktop app: Download the installer
    • Alternatively, you can clone this repository, checkout a specific commit, use NPM and run the installation script
  • Local webserver: Clone this repository, install streamlit with pip install streamlit==1.39.0, navigate to frontend/GraphXplore and run streamlit run streamlit_app.py

Documentation

In the GraphXplore user guide you can find detailed information about the data-related tasks that you can work in with GraphXplore, as well as its functionalities. Additionally, the same information is given in the app via various how-to pages and tooltips.

For information on coding with GraphXplore, read the Python package code documentation.

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