iris-DataViz is an Exploratory Data Analysis and Visualization Streamlit Application that leverages the functionality of IRIS embedded python and SQLAlchemy to interact with IRIS, as well as the PyGWalker python library for data analysis and data Visualization. PyGWalker (Python Graphic Walker) is an interactive data visualization library built for Python, aiming to bring the ease and functionality of Tableau-style drag-and-drop visualization into Python environments.
- Drag-and-Drop Visualization
- Manipulate and clean your data within the visualization
- Wide Range of Chart Types:
- Interactive Data Exploration
- Interactive Aggregation and Grouping:
- Exportable Visualizations
- Automatic Data Summarization
- Calculated / Computed Fields
- Support for Categorical, Numerical, and Temporal Data
- Interactive Legends and Filters
- Interactive Report Generation
- Geospatial Data Support
- Clone/git pull the repo into any local directory
git clone https://github.com/mwaseem75/iris-DataViz.git
- Open a Docker terminal in this directory and run:
docker-compose build
- Run the IRIS container:
docker-compose up -d
Application already imported car-related data. In order to view the data navigate to the Management Portal SQL (http://localhost:52773/csp/sys/exp/%25CSP.UI.Portal.SQL.Home.zen?$NAMESPACE=USER) to view Data [SuperUser | SYS]
To run the application Navigate to http://localhost:8051
On macOS, you need to start the application manually. Run the following command inside the container:
streamlit run /irisdev/app/src/python/dataviz/app.py --server.port=8051 --server.address=0.0.0.0
Select Namespace,Schema and table. Click on Data tab to view the data
Drag desired columns in X-Axis and Y-Axis, and select the desired graph type.
