This example will draw some illustrations of data visualization drawn from a Jupoyter notebook analysis and then converted to an interactive web frontend.
LOG
Date November 19, 2023
I did some reading into streamlit, and noticed that you can deploy the platform onto streamlit cloud. This might shorten my develop to deploy cycle, at least for the POC. So I have decided to move from dash to streamlit.
Keep up with the progress, here is the link to streamlit cloud and community.
in order to test the initial visuals, the processed dataframe from the jupyter notebook with geo locations will be used to be passed in this example.
Plan
| ToDo | Doing | Done |
|---|---|---|
| Setup basic visual platform | Sample Dash app | |
| Import processed Traffy fondue data | ||
| Display data in dynamic map | ||
| Add interactive options date, type, district | ||
| Build import module -scrape API | ||
| Build clean module | ||
| Update visual app with new data | ||
| Deploy to streamlit cloud |
Date: November 18, 2023
Initial code creation. This code should run with no sample data, and just display the web application and use the basic library dash
The sample code should take the sample data and create a barchart
run with docker commands:
docker build -t dash-example . docker run -p 8050:8050 dash-example
and open http://localhost:8050 in a browser