A corona stats dashboard using streamlit.

The notebook explore-data.ipynb visualizes various corona statistics. The interesting results from this exploration are then integrated into the streamlit app.

pip3 install millify

streamlit run app.py

Reading the .CSV files from URL requires the "RAW" data link eg: https://raw.githubusercontent.com/...

Streamlit info

deploy app: https://share.streamlit.io/signup (Once deployed, reachable: https://share.streamlit.io/mikehemberger/corona-dashboard/main/app.py ) python api: https://docs.streamlit.io/library/api-reference

Data and sources

• Infection numbers timeseries: https://github.com/CSSEGISandData/COVID-19/blob/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv
• Virus variants: https://www.ecdc.europa.eu/en/publications-data/data-virus-variants-covid-19-eueea
• Big diverse data: https://www.ecdc.europa.eu/en/covid-19/data
• RKI dashboard: https://experience.arcgis.com/experience/478220a4c454480e823b17327b2bf1d4/page/Bundesl%C3%A4nder/

Omicron timeline - https://cdn.knightlab.com/libs/timeline3/latest/embed/index.html?source=1XjAYFLM5Rvh9l9ySqMbb_NVkWRpKsSQBDmwytmPdLUg&font=Default&lang=en&initial_zoom=2&height=650

B.1.1.529 - Omicron