Analysing Austrias deaths and their Covid-19 correlation

The data is used from data.gv.at which is Austrias official open data source. More about it here.

Central Notebook is covid_analysis_charts.ipynb

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Published notebook on

https://createdd.github.io/covid_analysis/covid_analysis_charts.html

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Datasets

The used datasets are from:

general deaths: https://www.data.gv.at/katalog/dataset/stat_gestorbene-in-osterreich-ohne-auslandssterbefalle-ab-2000-nach-kalenderwoche/resource/b0c11b84-69d4-4d3a-9617-5307cc4edb73

covid deaths: https://www.data.gv.at/katalog/dataset/covid-19-zeitverlauf-der-gemeldeten-covid-19-zahlen-der-bundeslander-morgenmeldung/resource/24f56d99-e5cc-42e4-91fa-3e6a06b73064?view_id=89e19615-c7b3-445c-9924-e9dd6b8ace75

Goal of the analysis

This project has multiple goals.

Work with Austria's open source data and see its ease of use Plot interactively the development of deaths and covid deaths over time Fit a (polynomial) regression through the data and calculate the slopes and given points to see the change of deaths rates.

Analysis of covid deaths

Get Started

Install dependencies like

conda install --file requirements.txt

Run notebook like

jupyter notebook

Streamlit App

To start the streamlit app, run the following in your terminal

streamlit run main.py

In case your environment cannot be found register your env as kernel like

See here

ipython kernel install --user --name=<any_name_for_kernel>

This will open a server, demonstrating

Further ideas to add for the streamlit app, here

Addtional

Medium Article: https://towardsdatascience.com/check-data-claims-yourself-with-python-an-example-8b8a92c0ae56 Explanation video: https://www.youtube.com/watch?v=fjJxxN2PtYk Timelapse video: https://www.youtube.com/watch?v=bZrwzROVczM