Understanding COVID-19 with Pandas and NetworkX

Jupyter notebooks includes all the code used to generate the figures in the blog posts. Run the code online using
EpiModel.py - Python module encapsulates all the code necessary to numerically implement arbitrary compartmental epidemic models
NetworkEpiModel.py - Python module encapsulates all the code necessary to numerically implement arbitrary epidemic models on networks
See Epidemic Modeling Reading List for more information

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Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
data		data
slides		slides
.gitignore		.gitignore
1. Country Data Exploration.ipynb		1. Country Data Exploration.ipynb
2. Individual Data.ipynb		2. Individual Data.ipynb
3. Simple Models.ipynb		3. Simple Models.ipynb
4. Simple Models II.ipynb		4. Simple Models II.ipynb
5. Seasonality.ipynb		5. Seasonality.ipynb
6. Practical Considerations.ipynb		6. Practical Considerations.ipynb
7. Stochastic Models.ipynb		7. Stochastic Models.ipynb
8. Network Models.ipynb		8. Network Models.ipynb
9. Vaccination.ipynb		9. Vaccination.ipynb
EpiModel.py		EpiModel.py
Infection.png		Infection.png
LICENSE		LICENSE
NetworkEpiModel.py		NetworkEpiModel.py
README.md		README.md
d4sci.mplstyle		d4sci.mplstyle
environment.yml		environment.yml

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