This repository preserves and extends a school data-science project examining whether seasonal SARS-CoV-2 wastewater activity can help predict periods of increased viral prevalence.
Can we use seasonal Wastewater Viral Activity Level (WVAL) trends of SARS-CoV-2 to predict which times of the year the virus will be most prevalent?
Final_Project_Sars_Cov2_ver.ipynb: Data cleaning, exploratory analysis, visualization, regression, and classification.Copy of ds 1002 project.pptx: Presentation summarizing the project.
The notebook expects a file named Virus_Data.csv.
Derived from https://data.cdc.gov/api/views/atcp-73re/
Seasonal WVAL can not be used to predict when SARS-CoV-2 is most prevalent. According to our extremely low R2 value of 0.0001189, SARS-CoV-2 levels are influenced by many factors other than season, and the relationship is not strongly correlated.
- Python
- Jupyter Notebook
- pandas
- NumPy
- Matplotlib
- Seaborn
- scikit-learn
- Git and GitHub
notebooks/sars_cov2_wastewater_analysis.ipynb: Data cleaning, exploratory analysis, visualization, regression, and classification.presentation/project_presentation.pptx: Presentation summarizing the project.data/README.md: Information about the dataset required by the notebook.data/Virus_Data.csv: Data
- Python 3
- Git
- Visual Studio Code
- VS Code Python and Jupyter extensions
From the repository root, run:
python -m venv .venvActivate the environment in Windows PowerShell:
.\.venv\Scripts\Activate.ps1python -m pip install --upgrade pip
python -m pip install -r requirements.txtOpen notebooks/sars_cov2_wastewater_analysis.ipynb in Visual Studio Code.
Use the notebook kernel picker to select the Python interpreter located in:
.venv\Scripts\python.exe
The notebook expects the wastewater dataset at:
data/Virus_Data.csv
See data/README.md for information about the dataset.