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Tracking normalized county level COVID cases with graphs and maps

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ptdoerr/COVIDdashboard

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COVIDdashboard

This is primarily a Jupyter Notebook with some support for running a subset of functions as Flask services. The motivation for this project was that local COVID data was only reported as raw data which is pretty useless. I also wanted to learn Python so the this code documents my journey in that endeavour. I found a standard county level dataset that was upated daily

Sections

Load and Normalize

Loads COVID and county population data and combine into single DataFrame. Perform 7 day moving average and normalize per 100k using conty population data.

Current Graphs

Display current case counts for selected counties. Any set of CONUS counties can be displayed.

Display graph of case counts for selected counties. Any set of CONUS counties can be displayed. Date range is also selectable.

Current Map

GIF Builder

Builds animated GIF of maps over selected date range.

Image Browser

Pick map image to display by date.

Environment

  • Jupyter Lab Interactive notebook
  • Flask

Installation

Required Software

  • Python 3.7
  • conda 22.9

Environment Variables

  • AWS AWS_ACCESS_KEY_ID

AWS_SECRET_ACCESS_KEY

  • MongoDb

Running

Notebook

conda env create -f config/test_geo.yml

conda activate test_geo

jupyter lab

Flask Server

conda env create -f config/flask_env.yml

conda activate flask_env

flask run