Fighting Against Coronavirus

Course project for "Comprehensive and Designing Experiments", 2021 Fall.

Overview

Since the beginning of 2020, COVID-19 has spread wantonly around the world. Making the public aware of the typical symptoms after COVID-19 infection and the different characteristics of the virus infection among different populations will enable the public to prepare more fully to deal with it. Therefore, we have developed the Fight Against Choronavirus (FAC) data visualization webpage, which enables the public to have a clear and intuitive understanding of the symptoms of COVID-19 infection in an interactive way. This project is completely open source for all the data processing, visualization, and web development parts.

Data Analytics and Visualization

Data

Downloaded from Vaccine Adverse Event Reporting System (VAERS).

All data used are in VAERSDATA.

Code

The code data processing and visualization part are divided to four parts :

• a_b_foundamental_visual.ipynb for foundamental visualization, corresponding to the first two pages of the main page
• c_wordcloud.ipynb for generating wordclouds of adverse reactions under different conditions
• d-time.ipynb for adverse effects over time
• e-model.ipynb for Adverse effects of deceased patients and health advice for people.

Dependencies

This code was confirmed to run with the following environment:

• Processed with Python 3.8
• pyecharts 0.5.11
• jupyter-notebook : 6.1.4

Web Development

How to Run

Online mode

Open ❗️with Safari browser.[will be deployed soon]

local mode of operation (LMO)

Download and open the whole project with Pycharm, click the triangle symbol next to

 `if __name__ == '__main__':` 

in app.py and open with Safari browser to get optimal effect.

Dependencies

This code was confirmed to run with the following environment:

• Python 3.8.5
• Flask 1.1.2.