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SARS COVID-19 Tracker

The program's purpose is to serve as a comparison mechanism for Flu and COVID-19 viruses. The main point of comparing these two is to see how much or less the SARS COVID-19 virus is dangerous from regular Flu in the USA.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

git clone https://github.com/SlavkoPrytula/Covid-19-Tracker

Prerequisites

For the program to run on your device, you should install the following libraries, modules, etc... You may use pip3 for installing if you have Python3 or use pip instead

pip install requests
pip install matplotlib
pip install beautifulsoup4
pip install PrettyTable
pip install numpy
pip install DateTime
pip install sklearn

Deployment

To run the program after cloning in on your machine, go to the MAIN folder and find the file named user_interface.py

The folder and the filee

After, click RUN, and the program will start.

Now you sould have the program interface on your screen. Screen

Now you can chose what statistics you want to see by typing in the command number in tnto the input line. The program provides you with statistical data of SARS COVID-19 and Flu viruses. (Cases, Recovers, Deaths, and much more)

Example_1

Example_2

It can also provide you with plotted statistics on the bar charts.

Predicted number of cases for COVID-19 up till 2021

Recovered now comparison from COVID-19 (red) to Flu(green)

Predicted amount of deaths till 2021 for COVID-19 (red) and compared to recet data for Flu(blue)

Running the tests

Here you will find the necessary tests for the program usage. They [modules] show how to work and integrate with the code correctly.

Built With

Contributing

Please read CODE_OF_CONDUCT.md for details on our code of conduct. If you have any questions, please contact at slavko.prytula@gmail.com

Authors

License

This project is licensed under the MIT License! It is available in the repository for view and read - see the LICENSE.md file for more details.

Acknowledgments

  • Special thanks to Ukrainian Catholic University for giving the opportunity to make the project become a reality. For all the provided help and tips