keikey/covid19-plotting

Analysis of the Impact of COVID-19

Project Structure

    project-root
    │
    └── app
        ├── main.py
        ├── time_series_covid19_confirmed_global.csv
        ├── time_series_covid19_deaths_global.csv
        ├── time_series_covid19_recovered_global.csv
        └── images
    ├── .gitignore
    ├── README.md
    ├── docker-compose.yml
    ├── Dockerfile
    ├── requirements.txt
    └── run.sh

• A strongly typed python has been used for the project

Setup Instructions

1. Clone the Repository

    git clone https://github.com/KeiKey/covid19-plotting.git
    cd covid19-plotting

2.a Local Machine Setup

Prerequisites:

• Python
• Dependencies from requirements.txt

    pip install -r requirements.txt
    python3 main.py

2.b Docker Setup

Prerequisites:

• Docker
• Docker Compose

    bash run.sh

After the above commands finish, you'll be inside the Docker container. Run the script like this:

    python3 main.py

Usage

The script main.py allows you to generate and save COVID-19 plots. Here are some usage examples:

    python3 main.py
    
    python3 main.py -c
    
    python3 main.py --countries France,Italy
    
    python3 main.py --countries Albania -dr

• Use --countries to specify a comma-separated list of countries. If it's missing then by default Germany is taken.
• Use -c, -d, or -r flags to include Confirmed Cases, Deaths, or Recoveries plots, respectively.

For more options and details, run:

    python3 main.py --help

Generated plots will be saved in the images folder.

Safe skipping countries

In case the script is run about countries/country that either are mistyped or the data is not existing, then they are skipped. Example:

    python3 main.py --countries Germ,Italy

Germ will be skipped and as a result the plot will be created only for Italy.

Improvement goals

• Use xserver to run a GUI, not just store images. Able to connect from inside the container to xserver in the local machine, but for some reason the GUI is not activated. Xeyes was able to run successfully.
• Getting data is coupled together. We are getting data for confirmed cases, deaths and recoveries, regardless if we need one or all of them.
• Another example of possible issue is if we want the plot for the confirmed cases. If the country has data in the time_series_covid19_confirmed_global.csv but not on one of the other csv, then the country is skipped.