Disclaimer: This dashboard and data visualization is in no way to be used for sophisticated decision making regarding the current events of the pandemic. This is a personal project with the main focus of gaining knowledge on the utilization of the Python Dash library.
This project provides a dashboard for the visualization of infection data of the ongoing COVID-19
pandemic. Building upon the "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University" (1) and vector data by
Natural Earth (2), the dashboard itself is created by using the Python framework Dash (3). It provides information about the current worldwide development of
the disease and shows both daily charts, as well as charts covering the time frame from disease outbreak up to the current day.
The following instructions assume that the your current working directory is a local copy of the repository. At the moment, there are two ways to run the dashboard on your own machine:
Create a new Anaconda environment called covid-dashboard by using the provided environment.yml (the environment name is changeable by editing the first line in the yaml file):
conda env create -f environment.yml
You can then activate the enviroment and start up the dashboard running python3 app.py
Build your own docker image using the provided Dockerfile via
docker build . --rm -t covid-dashboard
to create an image called covid-dashboard. When running the container, it is
advised to mount a volume where the downloaded and parsed data is stored. This
can be a local folder (don't forget to change the host path in the docker run [...]
command if do so) or a docker volume for example. If you want to use the latter,
you can create a volume named dashboard-volume using:
docker volume create dashboard-volume
After the build process has successfully completed, you can run the image in a container via
docker run \
-ti \
--name covid-dashboard \
--publish 8050:8050 \
--volume dashboard-volume:/home/appuser/app/data \
covid-dashboard
You can also use docker_build.sh and docker_run.sh which contain the commands
specified above.
The dashboard is web based and can be accessed via browsing to
http://0.0.0.0:8050/ with a browser of your choice (On Linux / Docker). If you are running the dashboard on a Windows machine you need to
use http://127.0.0.1:8050/ or http://localhost:8050/.