Using goals scored data from the Fifa World Cup 2018 in Russia. I have created a data dash-board using D3.js, DC.js and Crossfilter. The site has been created with Python using the Flask web framework, and has been deployed using Heroku.

As the charts update upon filtering, you can explore patterns in how the goals were scored based on a variety of factors. Such as the minute scored, the current round, the country or continent etc

Visit site..

The page boots with a tutorial upon visiting. Follow the simple instructions to use.

My initial setup and help with deployement owes to sahildiwan's blog. I gained inspiration from his app file setup and changed the routes to fit my need.

First you will need to get pip and Postgresql

CD to your desired folder and run the following from the terminal:

git clone https://github.com/danieldeiana/wcdatadash.git

Activate the virtual environment:

. myenv/bin/activate

To run the app locally go to the app.py file in the root folder and change the LOCAL variable to True. Then run the app from the terminal:

python app.py

and visit local host in your favourite browser.

To run the tests go to the root folder in the terminal and run:

python tests.py

If you would like to use the goals data locally you can link to it as so..

At the top of the app.py file, import urllib

Change the get_goals_json() function from this:

@app.route('/goalsdata')
def get_goals_json():
    """
    When accessing this route, the serialized Goal object is provided
    """
    return goals_to_json(Goal)

to this:

@app.route('/goalsdata')
def get_goals_json():
    """
    When accessing this route, the serialized Goal object is provided
    """
    link = 'https://wcgoals-datadash.herokuapp.com/goalsdata'
    open_link = urllib.urlopen(link)
    goals_data = open_link.read()
    return goals_data