/FIFA20-Analysis

Web App for Statistical Analysis of Teams and Players in FIFA-20 using Numpy, Pandas, Seaborn, Plotly and Streamlit.

Primary LanguageJupyter Notebook

FIFA-20 Statistical Analysis

Libraries I've used for this:

  • Pandas
  • Numpy
  • Seaborn
  • Plotly
  • Streamlit

The notebook contains some Player as well as Team Analysis and the results are plotted using visualization libraries like Plotly and Seaborn. Github performs a static render of the notebooks and it doesn't include the embedded HTML/JavaScript that makes up a plotly graph, so the graphs which are plotted using Plotly cannot be displayed in Github. To view the complete notebook with outputs as well, one nice option is to paste the link of GitHub notebook into http://nbviewer.jupyter.org/, which will present a rich view of the notebook.

FIFA_App.py is the code for FIFA20 Stats App which is created using Streamlit library and the Web App is deployed on Heroku cloud platform. We can see some of the results from the Jupyter Notebook in the web app plus there's an additional factor of interactivity because of Streamlit.

  1. Check out https://fifa-stats-app.herokuapp.com/ for the streamlit based data visualization webapp.
  2. Check out https://nbviewer.jupyter.org/github/tejaslinge/FIFA20-Analysis/blob/master/FIFA.ipynb to view complete Jupyter notebook.