Using this Library to build a Cool mini project!

Portfolio projects are central to your resume whenever you apply for a Data job!

These prove that you implemented whatever you learned and built something cool.

The best way to maximize the potential of your projects is to implement them into a simple web app like this:

footballapp.streamlit.app

This is a Streamlit app for exploring English Premier League (EPL) football team statistics and creating visualizations in a Dashboard UI.

I’m going to show you how to build this app using Streamlit and PygWalker!

1/ Importing libraries

These are Python libraries used for creating the web app (Streamlit for the app interface), handling data (Pandas, NumPy), and creating visualizations (PygWalker).

2/ Title and description

Here we set the title of the app and provide a brief description of what the app does, including the Python libraries used and the data source.

3/ User Input slider

Using the sidebar function from Streamlit we are writing the code for a sidebar for some user inputs.

The sidebar allows users to select the year for which they want to explore EPL stats.

4/ Data Source and Web Scraping

The load_data function (pandas) retrieves EPL team stats for the selected year by scraping data from the provided URL. ‘

The data is stored in a Pandas DataFrame.

5/ Team Selection User Input

Users can select one or more teams from the sidebar.

The data is filtered based on the selected teams, and the resulting DataFrame is displayed.

6/ Visualise using Dashboard UI

A button is provided to generate a visualization using the PygWalker library.

When clicked, it calls the analysisdash function, which converts the DataFrame to HTML using PygWalker and displays it in the app.

For the Data Visualisation UI, the package used is PygWalker.

Check it out here: https://kanaries.net/home/pygwalker 

The complete Github code is here: