/uefa_top_teams_insights

Primary LanguageJupyter Notebook

Union of European Football Associations (UEFA) Project

Week 18 - Group 1

UEFA champions league

This Project aims to Utilise The UEFA Champions League Team and Player stats to outline the NAtionality diversity amongst the UEFA Champions league top 4 Teams of the 20-2021 Season. By gathering multiple dataset statistics, the objective is to analyse, dissect and extract the important data to be readily available for useful application.

Assignment structure

Heroku-Project
| 
|__ images/          
|   |__ 20-21_table.png![20-21_table](https://user-images.githubusercontent.com/80458900/126598712-e23c850f-c443-4881-9c93-f46ea2f63ed2.png)
|   |__ ChampionsLeague.PNG
|   |__ Chelswa_img1.jpg
|   |__ Manchester_City_img4.jpg
    |__ nav_bar_img.png
    |__ Paris_Saint_Germain_img3.jpg
    |__ Real_Madrid_img2.jpg
    |__ UEFA_clubs.PNG
|
|__ Resources/
|   |__ Team Data/
|      |__ chelsea_players.csv
|      |__ Footballteams.csv
|      |__ laliga_foreign_player_mminutes.csv
|      |__ manchester_play.csv
|   |__ premierleague_forign_player_minutes.csv
|   |__ psg_players.csv
|   |__ real_madrid_players.csv
|   |__ soccer_player_webscraping.ipynbv
|   |__ world_country_latitude_and_longitude_values.csv
|   
|   
|
|__ SQL/
|   |__ SQlite databse creation
|
|__ .gitignore 
|__ .ipynb
|__ Teams.ipynb
|__ README - Project Guidelines.md
|__ README - Project Proposal.md
|__ README.md
|

Usage

# Dependencies and Setup

from bs4 import BeautifulSoup
import requests
import pandas as pd
import json
from sqlalchemy import create_engine
from geojson import Feature, FeatureCollection, Point

Data Sources:

No Source Link
1 Kaggle https://www.kaggle.com/varpit94/football-teams-rankings-stats
2 Kaggle https://www.transfermarkt.co.uk/manchester-city/kader/verein/281/saison_id/2021
3 Kaggle https://www.kaggle.com/rajatrc1705/english-premier-league202021

Datasets

No Source Link
1 Team_Data.geojson https://github.com/KenyanBoy/HML-Project/blob/main/Resources/Team_Data.geojson
2 Footballteams.csv LINK
3 laliga_foreign_player_mminutes.csv LINK
4 manchester_play.csv LINK
5 premierleague_forign_player_minutes.csv LINK
6 psg_players.csv LINK
7 real_madrid_players.csv LINK
8 world_country_latitude_and_longitude_values.csv LINK
9 chelsea_players.csv LINK

Project Task Breakdown:

Javascript.PNG

  1. Research
  2. Acquire datasets
  3. Clean datasets
    1. Jupyter notebook
    2. Create GeoJSON files
  4. Create database SQL
    1. load dataframes
    2. upload them on app.js ustilising the Flask library

Proposal

A copy of the Project proposal is located in the following link: []

Contributors