Web Scraping Football Matches From The EPL in Python
- Guided Project
- 2 hours
- Intermediate
- Python
Practice web scraping, data cleaning, and merging datasets using Python to prepare EPL match data for machine learning.
Overview
In this project, you'll assume the role of a data scientist working to predict the winners of English Premier League (EPL) football matches. Using Python libraries like requests, Beautiful Soup, and pandas, you'll scrape data on EPL match results and team stats from the web.
You'll gain hands-on experience in web scraping, data cleaning, and merging datasets to create a unified data source primed for machine learning. This project allows you to apply and showcase in-demand data wrangling skills highly relevant to real-world data science projects.
Objective: Scrape, clean, and merge web data on EPL football matches to prepare a dataset for predicting match winners using machine learning.
What You'll Learn
- ✓ Scrape data from the web using the requests library
- ✓ Import data into pandas
- ✓ Parse HTML links using the Beautiful Soup library
- ✓ Merge data from multiple sources
Before You Start
- ✓ Working with Python data types, variables, and functions
- ✓ Implementing control flow statements like loops and conditionals
- ✓ Loading and manipulating audio files using Python libraries
- ✓ Installing and importing Python packages like vosk, pydub, and transformers
Project Steps
8 steps
- 1 Project Overview
- 2 Downloading and Exploring the EPL Stats Page
- 3 Parsing HTML Links
- 4 Extracting Match Stats
- 5 Getting Match Shooting Stats
- 6 Cleaning and Merging Scraped Data
- 7 Scraping Data for Multiple Seasons and Teams
- 8 Conclusion
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