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https://github.com/vvipjain/hockey-tournament-analysis
Hockey Tournament Analysis
https://github.com/vvipjain/hockey-tournament-analysis
beautifulsoup data data-analysis data-visualization databases pandas pandas-dataframe powerbi python python-library python-script requests-library-python sql sql-server sqlalchemy
Last synced: 8 days ago
JSON representation
Hockey Tournament Analysis
- Host: GitHub
- URL: https://github.com/vvipjain/hockey-tournament-analysis
- Owner: VVipJain
- Created: 2024-08-15T08:01:16.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2024-09-12T07:28:32.000Z (21 days ago)
- Last Synced: 2024-09-26T00:20:11.133Z (8 days ago)
- Topics: beautifulsoup, data, data-analysis, data-visualization, databases, pandas, pandas-dataframe, powerbi, python, python-library, python-script, requests-library-python, sql, sql-server, sqlalchemy
- Language: Jupyter Notebook
- Homepage:
- Size: 411 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# HOCKEY TOURNAMENT ANALYSIS
This project focuses on analyzing hockey tournament data through a combination of data scraping, cleaning, and visualization. The primary objective is to gather data from a website, format and clean the data using SQL, and then visualize and analyze the data using Power BI.
# PROJECT WORKFLOW
-> Data Scraping (Python):
Tools Used: Python, BeautifulSoup, Requests
Description: The project starts with scraping data from a specific website that hosts hockey tournament information. Python scripts are used to extract relevant data such as team names, Wins, Losses, Goals For, Goals Against etc.
-> Data Formatting and Cleaning (SQL):
Tools Used: Excel
Description: After scraping, the raw data is stored in SQL database. SQL is used to clean and format the data. This includes tasks like removing duplicates, handling missing values, normalizing data, and preparing it for analysis.
-> Data Visualization and Analysis (Power BI):
Tools Used: Power BI
Description: The cleaned data is then imported into Power BI for visualization and analysis. Various charts, graphs, and dashboards are created to help understand trends, team performance, and other insights.
