GameStop - Python

GameStop is an American video game, consumer electronics and gaming merchandise retailer. This project utilizes Python to scrape and analyze GameStop's online inventory and pricing data.

Requirements

• Python 3.6+
• Scrapy
• Pandas
• Matplotlib

Usage

To run the program, navigate to the project directory and run the following command:

scrapy crawl gamestop -o items.csv

This will start the web scraping process and output the data into a CSV file named "items.csv".

To analyze the data, run the "analysis.ipynb" Jupyter Notebook.

Data Collected

The following data is collected for each item in GameStop's online inventory:

• Title
• Platform
• Price
• Sale Price
• Savings
• Availability
• Image URL

Data Analysis

The "analysis.ipynb" notebook contains data analysis techniques utilizing Pandas and Matplotlib. The notebook covers topics such as:

• Average price of each console
• Discount analysis
• Bestselling games by platform
• Price distribution across different platforms

Conclusion

The GameStop - Python project showcases the power of web scraping and data analysis with Python. By utilizing libraries such as Scrapy, Pandas, and Matplotlib, we were able to gain useful insights into GameStop's online inventory and pricing data. This project can be further extended to include more data points and analysis techniques.