This project received an Excellent grade for its technical execution and data-driven insights.

Project Structure

• PowerPoint.pdf: Presentation slides

• Report.pdf: Final project report

• Video Games Sales (1980-2024) - Raw.csv: Original dataset

• Video_Game_Sales_Analysis.ipynb: Main analysis with data cleansing and data visualization

Project Title:

Video Game Sales (1980 - 2024) Analysis

Objective:

To analyze video game sales from 1980 to 2024, identify key factors influencing sales performance (including platform, genre and region), and provide data-driven sales strategy recommendations for game publishers and developers.

Key Findings:

• GTA and COD Franchise account for more than 90% of global total sales. Publishers should continue these IPs rather than developing new IPs to guarantee high profits.

• A high score is a prerequisite for million sales of a game, rather than a guarantee of it.

• Genre is a more important factor than score in high sales. Developers should give preference to those popular genres like Action, Shooter and Sports.

• Games should be released in "cross-platform" rather than "platform-exclusivity" to capture the majority of console markets.

• Previous handheld developers for PSP and NDS should now target mobile game market.

• Japanese gamers have unique preference for RPG and Visual Novel games. These games are low thresholds for indie developers due to their low cost. Major publishers should incorporate RPG elements or special character designs into their games if they want to successfully penetrate the Japanese market.

• Small studios or indie developers should consider bringing their titles to Game Pass to enhance game exposure and sales.

Tech Stack:

Python(Scikit-learn, Pandas, Matplotlib, Seaborn)

Data Visualization:

For more comprehensive analysis and detailed visualizations, please refer to the report or the Jupyter Notebook.