Animal Crossing: New Horizons - Analysis

Introduction

This project dives into the rich world of Animal Crossing: New Horizons, a popular life simulation video game developed by Nintendo. Utilizing data from the TidyTuesday repository, VillagerDB, and Metacritic, this analysis seeks to uncover insights into user and critic reviews, as well as the diverse characteristics of villagers and in-game items.

"Animal Crossing: New Horizons" offers players a unique, soothing experience of developing a deserted island into a vibrant community. This analysis aims to understand the game's public reception, the diversity among its characters, and the intricacies of its items and economy.

Objectives

The main goal of this project is to:

1. Analyze user and critic reviews for sentiment and themes, understanding public reception.
2. Explore the diversity of villagers in terms of gender, species, and personality.
3. Investigate the game's items, focusing on categories, pricing, and crafting complexities.
4. Examine cultural elements through villagers' birthdays and star signs.

Data Sources

• VillagerDB: Information on villagers and items in the game.
• Metacritic: User and critic reviews, including scores and textual feedback.

Analysis Outline

1. Reviews Analysis: Employing NLP for sentiment analysis, text mining for themes, and statistical methods to explore review scores and their temporal effects.
2. Villager/Items Analysis: Demographic studies of villagers, thematic analysis of sayings, economic analysis of item pricing and crafting recipes, and cultural insights through star sign distribution.

Technologies Used

• Python, Jupyter Notebook
• Pandas for data manipulation
• Matplotlib for visualization
• NLTK for natural language processing

Viewing the Analysis

This project is contained within a Jupyter Notebook which is viewable directly on GitHub for convenience. Simply navigate to the 'animal_crossing_analysis.ipynb' file in the repository to view the analysis and results.

For those interested in running the notebook locally or exploring the analysis further, ensure you have Jupyter installed and run the notebook within your environment. For more details on working with Jupyter Notebooks, visit the Jupyter documentation.

Contributing

While this project is primarily a personal portfolio piece and not actively seeking contributions, I'm open to ideas and suggestions! If you have feedback or suggestions that could improve the project, feel free to open an issue or contact me directly at ckudrave@gmail.com.

Acknowledgements

• This project makes use of data from the TidyTuesday initiative, a weekly social data project organized by the R4DS Online Learning Community. The data and inspiration for this project were drawn from the following source:

  R4DS Online Learning Community (2023). Tidy Tuesday: A weekly social data project.

  https://github.com/rfordatascience/tidytuesday.

• VillagerDB and Metacritic for providing the data.

• Nintendo for creating "Animal Crossing: New Horizons".

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact Information

For any queries or discussions, feel free to contact me at ckudrave@gmail.com.