This GitHub repository hosts a data analysis project that investigates the popularity of film genres created Studio Ghibli, known for its beautiful storytelling and iconic animation quality. This project analyzes various aspects of the studio’s films, such as financial performance, genre effectiveness, and audience preferences, to identify the genres that resonate most with audiences and yield the highest financial returns.
The project analyzes the success of different genres across Studio Ghibli films. By examining metrics such as budgets, revenues, film durations, and directorial influence, this analysis aims to uncover patterns and trends that can inform future film projects and marketing strategies. The goal is to sustain and enhance the studio's impact on its global audience.
This analysis addresses key questions that could guide Studio Ghibli's future production decisions:
- Which genre combinations are most frequently produced, and what does this reveal about viewer preferences?
- Which genres are most financially successful?
- How do film durations correlate with different genres and their audience engagement?
The analysis involves:
- Data cleaning and preparation using Python.
- Statistical analysis to understand genre popularity and financial metrics.
- Visualization of findings through interactive dashboards created in Tableau.
- Python
- Pandas for data manipulation
- Matplotlib and Seaborn for data visualization
- Jupyter Notebook
- Tableau
- Adventure-Animation genres have shown significant financial success.
- Animation-Drama remains a staple, proving its sustained appeal to audiences.
- Films done by Hayao Miyazaki significantly enhance film performance.
Based on the analysis, the following strategies are recommended for Studio Ghibli:
- Prioritize production in high-return genres such as Adventure-Animation.
- Continue to explore deep narrative themes in Animation-Drama.
- Utilize experienced directors to maximize the potential of successful genres.
- Tailor film lengths to meet genre-specific audience expectations to improve engagement.
- Data: Studio Ghibli Dataset on Kaggle
- Visualization Tools: Tableau Public
- Design Tools: Canva
- Images: PNGEgg
This project is available under the Apache License, Version 2.0.
For further inquiries or collaboration, feel free to contact:
- Email: [email protected]
- LinkedIn: Brittany Phelps
- GitHub: phelpsbp