Welcome to the Disney Movies & Box Office Success Project! This project is part of a Python workshop designed to explore Disney movie data, analyze trends, and build predictive models using Python libraries like pandas, numpy, matplotlib, and seaborn.
- Objective: Analyze Disney movie data to identify factors contributing to box office success.
- Tasks:
- Explore top-grossing Disney movies.
- Analyze trends in genre popularity over time.
- Build a linear regression model to predict box office success.
Disney_Movies_Assignment.pdf: Detailed assignment instructions.Disney_Movies_Box_Office_Success_Notebook.ipynb: Jupyter Notebook with step-by-step analysis and modeling.disney_movies_total_gross.csv: Dataset containing Disney movie details and box office earnings.
- Clone the repository to your local machine.
- Open the Jupyter Notebook to follow along with the analysis.
- Explore, modify, and run the code to gain insights and complete the tasks.
This project is for learning and exploration. You are encouraged to complete it independently to fully benefit from the exercise. Have fun discovering what makes Disney movies so magical!
For any questions, please reach out via the MMA office: mma@mcgill.ca.