Cinemalytics is a data science project focused on analyzing movie genres across Netflix, Prime Video, and Disney+ to guide filmmakers on where to release their work for maximum exposure and potential revenue. From data preparation to insightful analysis, our project leverages comprehensive datasets to deliver actionable insights.
Ensure you have Python 3.x and pip installed on your system to get started with Cinemalytics.
Set up your environment with the following steps:
- Clone the repository:
git clone https://github.com/ulquyorra-11/cinemalytics.git - Navigate to the project directory:
cd Cinemalytics - Install the required libraries:
pip install -r requirements.txt
Make sure to have the following libraries installed:
- pandas
- numpy
- matplotlib
- seaborn
- scikit-learn
- Pillow
- joblib
These libraries are crucial for data manipulation, analysis, visualization, interface development, and the overall functioning of our project.
Run the project with:
- Activate your environment, if necessary.
- Execute the main script:
python main.py
The project utilizes various libraries for analysis, visualization, and interface development, including but not limited to Pandas, NumPy, Matplotlib/Seaborn, Tkinter, and Pillow (PIL).
Our analysis incorporates datasets from major streaming platforms, offering a rich basis for our insights:
- Netflix Movies and TV Shows: View Dataset
- Amazon Prime Movies and TV Shows: View Dataset
- Disney+ Movies and TV Shows: View Dataset
- (Outdated) IMDB Movies Dataset: View Dataset
Experience our tool's capabilities firsthand with a glimpse into the user interface and prediction results. Below is a snapshot of Cinemalytics in action, demonstrating how our analytical insights are presented through the GUI. This intuitive interface showcases genre popularity predictions across different platforms, offering filmmakers data-driven guidance on where to distribute their content.
- Anh Quy Daniel Nguyen
- Muhammad Uzair Rana
- Samer Eladad
We encourage collaboration and are open to new ideas that can enhance Cinemalytics. For more detailed information on our process and findings, refer to our Project Documentation.
Interested in contributing or discussing the project further? We'd love to hear from you! Here's how you can reach us:
- GitHub Issues: For technical suggestions or inquiries, feel free to open an issue in our repository.
- LinkedIn:
Your contributions and insights are invaluable to us. Let's explore how we can push the boundaries of content analytics together.
Special thanks to TechLabs and our mentor for their support and guidance throughout this project.
For any queries or more information, feel free to contact us through the project's GitHub page or our LinkedIn profiles linked above.