This project explores correlations between different attributes of movies such as budget, gross earnings, company, genre, and more. The analysis is performed using Python libraries to visualize and identify patterns in the dataset.
The main objective of this project is to understand how various movie features are related to each other and to identify which factors contribute most to a movie’s success.
Key steps include:
- Importing and cleaning the dataset
- Handling missing values
- Data exploration and visualization
- Correlation analysis using heatmaps and scatter plots
- Python 3
- Pandas – data manipulation
- NumPy – numerical operations
- Matplotlib – data visualization
- Seaborn – advanced visualization & heatmaps
- The relationship between budget and gross earnings shows a strong positive correlation.
- Certain companies and genres have a significant impact on revenue generation.
- Visualizations like heatmaps and pairplots make it easier to understand feature relationships.