This repository contains the Jupyter Notebook file for analyzing box office data using Python. The analysis aims to uncover trends and patterns in movie performance based on box office statistics.
- Box Office Data: The dataset includes information about movie titles, release years, budgets, box office gross earnings, genres, ratings, and runtime.
The Jupyter Notebook file (Box-Office-Analysis.ipynb) provides detailed analysis and visualization of the box office dataset. Some of the key aspects covered in the analysis include:
- Data cleaning and preprocessing of box office data.
- Exploratory Data Analysis (EDA) to identify patterns and insights.
- Statistical analysis to predict box office success factors.
To replicate or explore the analysis:
- Clone this repository to your local machine.
- Ensure you have Jupyter Notebook installed.
- Open
Box-Office-Analysis.ipynbusing Jupyter Notebook. - Follow the step-by-step instructions in the notebook to run the analysis.
- Python 3.9
- Jupyter Notebook
- Pandas
- Matplotlib
- Seaborn
- Scikit-learn
The box office dataset used in this analysis is sourced from Kaggle. You can download the dataset from here.
Contributions to improve the analysis or add new features are welcome! Feel free to fork this repository and submit pull requests.