Overview: This project performs an end-to-end exploratory data analysis (EDA) on the IMDb dataset. It includes data cleaning, preprocessing, visualization, and insight generation using Python and popular data-science libraries. The goal is to understand: Top-rated movies Most frequent directors Genre distribution Certificate/category distribution Movie rating trends
Technologies Used: Python Pandas NumPy Seaborn Matplotlib Jupyter Notebook / VS Code
Features and Workflow:
- Data Import & Setup
- Data Cleaning
- Exploratory Data Analysis
Sample Visualizations: Barplots Countplots Histograms Genre distribution charts
Output: Cleaned dataset saved as: CLEANED_IMDb_Dataset.csv Visual insights printed and plotted within notebook Console logs track progress of each processing step
Conclusion This project provides a clear, structured analysis of movie trendsusing Python-based EDA. It showcases practical skills in data cleaning, visualizationand insight extraction suitable for academic, internship, or entry-level data roles.