🎬Movie Data Analysis

📌 Overview

This project explores a large movie dataset by performing extensive data wrangling, exploratory data analysis (EDA), and visualization. The goal is to uncover patterns and trends related to movie sales, seasonal performance, and other key factors influencing the industry.

📊 Key Findings

• ✔ Seasonal Trends: Movies tend to perform better during summer and winter breaks, which coincide with school holidays and festive periods.
• ✔ Extensive Data Wrangling: A significant amount of cleaning and transformation was required to ensure data accuracy.
• ✔ In-Depth Exploration: Various factors, such as revenue, ratings, and audience preferences, were thoroughly analyzed.
• ✔ Clear Communication of Insights: Visualizations and explanations made the findings accessible to both technical and non-technical audiences.

🛠️ Technologies Used

• Programming Language: Python
• Data Processing: Pandas, NumPy
• Visualization: Matplotlib
• Jupyter Notebook for interactive analysis