Objective: To identify the key factors that influence a movie's success.
Overview: This project analyzed a dataset of movies released from 1970 to 2022, containing details such as titles, ratings, genres, release dates, budgets, gross earnings, and more. The process involved loading, cleaning, and preprocessing the data, conducting exploratory data analysis (EDA), and examining the correlation between budget and gross earnings using Pearson’s correlation.
Skills: Data cleaning, data analysis, correlation analysis, data visualization.
Tools: Python, Pandas, Numpy, Seaborn, Matplotlib, SciPy.
Findings: The analysis revealed that votes and budget are the strongest predictors of gross earnings, while the production company shows no significant correlation.