Movie Success Rate

Description

In this analysis, Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn are used to clean, process, and visualize the dataset. The success of a movie is typically defined using criteria such as profitability (revenue greater than budget), return on investment (ROI), audience ratings, or popularity scores. The workflow begins with data preprocessing, where missing values are handled, duplicates are removed, and categorical variables are encoded. After cleaning, exploratory data analysis (EDA) is performed to understand relationships between features like budget, genre, runtime, and ratings with the movie’s success.

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