Final Project

Genres & Stardom Analytics Project

*** Link to Presentation *** https://baruch.zoom.us/rec/share/-mwXd2R6YsKSuS3ErTdQKiE5ZmdVNUzMYI9MxRgXDVKV0KS8uaZAWZdcS7Aj3YyF.QtxYkRkic0KAStEv  Passcode: d^0Lh+39

Project Description

In the post-COVID era, the film industry has evolved with streaming platforms, shifting audience preferences, and box office dynamics. This project, by Bukola and Jeremiah, analyzes patterns in movie performance using data from TMDb and NYT. We explore:

• Genres: Trends in popularity and critical reception.
• A-list actors: Impact on movie success.

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Features

Genre Analysis

• Tracks TMDb ratings and NYT mentions for Action, Drama, and Comedy genres.
• Evaluates trends over time (2020-2024).

Actor Analysis

• Analyzes movies by A-list actors (e.g., Will Smith, Adam Sandler).
• Measures average TMDb ratings and NYT reviews.

Visualization

• Line plots for genre trends.
• Bar charts comparing actor performance.

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Usage

• Calculates TMDb ratings and NYT mentions for genres.
• Analyzes A-list actors' movie performances.
• Visualizations include:
  • Line plots: Genre ratings over time.
  • Bar charts: Actor performance metrics.

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APIs Used

1. TMDb API:

   • Fetches genre and movie details.
   • TMDb API Docs.

2. NYT API:

   • Retrieves article mentions and reviews.
   • NYT API Docs.

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License

Licensed under the MIT License. See LICENSE for details.