Global and U.S. Box Office Performance Data

This dataset, titled Global and U.S. Box Office Performance Data, was created as part of an academic project focused on the automated extraction of financial performance data from the film industry. The data was collected from Box Office Mojo by IMDbPro, a widely recognized source for box office statistics. The project uses a custom web scraping pipeline developed in Python, combining Selenium and BeautifulSoup to systematically explore various sections of the website (e.g., brands, franchises, weekly/monthly reports) and extract structured information from HTML tables. The dataset contains 14,086 records with 35 fields, covering key financial and commercial metadata of movies such as lifetime gross, opening weekend revenue, release date, number of theaters, distributor, and more. Each entry includes a source URL and a category field that indicates the specific section of the website where the data was obtained. The dataset spans from 1972 to early 2025, with a particular focus on daily, monthly, and quarterly data from 2024–2025 and aggregated statistics by brand, genre, holiday, and franchise. This dataset can support various use cases, including market analysis, trend detection in the film industry, or the development of predictive models for commercial movie success. Due to the heterogeneity of the original website, the data has not been extensively cleaned or normalized—allowing future users to define their own preprocessing steps depending on the analytical goal. Important Note: The dataset was created for educational purposes only and follows ethical guidelines including minimal server load, respect for website structure, and explicit non-commercial intent. The scraping process was limited in scope and rate, and all data references the original source (IMDb) with proper attribution. The dataset is distributed under the Creative Commons BY-NC-ND 4.0 license with additional restrictions detailed in the LICENSE file of the project’s GitHub repository.