Cinema-Tickets
OpenML dataset with id 43388
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22102213/Cinema-Tickets.arff
Upload date: 23 March 2022
Copyright license: No records found.
Dataset Characteristics
Number of features: 14 (numeric: 13, symbolic: 0 and in total binary: 0 )
Number of instances: 142,524
Number of instances with missing values: 125
Number of missing values: 250
Context Cinema industry is not excluded of getting advantage of predictive modeling. Like other industry it can help cinemas for cost reduction and better ROI. By forecasting sale, screening in different location could be optimized as well as effective market targeting and pricing. Also historical data of sale and movies details e.g. cost, cast and crews, and other project details like schedule, could help producers to select high performance cast and crews and planning for better projects ROI . Also it helps to assign screening location on hot spots and areas.
Content About eight months sales history of different cinemas with detailed data of screening , during 2018 with encoded annonymized locations . Starter Kernels EDA , Temporal Feat Eng and XGBoost
Inspiration
Time series analysis
Cinema Clustering
Forecast sales for each cinema
Recommendation:
Movie genre recommendation for cinemas
Cinema location recommendation
Cast and crew ratings
This page was built for dataset: Cinema-Tickets
