Hotel Sales (Time Series)

Introduced by Farhangi et al. in A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19

The dataset contains the hotel demand and revenue of 8 major tourist destinations in the US (e.g., Los Angeles, Orlando ...). The dataset contains sales, daily occupancy, demand, and revenue of the upper-middle class hotels.

We also gathered dynamic exogenous variables such as the state’s closure/open policy to enrich our dataset. Specifically, we gathered numerious static features such as the number of hospitals, GPD, and population.


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