Dataset

africa-mauritius-hotel-room-occupancy-rate-2019-to-2023-for-all-hotels-by-s-ef4516bd

Estimates, Events & Fund Flows Download 1 source

Prepared by Electric Sheep Africa, this MDPA-sourced dataset supplies 10 entries of hotel room occupancy rates for Mauritius over 2019-2023, delivered as ML-ready Parquet files accompanied by uniform Hugging Face metadata and source provenance.

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Dataset card

This dataset, published by Electric Sheep Africa on Hugging Face, contains 10 rows of hotel room occupancy rates for Mauritius sourced from MDPA. It is distributed as an ML-ready Parquet file under a CC BY 4.0 license.

What this dataset contains

The dataset tracks hotel room occupancy rates in Mauritius from 2019 to 2023, broken out by semester. It is tagged for tabular regression and time-series forecasting and is delivered as a single train split of 10 rows. Provenance metadata points to MDPA as the original source publisher.

Structure and fields

Each row is keyed by fields such as indicator_id, country_iso3 ("MU"), year (int64), value (float64), and dimension_year (e.g., semester labels). Supporting columns include indicator_name, country_name, unit, source_sheet, source_period_start_year, source_period_end_year, source_period_label, source_provider, source_dataset, source_resource, source_package_id, source_resource_id, source_url, license_id, and retrieved_at. The dataset size falls in the n<1K category.

How analysts use it

Analysts can pivot the value column by year and indicator_id to construct a time series of occupancy rates, or filter on country_iso3 for a Mauritius-only view. The semester-level dimension_year field allows intra-year seasonality checks relevant to tourism-exposed equities and macro funds with Mauritius exposure. The small sample size (10 rows) limits its use to exploratory trend context rather than model training.

Documentation & references 1