Dataset
africa-mauritius-quarterly-hotel-room-occupancy-rate-2019-to-2023-for-all-h-b774165b
Compiled by Electric Sheep Africa from MDPA, this 20-row dataset records quarterly hotel room occupancy rates in Mauritius for all hotel categories between 2019 and 2023 and is delivered as ML-ready Parquet.
Data preview
Dataset card
This dataset provides quarterly hotel room occupancy rates for Mauritius from 2019 to 2023, sourced from MDPA and republished by Electric Sheep Africa as an ML-ready Parquet file on Hugging Face. It contains 20 rows of structured tourism statistics for a single country.
What this dataset contains
The dataset records hotel room occupancy rates in Mauritius at a quarterly cadence across a five-year window. Each row is tied to a specific country (country_iso3 = "MU") and source period, with the original data attributed to MDPA. The scope is limited to all-hotels coverage and does not segment by star rating, region, or hotel type.
Structure and fields
Records are organized in a single training split of 20 rows. Key columns include indicator_id and indicator_name describing the metric, country_iso3 and country_name for geography, year and dimension_year for the quarterly breakdown, and value as a float64 holding the occupancy percentage. Provenance fields such as source_provider, source_dataset, source_resource, source_url, license_id, and retrieved_at accompany each row, along with source_period_start_year, source_period_end_year, and source_period_label.
How analysts use it
Analysts can pivot the long-format table into a year-by-quarter matrix using indicator_id, year, and value to visualize seasonal occupancy trends or model tourism demand. The data can be filtered by country_iso3 to focus solely on Mauritius or combined with other country releases in the same schema for cross-country comparisons. Given the limited 20-row size, use cases are best suited to descriptive trend analysis, time-series forecasting exercises, or benchmarking against broader African hospitality indicators.
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