electricsheepafrica/africa-mauritius-quarterly-hotel-room-occupancy-rate-2019-to-2023-for-all-h-04a9bd9a
Quarterly Hotel Room Occupancy Rate 2019 to 2023 for All H | Africa (MDPA) 20 rows - 1 Africa country/area - 2019-2023 - 1 indicator - Engineered by Electric Sheep Africa TL;DR This dataset contains 20 rows from MDPA, covering Quarterly Hotel Room Occupancy Rate 2019 to 2023 for All H. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-quarterly-hotel-room-occupancy-rate-2019-to-2023-for-all-h-04a9bd9a.
Quarterly Hotel Room Occupancy Rate 2019 to 2023 for All H | Africa (MDPA)
20 rows - 1 Africa country/area - 2019-2023 - 1 indicator - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
TL;DR
This dataset contains 20 rows from MDPA, covering Quarterly Hotel Room Occupancy Rate 2019 to 2023 for All H. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
What This Dataset Measures
Transport datasets help analysts examine mobility, infrastructure, passenger movement, logistics, and access to services.
Source-provided context: Dataset shows Quarterly Hotel Room Occupancy Rate, 2019 to 2023 for All Hotels
How To Read This Dataset
- One row means: one indicator observation for one geography, time period, and optional source dimensions.
- Primary geography column:
country_iso3. - Best time column:
year. - Time coverage basis: year.
- Recommended join keys:
country_iso3,year,indicator_id.
Coverage
Geographic Coverage
Top areas shown below, sorted by row count when available:
Indicators, Variables, Or Resource Contents
quarterly-hotel-room-occupancy-rate-2019-to-2023-for-all-hotels-04a9bd9a- Quarterly Hotel Room Occupancy Rate, 2019 to 2023 for All Hotels(sourceunitsunspecified)
Schema
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-mauritius-quarterly-hotel-room-occupancy-rate-2019-to-2023-for-all-h-04a9bd9a")
df = ds["train"].to_pandas()
print(df.head())Inspect Columns
print(df.info())
print(df.head())Filter By Geography
if "country_iso3" in df.columns:
sample = df[df["country_iso3"] == "MU"]Time-Series Pattern
if "value" in df.columns and "year" in df.columns:
trend = df.sort_values("year")Pivot For Analysis
if {"indicator_id", "year", "value"}.issubset(df.columns):
matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
print(matrix.tail())Data Quality Notes
- Canonical time field:
year. - Missing values are preserved rather than silently imputed.
- Column names are standardized for machine use; source meanings are preserved where known.
- Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.
Source And Provenance
- Source: MDPA
- Publisher: MDPA
- Portal: https://data.govmu.org
- Resource: Source File
- License: CC BY 4.0
- Retrieved/generated:
2026-08-08T16:25:08Z - Hugging Face repo: electricsheepafrica/africa-mauritius-quarterly-hotel-room-occupancy-rate-2019-to-2023-for-all-h-04a9bd9a
Transformations Applied
- Converted the source table to Parquet for efficient analytics and ML workflows.
- Added or preserved source provenance columns where available.
- Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
- Preserved source-reported values without analytical imputation.
Suggested Analyses
- Track mobility over time
- Compare routes or geographies
- Join with economic and population data
- Build time-series views and period-over-period comparisons
- Pivot to geography x period or indicator x period matrices
- Check missingness before modeling
- Use
country_iso3as the safest geography join key when present
Citation
@misc{electric_sheep_africa_africa_mauritius_quarterly_hotel_room_occupancy_rate_2019_to_2023_for_all_h_04a9_2023,
title = {Quarterly Hotel Room Occupancy Rate 2019 to 2023 for All H | Africa (MDPA)},
author = {MDPA},
year = {2023},
url = {https://data.govmu.org/dataset/quarterly-hotel-room-occupancy-rate-2019-to-2023-for-all-hotels},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-quarterly-hotel-room-occupancy-rate-2019-to-2023-for-all-h-04a9bd9a}}
}License
Released under CC BY 4.0.
Original data is published by MDPA. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.
About Electric Sheep Africa
Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/quarterly-hotel-room-occupancy-rate-2019-to-2023-for-all-hotels
