--- license: cc-by-4.0 language: - en task_categories: - tabular-regression - time-series-forecasting multilinguality: monolingual size_categories: - n<1K tags: - tabular - csv - africa - mauritius - official-statistics - open-data - tourism pretty_name: "Selected tourism statistics for Hotel - Travel arrangement, %, 2015, 2018 and 2023 | Africa (Mauritius official open data)" --- # Selected tourism statistics for Hotel - Travel arrangement, %, 2015, 2018 and 2023 | Africa (Mauritius official open data) 4 rows - 1 Africa country - 1970 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica) ![rows](https://img.shields.io/badge/rows-4-blue) ![countries](https://img.shields.io/badge/countries-1-green) ![years](https://img.shields.io/badge/years-1970-orange) ![indicators](https://img.shields.io/badge/indicators-2-purple) ![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey) ## TL;DR This dataset packages one official CSV resource from **Mauritius** as ML-ready Parquet. The CSV is the provenance boundary; all usable indicators or tabular columns from the source file stay together in this repo. ## About the source - **Source:** [Selected tourism statistics for Hotel - Travel arrangement, %, 2015, 2018 and 2023](https://data.govmu.org/dataset/selected-tourism-statistics-for-hotel-travel-arrangement-2015-2018-and-2023) - **Publisher:** MDPA - **Resource:** [CSV File](https://data.govmu.org/dataset/37f12ef7-49d1-49d7-97e0-aef7863d0fed/resource/b3f420cb-f327-4f68-8c7c-eb4d45c9d54a/download/book1.csv) - **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) - **Packaging mode:** `indicator_long` ## Geographic coverage 1 Africa country: | Country | Rows | First year | Last year | Name | |---------|-----:|-----------:|----------:|------| | `MUS` | 4 | 1970 | 1970 | `Mauritius` | ## Indicators or Resource Contents - `selected-tourism-statistics-for-hotel-travel-arrangement-2015-2018-and-2-562081d2` - Selected tourism statistics for Hotel - Travel arrangement, %, 2015, 2018 and 2023 - d 2015 - `selected-tourism-statistics-for-hotel-travel-arrangement-2015-2018-and-2-d57dc24d` - Selected tourism statistics for Hotel - Travel arrangement, %, 2015, 2018 and 2023 - d 2018 ## Schema | Column | Type | Description | Example | |--------|------|-------------|---------| | `indicator_id` | `object` | Stable indicator identifier. | `selected-tourism-statistics-for-hotel-travel-arrangement-2015-2018-and-2` | | `indicator_name` | `object` | Human-readable indicator name. | `Selected tourism statistics for Hotel - Travel arrangement, %, 2015, 201` | | `country_iso3` | `object` | ISO3 country code. | `MUS` | | `country_name` | `object` | Country name. | `Mauritius` | | `date` | `string` | Observation date. | `1970-01-01` | | `year` | `Int64` | Observation year. | `1970` | | `value` | `float64` | Numeric observation value. | `79.0` | | `unit` | `object` | Measurement unit, when available. | `source_units_unspecified` | | `dimension_details` | `string` | Source dimension. | `Package` | | `source_provider` | `object` | Publishing organization. | `MDPA` | | `source_dataset` | `object` | Source package title. | `Selected tourism statistics for Hotel - Travel arrangement, %, 2015, 201` | | `source_resource` | `object` | Source resource title. | `CSV File` | | `source_package_id` | `object` | CKAN package UUID. | `37f12ef7-49d1-49d7-97e0-aef7863d0fed` | | `source_resource_id` | `object` | CKAN resource UUID. | `b3f420cb-f327-4f68-8c7c-eb4d45c9d54a` | | `source_url` | `object` | Original CSV URL. | `https://data.govmu.org/dataset/37f12ef7-49d1-49d7-97e0-aef7863d0fed/reso` | | `license_id` | `object` | Source license identifier. | `cc-by` | | `retrieved_at` | `object` | UTC retrieval timestamp. | `2026-07-16T19:23:24Z` | ## Usage ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-mauritius-selected-tourism-statistics-for-hotel-travel-arrangement-2-0e5cf083") df = ds["train"].to_pandas() print(df.head()) ``` ### Filter to one country ```python sample_country = df[df["country_iso3"] == "MUS"] ``` ### Work with indicators ```python if "indicator_id" in df.columns: print(df["indicator_id"].value_counts().head()) sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns]) ``` ## Citation ```bibtex @misc{electric_sheep_africa_africa_mauritius_selected_tourism_statistics_for_hotel_travel_arrangement_2_0e5c_1970, title = {Selected tourism statistics for Hotel - Travel arrangement, %, 2015, 2018 and 2023 | Africa (Mauritius official open data)}, author = {MDPA}, year = {1970}, url = {https://data.govmu.org/dataset/selected-tourism-statistics-for-hotel-travel-arrangement-2015-2018-and-2023}, publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa}, howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-selected-tourism-statistics-for-hotel-travel-arrangement-2-0e5cf083}} } ``` ## License Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Original data (c) MDPA. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging. ## About Electric Sheep Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use `load_dataset()` to start working in seconds. Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica) --- Provenance: ingested 2026-07-16 via the Electric Sheep pipeline. Source URL: https://data.govmu.org/dataset/37f12ef7-49d1-49d7-97e0-aef7863d0fed/resource/b3f420cb-f327-4f68-8c7c-eb4d45c9d54a/download/book1.csv