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indicator_id
stringclasses
2 values
indicator_name
stringclasses
2 values
country_iso3
stringclasses
1 value
country_name
stringclasses
1 value
date
stringdate
1970-01-01 00:00:00
1970-01-01 00:00:00
year
int64
1.97k
1.97k
value
float64
4.4
95.6
unit
stringclasses
1 value
dimension_year
stringclasses
2 values
source_provider
stringclasses
1 value
source_dataset
stringclasses
1 value
source_resource
stringclasses
1 value
source_package_id
stringclasses
1 value
source_resource_id
stringclasses
1 value
source_url
stringclasses
1 value
license_id
stringclasses
1 value
retrieved_at
stringdate
2026-07-16 19:23:24
2026-07-16 19:23:24
travel-arrangements-in-2015-2018-and-2023-for-non-hotels-d-2015-bff884f4
Travel arrangements in 2015, 2018 and 2023 for non-hotels - d 2015
MUS
Mauritius
1970-01-01
1,970
4.4
source_units_unspecified
Package
MDPA
Travel arrangements in 2015, 2018 and 2023 for non-hotels
CSV File
ee5efcac-784e-487a-ad1f-4022e1a7d7f2
0e3dc759-1aa0-4998-ab4b-db96920f6394
https://data.govmu.org/dataset/ee5efcac-784e-487a-ad1f-4022e1a7d7f2/resource/0e3dc759-1aa0-4998-ab4b-db96920f6394/download/book1.csv
cc-by
2026-07-16T19:23:24Z
travel-arrangements-in-2015-2018-and-2023-for-non-hotels-d-2015-bff884f4
Travel arrangements in 2015, 2018 and 2023 for non-hotels - d 2015
MUS
Mauritius
1970-01-01
1,970
95.6
source_units_unspecified
Non-package
MDPA
Travel arrangements in 2015, 2018 and 2023 for non-hotels
CSV File
ee5efcac-784e-487a-ad1f-4022e1a7d7f2
0e3dc759-1aa0-4998-ab4b-db96920f6394
https://data.govmu.org/dataset/ee5efcac-784e-487a-ad1f-4022e1a7d7f2/resource/0e3dc759-1aa0-4998-ab4b-db96920f6394/download/book1.csv
cc-by
2026-07-16T19:23:24Z
travel-arrangements-in-2015-2018-and-2023-for-non-hotels-d-2018-4b46d63b
Travel arrangements in 2015, 2018 and 2023 for non-hotels - d 2018
MUS
Mauritius
1970-01-01
1,970
6.2
source_units_unspecified
Package
MDPA
Travel arrangements in 2015, 2018 and 2023 for non-hotels
CSV File
ee5efcac-784e-487a-ad1f-4022e1a7d7f2
0e3dc759-1aa0-4998-ab4b-db96920f6394
https://data.govmu.org/dataset/ee5efcac-784e-487a-ad1f-4022e1a7d7f2/resource/0e3dc759-1aa0-4998-ab4b-db96920f6394/download/book1.csv
cc-by
2026-07-16T19:23:24Z
travel-arrangements-in-2015-2018-and-2023-for-non-hotels-d-2018-4b46d63b
Travel arrangements in 2015, 2018 and 2023 for non-hotels - d 2018
MUS
Mauritius
1970-01-01
1,970
93.8
source_units_unspecified
Non-package
MDPA
Travel arrangements in 2015, 2018 and 2023 for non-hotels
CSV File
ee5efcac-784e-487a-ad1f-4022e1a7d7f2
0e3dc759-1aa0-4998-ab4b-db96920f6394
https://data.govmu.org/dataset/ee5efcac-784e-487a-ad1f-4022e1a7d7f2/resource/0e3dc759-1aa0-4998-ab4b-db96920f6394/download/book1.csv
cc-by
2026-07-16T19:23:24Z

Travel arrangements in 2015, 2018 and 2023 for non-hotels | Africa (Mauritius official open data)

4 rows - 1 Africa country - 1970 - Repackaged by Electric Sheep Africa

rows countries years indicators license

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

Geographic coverage

1 Africa country:

Country Rows First year Last year Name
MUS 4 1970 1970 Mauritius

Indicators or Resource Contents

  • travel-arrangements-in-2015-2018-and-2023-for-non-hotels-d-2015-bff884f4 - Travel arrangements in 2015, 2018 and 2023 for non-hotels - d 2015
  • travel-arrangements-in-2015-2018-and-2023-for-non-hotels-d-2018-4b46d63b - Travel arrangements in 2015, 2018 and 2023 for non-hotels - d 2018

Schema

Column Type Description Example
indicator_id object Stable indicator identifier. travel-arrangements-in-2015-2018-and-2023-for-non-hotels-d-2015-bff884f4
indicator_name object Human-readable indicator name. Travel arrangements in 2015, 2018 and 2023 for non-hotels - d 2015
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. 4.4
unit object Measurement unit, when available. source_units_unspecified
dimension_year string Source dimension. Package
source_provider object Publishing organization. MDPA
source_dataset object Source package title. Travel arrangements in 2015, 2018 and 2023 for non-hotels
source_resource object Source resource title. CSV File
source_package_id object CKAN package UUID. ee5efcac-784e-487a-ad1f-4022e1a7d7f2
source_resource_id object CKAN resource UUID. 0e3dc759-1aa0-4998-ab4b-db96920f6394
source_url object Original CSV URL. https://data.govmu.org/dataset/ee5efcac-784e-487a-ad1f-4022e1a7d7f2/reso
license_id object Source license identifier. cc-by
retrieved_at object UTC retrieval timestamp. 2026-07-16T19:23:24Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-travel-arrangements-in-2015-2018-and-2023-for-non-hotels-3f157212")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "MUS"]

Work with indicators

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

@misc{electric_sheep_africa_africa_mauritius_travel_arrangements_in_2015_2018_and_2023_for_non_hotels_3f1572_1970,
  title        = {Travel arrangements in 2015, 2018 and 2023 for non-hotels | Africa (Mauritius official open data)},
  author       = {MDPA},
  year         = {1970},
  url          = {https://data.govmu.org/dataset/travel-arrangements-in-2015-2018-and-2023-for-non-hotels},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-travel-arrangements-in-2015-2018-and-2023-for-non-hotels-3f157212}}
}

License

Released under CC 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


Provenance: ingested 2026-07-16 via the Electric Sheep pipeline. Source URL: https://data.govmu.org/dataset/ee5efcac-784e-487a-ad1f-4022e1a7d7f2/resource/0e3dc759-1aa0-4998-ab4b-db96920f6394/download/book1.csv

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