electricsheepafrica/africa-mauritius-arrival-and-departure-of-tourist-by-year-age-group-and-gen-647d1ea9

Arrival and Departure of Tourist by Year Age Group and Gen | Africa (MDPA)

136 rows - 1 Africa country/area - 2019-2020 - 17 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 136 rows from MDPA, covering Arrival and Departure of Tourist by Year Age Group and Gen. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Demographic datasets help analysts understand population structure, household conditions, migration, gender, age, and settlement patterns.

Source-provided context: The data shows number of arrival and departure of tourist by year, by travel status, by age group and by gender

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

Dimension	Value
Rows	136
Countries/areas	1
First period	2019
Last period	2020
Indicators	17
Columns	20
Source format	CSV

Geographic Coverage

Top areas shown below, sorted by row count when available:

Area	Rows	First year	Last year	Name
MU	136	2019	2020	Mauritius

Indicators, Variables, Or Resource Contents

• arrival-and-departure-of-tourist-by-year-age-group-and-gender-under-1-56b9f4ae - Arrival and Departure of Tourist by year, age group and gender - under 1(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-1-4-a76f519e - Arrival and Departure of Tourist by year, age group and gender - d 1 4(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-5-9-027c859a - Arrival and Departure of Tourist by year, age group and gender - d 5 9(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-10-14-51e75f59 - Arrival and Departure of Tourist by year, age group and gender - d 10 14(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-15-19-58d9ff8a - Arrival and Departure of Tourist by year, age group and gender - d 15 19(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-20-24-c9e1f7c0 - Arrival and Departure of Tourist by year, age group and gender - d 20 24(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-25-29-c769dd67 - Arrival and Departure of Tourist by year, age group and gender - d 25 29(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-30-34-9a285493 - Arrival and Departure of Tourist by year, age group and gender - d 30 34(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-35-39-569157ac - Arrival and Departure of Tourist by year, age group and gender - d 35 39(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-40-44-44ca86a4 - Arrival and Departure of Tourist by year, age group and gender - d 40 44(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-45-49-b278edc1 - Arrival and Departure of Tourist by year, age group and gender - d 45 49(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-50-54-6065293c - Arrival and Departure of Tourist by year, age group and gender - d 50 54(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-55-59-0f0932ef - Arrival and Departure of Tourist by year, age group and gender - d 55 59(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-60-64-3964f3d5 - Arrival and Departure of Tourist by year, age group and gender - d 60 64(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-65-69-ed4ebc88 - Arrival and Departure of Tourist by year, age group and gender - d 65 69(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-70-and-o-bd9c9022 - Arrival and Departure of Tourist by year, age group and gender - d 70 and over(source_units_unspecified)
• arrival-and-departure-of-tourist-by-year-age-group-and-gender-not-stated-2391a5c4 - Arrival and Departure of Tourist by year, age group and gender - not stated(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	arrival-and-departure-of-tourist-by-year-age-group-and-gender-under-1...
indicator_name	string	Human-readable indicator name.	Arrival and Departure of Tourist by year, age group and gender - under 1
country_iso3	string	ISO3 country or area code.	MU
country_name	string	Country or area name.	Mauritius
year	int64	Observation year.	2019
value	double	Numeric observation value.	4822.0
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_status	string	Source dimension retained during long-form normalization.	Arrival
dimension_gender	string	Source dimension retained during long-form normalization.	Male
source_period_start_year	int64	Start year inferred from source metadata.	``
source_period_end_year	int64	End year inferred from source metadata.	``
source_period_label	string	Source column from the original resource.	``
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	MDPA
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Arrival and Departure of Tourist by year, age group and gender
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Arrival-and-Departure-of-Tourist-by-year-age-group-and-gender_0.csv
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	452a5676-4fec-4451-808f-6edfeb3ea6de
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	53d5103d-9498-4765-be6f-fa94eaf90293
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/452a5676-4fec-4451-808f-6edfeb3ea6de/r...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	CC-BY-SA-4.0
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-08T16:26:20Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-arrival-and-departure-of-tourist-by-year-age-group-and-gen-647d1ea9")
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: Arrival-and-Departure-of-Tourist-by-year-age-group-and-gender_0.csv
• License: CC BY-SA 4.0
• Retrieved/generated: 2026-08-08T16:42:03Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-arrival-and-departure-of-tourist-by-year-age-group-and-gen-647d1ea9

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

• Build demographic profiles
• Normalize indicators per capita
• Join with service-delivery datasets
• 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_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_mauritius_arrival_and_departure_of_tourist_by_year_age_group_and_gen_647d_2020,
  title        = {Arrival and Departure of Tourist by Year Age Group and Gen | Africa (MDPA)},
  author       = {MDPA},
  year         = {2020},
  url          = {https://data.govmu.org/dataset/arrival-and-departure-tourist-year-age-group-and-gender},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-arrival-and-departure-of-tourist-by-year-age-group-and-gen-647d1ea9}}
}

License

Released under CC BY-SA 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.

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Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/arrival-and-departure-tourist-year-age-group-and-gender