README.md

---
license: cc-by-sa-4.0
language:
- en
task_categories:
- tabular-classification
- tabular-regression
multilinguality: multilingual
size_categories:
- n<1K
tags:
- "tabular"
- "africa"
- "open-data"
- "official-statistics"
- "mauritius"
- "mdpa"
- "travel-and-tourism"
- "earnings"
- "tourism"
- "tourist"
- "value-added"
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-00000-of-00001.parquet
pretty_name: "Earnings and Value Added of the Tourism Sector | Africa (MDPA)"
---

# Earnings and Value Added of the Tourism Sector | Africa (MDPA)

**796 rows** - **1 Africa country/area** - **1980-2022** - **source table** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*

![rows](https://img.shields.io/badge/rows-796-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![period](https://img.shields.io/badge/period-1980--2022-orange)
![indicators](https://img.shields.io/badge/indicators-0-purple)
![license](https://img.shields.io/badge/license-cc--by--sa--4.0-lightgrey)

## TL;DR

This dataset contains **796 rows** from **MDPA**, covering **Earnings and Value Added of the Tourism Sector**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

## What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: Dataset shows Tourism Earnings, % contribution to GDP and Value Added (at current basic prices) of the Tourism Sector as from 1983

## How To Read This Dataset

- **One row means:** one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
- **Primary geography column:** `country_iso3`.
- **Best time column:** `year`.
- **Time coverage basis:** year.
- **Recommended join keys:** `country_iso3` where available plus source-specific keys.

## Coverage

| Dimension | Value |
|---|---:|
| Rows | 796 |
| Countries/areas | 1 |
| First period | 1980 |
| Last period | 2022 |
| Indicators | 0 |
| Columns | 194 |
| Source format | XLS |

## Geographic Coverage

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

| Area | Rows | First year | Last year | Name |
|------|-----:|-----------:|----------:|------|
| `MU` | 796 | 1980 | 2022 | `Mauritius` |

## Indicators, Variables, Or Resource Contents

- This repo preserves one source tabular resource with its usable columns kept together.

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `source_record_id` | `string` | Stable row identifier assigned during Electric Sheep Africa engineering. | `3420c2ad-6b29-4021-9c78-df2cbfc7d3a7:table-of-contents:0` |
| `country_iso3` | `dictionary<values=string, indices=int8, ordered=0>` | ISO3 country or area code. | `MU` |
| `country_name` | `dictionary<values=string, indices=int8, ordered=0>` | Country or area name. | `Mauritius` |
| `source_sheet` | `string` | Source column from the original resource. | `Table of contents` |
| `year` | `double` | Observation year. | `1983.0` |
| `d_5a` | `string` | Source column from the original resource. | `5b` |
| `tourist_arrivals_by_country_of_residence_1983_2012` | `string` | Source column from the original resource. | `Tourist arrivals by country of residence (covering a wider range of c...` |
| `source_period_start_year` | `int64` | Start year inferred from source metadata. | `1983` |
| `source_period_end_year` | `int64` | End year inferred from source metadata. | `1983` |
| `source_period_label` | `dictionary<values=string, indices=int8, ordered=0>` | Source column from the original resource. | `1983` |
| `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. | `Earnings and Value Added of the Tourism Sector` |
| `source_resource` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource title, table name, or file name. | `HS_Tourism_Yr22_250523_0.xls` |
| `source_package_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source package identifier. | `bf849e4c-49ca-4c54-8d9f-a05710082cab` |
| `source_resource_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource identifier. | `3420c2ad-6b29-4021-9c78-df2cbfc7d3a7` |
| `source_url` | `dictionary<values=string, indices=int8, ordered=0>` | Original source URL or download URL. | `https://data.govmu.org/dataset/bf849e4c-49ca-4c54-8d9f-a05710082cab/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` |
| `d_1` | `double` | Source column from the original resource. | `` |
| `tourist` | `string` | Source column from the original resource. | `` |
| `a_tourist_is_defined_as_a_non_resident_staying_overnight` | `string` | Source column from the original resource. | `` |
| `1980` | `double` | Source column from the original resource. | `` |
| `d_163230` | `double` | Source column from the original resource. | `` |
| `d_167269` | `double` | Source column from the original resource. | `` |
| `d_6042` | `string` | Source column from the original resource. | `` |
| `d_5722` | `double` | Source column from the original resource. | `` |
| `country_of_disembarkation` | `string` | Source column from the original resource. | `` |
| `1983` | `double` | Source column from the original resource. | `` |
| `1984` | `double` | Source column from the original resource. | `` |
| `1985` | `double` | Source column from the original resource. | `` |
| `1986` | `double` | Source column from the original resource. | `` |
| `1987` | `double` | Source column from the original resource. | `` |
| `1988` | `double` | Source column from the original resource. | `` |
| `1989` | `double` | Source column from the original resource. | `` |
| `1990` | `double` | Source column from the original resource. | `` |
| `1991` | `double` | Source column from the original resource. | `` |
| `1992` | `double` | Source column from the original resource. | `` |
| `1993` | `double` | Source column from the original resource. | `` |
| `1994` | `double` | Source column from the original resource. | `` |
| `1995` | `double` | Source column from the original resource. | `` |
| `1996` | `double` | Source column from the original resource. | `` |
| `1997` | `double` | Source column from the original resource. | `` |
| `1998` | `double` | Source column from the original resource. | `` |
| `1999` | `double` | Source column from the original resource. | `` |
| `2000` | `double` | Source column from the original resource. | `` |
| `2001` | `double` | Source column from the original resource. | `` |
| `2002` | `double` | Source column from the original resource. | `` |
| `2003` | `double` | Source column from the original resource. | `` |
| `2004` | `double` | Source column from the original resource. | `` |
| `2005` | `double` | Source column from the original resource. | `` |
| `2006` | `double` | Source column from the original resource. | `` |
| `2007` | `double` | Source column from the original resource. | `` |
| `2008` | `double` | Source column from the original resource. | `` |
| `2009` | `double` | Source column from the original resource. | `` |
| `2010` | `double` | Source column from the original resource. | `` |
| `2011` | `double` | Source column from the original resource. | `` |
| `2012` | `double` | Source column from the original resource. | `` |
| `2013` | `double` | Source column from the original resource. | `` |
| `2014` | `double` | Source column from the original resource. | `` |
| `2015` | `double` | Source column from the original resource. | `` |
| `2016` | `double` | Source column from the original resource. | `` |
| `2017` | `double` | Source column from the original resource. | `` |
| `2018` | `double` | Source column from the original resource. | `` |
| `2019` | `double` | Source column from the original resource. | `` |
| `2020` | `double` | Source column from the original resource. | `` |
| `2021` | `double` | Source column from the original resource. | `` |
| `2022` | `double` | Source column from the original resource. | `` |
| `month_of_arrival` | `string` | Source column from the original resource. | `` |
| `1974` | `double` | Source column from the original resource. | `` |
| `1975` | `double` | Source column from the original resource. | `` |
| `1976` | `double` | Source column from the original resource. | `` |
| `1977` | `double` | Source column from the original resource. | `` |
| `1978` | `double` | Source column from the original resource. | `` |
| `1979` | `double` | Source column from the original resource. | `` |
| `1981` | `double` | Source column from the original resource. | `` |
| `1982` | `double` | Source column from the original resource. | `` |
| `country_of_residence` | `string` | Source column from the original resource. | `` |
| `europe` | `string` | Source column from the original resource. | `` |
| `d_547061` | `double` | Source column from the original resource. | `` |
| `d_570684` | `double` | Source column from the original resource. | `` |
| `d_631627` | `double` | Source column from the original resource. | `` |
| `d_734506` | `double` | Source column from the original resource. | `` |
| `d_780209` | `double` | Source column from the original resource. | `` |
| `d_824334` | `double` | Source column from the original resource. | `` |
| `d_835946` | `double` | Source column from the original resource. | `` |
| `d_207641` | `double` | Source column from the original resource. | `` |
| `d_145812` | `double` | Source column from the original resource. | `` |
| `d_674511` | `double` | Source column from the original resource. | `` |
| `d_55_1` | `double` | Source column from the original resource. | `` |
| `d_55` | `double` | Source column from the original resource. | `` |
| `d_54_9` | `double` | Source column from the original resource. | `` |
| `d_57_6` | `double` | Source column from the original resource. | `` |
| `d_58_1` | `double` | Source column from the original resource. | `` |
| `d_58_9` | `double` | Source column from the original resource. | `` |
| `d_60_4` | `double` | Source column from the original resource. | `` |
| `d_67_2` | `double` | Source column from the original resource. | `` |
| `d_81_1` | `double` | Source column from the original resource. | `` |
| `d_67_6` | `double` | Source column from the original resource. | `` |
| `tourism_earnings_1_rs_million` | `double` | Source column from the original resource. | `` |
| `value_added_2_rs_million` | `string` | Source column from the original resource. | `` |
| `contribution_to_gdp_2` | `string` | Source column from the original resource. | `` |
| `food_service` | `double` | Source column from the original resource. | `` |
| `hotels` | `double` | Source column from the original resource. | `` |
| `travel_other_services_2` | `double` | Source column from the original resource. | `` |
| `total_tourism_industry` | `double` | Source column from the original resource. | `` |
| `d_470` | `double` | Source column from the original resource. | `` |
| `d_114610` | `double` | Source column from the original resource. | `` |
| `d_115080` | `double` | Source column from the original resource. | `` |
| `d_1301730` | `double` | Source column from the original resource. | `` |
| `d_43` | `double` | Source column from the original resource. | `` |
| `d_4000` | `double` | Source column from the original resource. | `` |
| `september` | `string` | Source column from the original resource. | `` |
| `d_66_8` | `double` | Source column from the original resource. | `` |
| `d_56_8` | `string` | Source column from the original resource. | `` |
| `d_82_9` | `double` | Source column from the original resource. | `` |
| `d_74_4` | `double` | Source column from the original resource. | `` |
| `d_84_9` | `double` | Source column from the original resource. | `` |
| `d_75_9` | `double` | Source column from the original resource. | `` |
| `d_81` | `double` | Source column from the original resource. | `` |
| `d_73_4` | `double` | Source column from the original resource. | `` |
| `d_74_5` | `double` | Source column from the original resource. | `` |
| `d_67_4` | `double` | Source column from the original resource. | `` |
| `d_63_9` | `double` | Source column from the original resource. | `` |
| `d_59_1` | `double` | Source column from the original resource. | `` |
| `d_67_9` | `double` | Source column from the original resource. | `` |
| `d_63_5` | `double` | Source column from the original resource. | `` |
| `d_72_3` | `double` | Source column from the original resource. | `` |
| `d_66_5` | `double` | Source column from the original resource. | `` |
| `d_76` | `double` | Source column from the original resource. | `` |
| `d_71` | `double` | Source column from the original resource. | `` |
| `d_73` | `double` | Source column from the original resource. | `` |
| `d_67` | `double` | Source column from the original resource. | `` |
| `d_77` | `double` | Source column from the original resource. | `` |
| `d_68` | `double` | Source column from the original resource. | `` |
| `d_85` | `double` | Source column from the original resource. | `` |
| `d_75` | `double` | Source column from the original resource. | `` |
| `d_82` | `double` | Source column from the original resource. | `` |
| `d_72` | `double` | Source column from the original resource. | `` |
| `d_77_2` | `double` | Source column from the original resource. | `` |
| `d_68_2` | `double` | Source column from the original resource. | `` |
| `d_76_2` | `double` | Source column from the original resource. | `` |
| `d_74` | `double` | Source column from the original resource. | `` |
| `d_66` | `double` | Source column from the original resource. | `` |
| `d_76_3` | `double` | Source column from the original resource. | `` |
| `d_68_3` | `double` | Source column from the original resource. | `` |
| `d_67_3` | `double` | Source column from the original resource. | `` |
| `d_59` | `double` | Source column from the original resource. | `` |
| `d_69` | `double` | Source column from the original resource. | `` |
| `d_62` | `double` | Source column from the original resource. | `` |
| `d_67_5` | `double` | Source column from the original resource. | `` |
| `d_60` | `double` | Source column from the original resource. | `` |
| `d_71_2` | `double` | Source column from the original resource. | `` |
| `d_63` | `double` | Source column from the original resource. | `` |
| `d_78` | `double` | Source column from the original resource. | `` |
| `d_70` | `double` | Source column from the original resource. | `` |
| `d_68_4` | `double` | Source column from the original resource. | `` |
| `d_61` | `double` | Source column from the original resource. | `` |
| `d_64` | `double` | Source column from the original resource. | `` |
| `d_56` | `double` | Source column from the original resource. | `` |
| `d_58` | `double` | Source column from the original resource. | `` |
| `d_66_2` | `double` | Source column from the original resource. | `` |
| `d_58_2` | `double` | Source column from the original resource. | `` |
| `d_62_2` | `double` | Source column from the original resource. | `` |
| `d_54` | `double` | Source column from the original resource. | `` |
| `d_67_7` | `double` | Source column from the original resource. | `` |
| `d_60_2` | `double` | Source column from the original resource. | `` |
| `d_68_5` | `double` | Source column from the original resource. | `` |
| `d_61_2` | `double` | Source column from the original resource. | `` |
| `d_74_2` | `double` | Source column from the original resource. | `` |
| `d_68_6` | `double` | Source column from the original resource. | `` |
| `d_78_2` | `double` | Source column from the original resource. | `` |
| `d_68_7` | `double` | Source column from the original resource. | `` |
| `d_79` | `double` | Source column from the original resource. | `` |
| `d_69_2` | `double` | Source column from the original resource. | `` |
| `d_82_2` | `double` | Source column from the original resource. | `` |
| `d_72_2` | `double` | Source column from the original resource. | `` |
| `d_77_3` | `double` | Source column from the original resource. | `` |
| `d_65` | `double` | Source column from the original resource. | `` |
| `d_8` | `double` | Source column from the original resource. | `` |
| `d_8_2` | `double` | Source column from the original resource. | `` |
| `d_11` | `double` | Source column from the original resource. | `` |
| `d_9` | `double` | Source column from the original resource. | `` |
| `d_75_2` | `double` | Source column from the original resource. | `` |
| `d_63_2` | `double` | Source column from the original resource. | `` |
| `accommodation` | `double` | Source column from the original resource. | `` |
| `meals_beverages` | `double` | Source column from the original resource. | `` |
| `transport` | `double` | Source column from the original resource. | `` |
| `sightseeing` | `double` | Source column from the original resource. | `` |
| `entertainment` | `double` | Source column from the original resource. | `` |
| `shopping` | `double` | Source column from the original resource. | `` |
| `other` | `double` | Source column from the original resource. | `` |
| `total_1` | `double` | Source column from the original resource. | `` |
| `country` | `string` | Source column from the original resource. | `` |
| `island_of_mauritius_1` | `double` | Source column from the original resource. | `` |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-earnings-and-value-added-of-the-tourism-sector-5c358d8e")
df = ds["train"].to_pandas()
print(df.head())
```

### Inspect Columns

```python
print(df.info())
print(df.head())
```

### Filter By Geography

```python
if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "MU"]
```

### Time-Series Pattern

```python
if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")
```

### Pivot For Analysis

```python
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](https://data.govmu.org/dataset/earnings-and-value-added-tourism-sector)
- **Publisher:** MDPA
- **Portal:** [https://data.govmu.org](https://data.govmu.org)
- **Resource:** [HS_Tourism_Yr22_250523_0.xls](https://data.govmu.org/dataset/bf849e4c-49ca-4c54-8d9f-a05710082cab/resource/3420c2ad-6b29-4021-9c78-df2cbfc7d3a7/download/hs_tourism_yr22_250523_0.xls)
- **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
- **Retrieved/generated:** `2026-08-08T16:45:04Z`
- **Hugging Face repo:** [electricsheepafrica/africa-mauritius-earnings-and-value-added-of-the-tourism-sector-5c358d8e](https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-earnings-and-value-added-of-the-tourism-sector-5c358d8e)

## 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

- Profile the distribution of values
- Compare categories or geographies
- Join with complementary public datasets
- Build time-series views and period-over-period comparisons
- Check missingness before modeling
- Use `country_iso3` as the safest geography join key when present

## Citation

```bibtex
@misc{electric_sheep_africa_africa_mauritius_earnings_and_value_added_of_the_tourism_sector_5c358d8e_2022,
  title        = {Earnings and Value Added of the Tourism Sector | Africa (MDPA)},
  author       = {MDPA},
  year         = {2022},
  url          = {https://data.govmu.org/dataset/earnings-and-value-added-tourism-sector},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-earnings-and-value-added-of-the-tourism-sector-5c358d8e}}
}
```

## License

Released under [CC BY-SA 4.0](https://creativecommons.org/licenses/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.

---

Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/earnings-and-value-added-tourism-sector