electricsheepafrica/africa-aviation-madagascar

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: other
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- aviation
- facilities-infrastructure
- geodata
- hxl
- transportation
- mdg
pretty_name: "Airports in Madagascar"
dataset_info:
splits:
- name: train
num_examples: 76
- name: test
num_examples: 19
---

# Airports in Madagascar

**Publisher:** OurAirports · **Source:** [HDX](https://data.humdata.org/dataset/ourairports-mdg) · **License:** `Public Domain` · **Updated:** 2026-02-17

---

## Abstract

List of airports in Madagascar, with latitude and longitude. Unverified community data from http://ourairports.com/countries/MG/

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-02-17. Geographic scope: **MDG**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Humanitarian and development data |
| **Unit of observation** | First-level administrative unit observations |
| **Rows (total)** | 95 |
| **Columns** | 23 (6 numeric, 16 categorical, 0 datetime) |
| **Train split** | 76 rows |
| **Test split** | 19 rows |
| **Geographic scope** | MDG |
| **Publisher** | OurAirports |
| **HDX last updated** | 2026-02-17 |

---

## Variables

**Geographic** — `type` (small_airport, medium_airport, large_airport), `latitude_deg` (range -25.3384–-12.2561), `longitude_deg` (range 43.2596–50.3202), `country_name` (Madagascar, #country +name), `iso_country` (MG, #country +code +iso2) and 4 others.

**Temporal** — `last_updated`.

**Outcome / Measurement** — `score` (range 50.0–1050.0).

**Identifier / Metadata** — `id` (range 2907.0–525780.0), `ident` (#meta +code, WAD, FMNB), `name` (Antsirabe Airport, #loc +airport +name, Bemolanga Airport), `gps_code`, `icao_code` and 3 others.

**Other** — `elevation_ft` (range 7.0–4997.0), `continent` (AF, #region +continent +code), `scheduled_service` (range 0.0–1.0), `wikipedia_link`.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-aviation-madagascar")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `id` | float64 | 1.1% | 2907.0 – 525780.0 (mean 126230.266) |
| `ident` | object | 0.0% | #meta +code, WAD, FMNB |
| `type` | object | 0.0% | small_airport, medium_airport, large_airport |
| `name` | object | 0.0% | Antsirabe Airport, #loc +airport +name, Bemolanga Airport |
| `latitude_deg` | float64 | 1.1% | -25.3384 – -12.2561 (mean -18.7329) |
| `longitude_deg` | float64 | 1.1% | 43.2596 – 50.3202 (mean 46.8724) |
| `elevation_ft` | float64 | 12.6% | 7.0 – 4997.0 (mean 883.4578) |
| `continent` | object | 0.0% | AF, #region +continent +code |
| `country_name` | object | 0.0% | Madagascar, #country +name |
| `iso_country` | object | 0.0% | MG, #country +code +iso2 |
| `region_name` | object | 0.0% | Toliara, Mahajanga, Toamasina |
| `iso_region` | object | 0.0% | MG-U, MG-M, MG-A |
| `local_region` | object | 0.0% | U, M, A |
| `municipality` | object | 5.3% | Ambovolavo, Antsirabe, #loc +municipality +name |
| `scheduled_service` | float64 | 1.1% | 0.0 – 1.0 (mean 0.1702) |
| `gps_code` | object | 30.5% | |
| `icao_code` | object | 33.7% | |
| `iata_code` | object | 28.4% | |
| `wikipedia_link` | object | 52.6% | |
| `score` | float64 | 1.1% | 50.0 – 1050.0 (mean 241.4894) |
| `last_updated` | datetime64[ns, UTC] | 1.1% | |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `id` | 2907.0 | 525780.0 | 126230.266 | 32482.5 |
| `latitude_deg` | -25.3384 | -12.2561 | -18.7329 | -18.2704 |
| `longitude_deg` | 43.2596 | 50.3202 | 46.8724 | 47.0921 |
| `elevation_ft` | 7.0 | 4997.0 | 883.4578 | 154.0 |
| `scheduled_service` | 0.0 | 1.0 | 0.1702 | 0.0 |
| `score` | 50.0 | 1050.0 | 241.4894 | 50.0 |

---

## Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 3 column(s) with >80% missing values were removed: `local_code`, `home_link`, `keywords`. 7 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

---

## Limitations

- Data originates from OurAirports and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling: `gps_code`, `icao_code`, `iata_code`, `wikipedia_link`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/ourairports-mdg) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_aviation_madagascar,
title = {Airports in Madagascar},
author = {OurAirports},
year = {2026},
url = {https://data.humdata.org/dataset/ourairports-mdg},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*