electricsheepafrica/africa-ourairports-mar

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
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
- morocco-earthquake
- transportation
- mar
pretty_name: "Airports in Morocco"
dataset_info:
splits:
- name: train
num_examples: 36
- name: test
num_examples: 9
---

# Airports in Morocco

**Publisher:** OurAirports · **Source:** [HDX](https://data.humdata.org/dataset/ourairports-mar) · **License:** `cc-by-igo` · **Updated:** 2026-03-30

---

## Abstract

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

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-03-30. Geographic scope: **MAR**.

*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)** | 46 |
| **Columns** | 24 (7 numeric, 16 categorical, 0 datetime) |
| **Train split** | 36 rows |
| **Test split** | 9 rows |
| **Geographic scope** | MAR |
| **Publisher** | OurAirports |
| **HDX last updated** | 2026-03-30 |

---

## Variables

**Geographic** — `type` (small_airport, large_airport, medium_airport), `latitude_deg` (range 28.4476–35.7317), `longitude_deg` (range -11.1617–-1.926), `country_name` (Morocco, #country +name), `iso_country` (MA, #country +code +iso2) and 5 others.

**Temporal** — `last_updated`.

**Outcome / Measurement** — `score` (range 0.0–1200.0).

**Identifier / Metadata** — `id` (range 3100.0–605980.0), `ident` (#meta +code, MA-0013, GMAZ), `name` (#loc +airport +name, El Jadida Airport, Zagora Airport), `gps_code` (#loc +airport +code +gps, GMMD, GMMO), `icao_code` and 3 others.

**Other** — `elevation_ft` (range 10.0–5459.0), `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-ourairports-mar")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `id` | float64 | 2.2% | 3100.0 – 605980.0 (mean 125316.0) |
| `ident` | object | 0.0% | #meta +code, MA-0013, GMAZ |
| `type` | object | 0.0% | small_airport, large_airport, medium_airport |
| `name` | object | 0.0% | #loc +airport +name, El Jadida Airport, Zagora Airport |
| `latitude_deg` | float64 | 2.2% | 28.4476 – 35.7317 (mean 32.5436) |
| `longitude_deg` | float64 | 2.2% | -11.1617 – -1.926 (mean -6.6818) |
| `elevation_ft` | float64 | 17.4% | 10.0 – 5459.0 (mean 1166.9737) |
| `continent` | object | 0.0% | AF, #region +continent +code |
| `country_name` | object | 0.0% | Morocco, #country +name |
| `iso_country` | object | 0.0% | MA, #country +code +iso2 |
| `region_name` | object | 0.0% | Casablanca-Settat Region, Souss-Massa Region, Marrakech-Safi Region |
| `iso_region` | object | 0.0% | MA-06, MA-09, MA-07 |
| `local_region` | float64 | 2.2% | 1.0 – 10.0 (mean 5.6444) |
| `municipality` | object | 0.0% | Casablanca, Zagora, #loc +municipality +name |
| `scheduled_service` | float64 | 2.2% | 0.0 – 1.0 (mean 0.3333) |
| `gps_code` | object | 37.0% | #loc +airport +code +gps, GMMD, GMMO |
| `icao_code` | object | 41.3% | |
| `iata_code` | object | 52.2% | |
| `wikipedia_link` | object | 23.9% | |
| `keywords` | object | 60.9% | |
| `score` | float64 | 2.2% | 0.0 – 1200.0 (mean 375.5556) |
| `last_updated` | datetime64[ns, UTC] | 2.2% | |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `id` | 3100.0 | 605980.0 | 125316.0 | 29845.0 |
| `latitude_deg` | 28.4476 | 35.7317 | 32.5436 | 32.8582 |
| `longitude_deg` | -11.1617 | -1.926 | -6.6818 | -6.8624 |
| `elevation_ft` | 10.0 | 5459.0 | 1166.9737 | 640.0 |
| `local_region` | 1.0 | 10.0 | 5.6444 | 6.0 |
| `scheduled_service` | 0.0 | 1.0 | 0.3333 | 0.0 |
| `score` | 0.0 | 1200.0 | 375.5556 | 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`. 2 column(s) with >80% missing values were removed: `local_code`, `home_link`. 8 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`, `keywords`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/ourairports-mar) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_ourairports_mar,
title = {Airports in Morocco},
author = {OurAirports},
year = {2026},
url = {https://data.humdata.org/dataset/ourairports-mar},
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.*

annotations_creators: 注释创建者：无注释
language_creators: 语言生成方式：从现有公开资源获取
language: 语言：英语
license: 许可协议：知识共享署名4.0（CC BY 4.0）
multilinguality: 多语言属性：单语言
size_categories: 样本规模：少于1000条
source_datasets: 源数据集：原创数据集
task_categories: 任务类别：其他
task_ids: 任务子类别：无
tags: 标签：非洲、人道主义、HDX（人道主义数据交换平台）、electric-sheep-africa（Electric Sheep Africa，非洲电羊团队）、航空、设施与基础设施、地理数据、HXL（人道主义交换语言）、morocco-earthquake（摩洛哥地震）、交通、MAR（摩洛哥国家代码）
pretty_name: 数据集展示名称：摩洛哥机场列表
dataset_info:
splits:
- name: train
num_examples: 36
- name: test
num_examples: 9

# 摩洛哥机场列表

**发布方**：OurAirports · **来源**：[HDX（人道主义数据交换平台）](https://data.humdata.org/dataset/ourairports-mar) · **许可协议**：`cc-by-igo` · **更新时间**：2026-03-30

---

## 摘要
本数据集收录摩洛哥境内所有机场的经纬度信息，数据为来自http://ourairports.com/countries/MA/ 的未经验证的社区贡献数据。

数据集中每一行代表一级行政区划的观测记录，数据最近一次在HDX平台更新的时间为2026年3月30日，地理覆盖范围：**MAR（摩洛哥国家代码）**。

*本数据集已由[Electric Sheep Africa（非洲电羊团队）](https://huggingface.co/electricsheepafrica)整理为适配机器学习的Parquet格式。*

---

## 数据集特征
| 类别 | 详情 |
|---|---|
| **应用领域** | 人道主义与发展数据 |
| **观测单元** | 一级行政区划观测记录 |
| **总样本行数** | 46 |
| **字段总数** | 24个（7个数值型字段、16个分类型字段、0个日期时间型字段） |
| **训练集划分** | 36行 |
| **测试集划分** | 9行 |
| **地理覆盖范围** | MAR |
| **发布方** | OurAirports |
| **HDX平台最后更新时间** | 2026-03-30 |

---

## 变量说明
### 地理类变量
包含`type`（机场类型：小型机场、大型机场、中型机场）、`latitude_deg`（纬度范围：28.4476–35.7317）、`longitude_deg`（经度范围：-11.1617–-1.926）、`country_name`（国家名称：摩洛哥，#country +name）、`iso_country`（国家ISO2代码：MA，#country +code +iso2）等共7个地理类字段（其余5个字段详见字段结构部分）。
### 时间类变量
`last_updated`（最后更新时间）。
### 结果/测量类变量
`score`（得分范围：0.0–1200.0）。
### 标识符/元数据类变量
包含`id`（编号范围：3100.0–605980.0）、`ident`（元代码，示例值：MA-0013、GMAZ，#meta +code）、`name`（机场名称，示例值：El Jadida Airport、Zagora Airport，#loc +airport +name）、`gps_code`（GPS代码，示例值：GMMD、GMMO，#loc +airport +code +gps）、`icao_code`（ICAO代码）等共6个标识符与元数据字段（其余3个字段详见字段结构部分）。
### 其他类变量
包含`elevation_ft`（海拔高度，单位：英尺，范围：10.0–5459.0）、`continent`（大洲代码：AF，#region +continent +code）、`scheduled_service`（定期航班服务标识，范围：0.0–1.0）、`wikipedia_link`（维基百科链接）。

---

## 快速上手示例
python
from datasets import load_dataset

# 加载数据集
ds = load_dataset("electricsheepafrica/africa-ourairports-mar")
# 转换为Pandas DataFrame格式
train_df = ds["train"].to_pandas()
test_df = ds["test"].to_pandas()

# 输出训练集维度
print(train_df.shape)
# 查看训练集前5条数据
train_df.head()

---

## 字段结构
| 字段名 | 数据类型 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `id` | float64 | 2.2% | 3100.0 – 605980.0（均值：125316.0） |
| `ident` | object | 0.0% | #meta +code，示例值：MA-0013、GMAZ |
| `type` | object | 0.0% | 小型机场、大型机场、中型机场 |
| `name` | object | 0.0% | #loc +airport +name，示例值：El Jadida Airport、Zagora Airport |
| `latitude_deg` | float64 | 2.2% | 28.4476 – 35.7317（均值：32.5436） |
| `longitude_deg` | float64 | 2.2% | -11.1617 – -1.926（均值：-6.6818） |
| `elevation_ft` | float64 | 17.4% | 10.0 – 5459.0（均值：1166.9737） |
| `continent` | object | 0.0% | AF（非洲大洲代码），#region +continent +code |
| `country_name` | object | 0.0% | 摩洛哥，#country +name |
| `iso_country` | object | 0.0% | MA（摩洛哥ISO2国家代码），#country +code +iso2 |
| `region_name` | object | 0.0% | 卡萨布兰卡-塞塔特区、苏斯-马萨区、马拉喀什-萨菲区 |
| `iso_region` | object | 0.0% | MA-06、MA-09、MA-07 |
| `local_region` | float64 | 2.2% | 1.0 – 10.0（均值：5.6444） |
| `municipality` | object | 0.0% | 卡萨布兰卡、扎古拉，#loc +municipality +name |
| `scheduled_service` | float64 | 2.2% | 0.0 – 1.0（均值：0.3333） |
| `gps_code` | object | 37.0% | #loc +airport +code +gps，示例值：GMMD、GMMO |
| `icao_code` | object | 41.3% | 无有效取值 |
| `iata_code` | object | 52.2% | 无有效取值 |
| `wikipedia_link` | object | 23.9% | 无有效取值 |
| `keywords` | object | 60.9% | 无有效取值 |
| `score` | float64 | 2.2% | 0.0 – 1200.0（均值：375.5556） |
| `last_updated` | datetime64[ns, UTC] | 2.2% | 无有效取值 |
| `esa_source` | object | 0.0% | 无有效取值 |
| `esa_processed` | object | 0.0% | 无有效取值 |

---

## 数值型字段统计摘要
| 字段名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `id` | 3100.0 | 605980.0 | 125316.0 | 29845.0 |
| `latitude_deg` | 28.4476 | 35.7317 | 32.5436 | 32.8582 |
| `longitude_deg` | -11.1617 | -1.926 | -6.6818 | -6.8624 |
| `elevation_ft`（单位：英尺） | 10.0 | 5459.0 | 1166.9737 | 640.0 |
| `local_region` | 1.0 | 10.0 | 5.6444 | 6.0 |
| `scheduled_service` | 0.0 | 1.0 | 0.3333 | 0.0 |
| `score` | 0.0 | 1200.0 | 375.5556 | 50.0 |

---

## 数据整理流程
原始数据通过CKAN应用程序编程接口从HDX平台下载，并转换为Parquet格式。所有字段名均转换为小写，并统一为蛇形命名规范。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。移除了2个缺失率超过80%的字段：`local_code`与`home_link`。基于解析成功率阈值（>85%），将8个字段从字符串类型转换为数值型或日期时间型。数据集以80:20的比例划分为训练集与测试集，采用固定随机种子（42）进行划分，并以Snappy压缩的Parquet格式存储。

---

## 数据局限性
1. 本数据集源自OurAirports平台，尚未经Electric Sheep Africa（ESA）独立验证。
2. 自动化数据清洗流程无法修正原始数据集中的错报值、定义不一致问题或采样偏差。
3. 以下字段缺失率超过20%，在建模过程中需谨慎使用：`gps_code`、`icao_code`、`iata_code`、`wikipedia_link`、`keywords`。
4. 如需了解发布方的方法论说明与免责声明，请参考[HDX平台原始数据集页面](https://data.humdata.org/dataset/ourairports-mar)。

---

## 引用格式
bibtex
@dataset{hdx_africa_ourairports_mar,
title = {Airports in Morocco},
author = {OurAirports},
year = {2026},
url = {https://data.humdata.org/dataset/ourairports-mar},
note = {由Electric Sheep Africa（https://huggingface.co/electricsheepafrica）重新打包适配机器学习场景}
}

---

*[Electric Sheep Africa（非洲电羊团队）](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施平台，总部位于尼日利亚拉各斯。*