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README.md
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---
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dataset_info:
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features:
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- name: id
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dtype: float64
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- name: ident
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dtype: string
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- name: type
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dtype: string
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- name: name
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dtype: string
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- name: latitude_deg
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dtype: float64
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- name: longitude_deg
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dtype: float64
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- name: elevation_ft
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dtype: float64
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- name: continent
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dtype: string
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- name: country_name
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dtype: string
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- name: iso_country
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dtype: string
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- name: region_name
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dtype: string
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- name: iso_region
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dtype: string
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- name: local_region
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dtype: string
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- name: municipality
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dtype: string
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- name: scheduled_service
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dtype: float64
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- name: gps_code
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dtype: string
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- name: icao_code
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dtype: string
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- name: iata_code
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dtype: string
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- name: local_code
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dtype: string
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- name: wikipedia_link
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dtype: string
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- name: keywords
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dtype: string
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- name: score
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dtype: float64
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- name: last_updated
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dtype: timestamp[ns, tz=UTC]
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- name: esa_source
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dtype: string
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- name: esa_processed
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dtype: string
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splits:
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num_bytes: 4363
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num_examples: 17
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download_size: 29618
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dataset_size: 20305
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: test
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path: data/test-*
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---
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---
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annotations_creators:
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- no-annotation
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language_creators:
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- found
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language:
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- en
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license: cc-by-4.0
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multilinguality:
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- monolingual
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size_categories:
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- n<1K
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source_datasets:
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- original
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task_categories:
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- tabular-classification
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- other
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task_ids: []
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tags:
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- africa
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- humanitarian
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- hdx
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- electric-sheep-africa
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- aviation
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- facilities-infrastructure
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- geodata
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- hxl
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- libya-floods
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- transportation
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- lby
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pretty_name: "Airports in Libya"
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dataset_info:
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splits:
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- name: train
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num_examples: 65
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- name: test
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num_examples: 16
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---
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# Airports in Libya
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**Publisher:** OurAirports · **Source:** [HDX](https://data.humdata.org/dataset/ourairports-lby) · **License:** `cc-by-igo` · **Updated:** 2026-03-30
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---
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## Abstract
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List of airports in Libya, with latitude and longitude. Unverified community data from http://ourairports.com/countries/LY/
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Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-03-30. Geographic scope: **LBY**.
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*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
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---
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## Dataset Characteristics
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| | |
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|---|---|
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| **Domain** | Natural hazards and disaster risk |
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| **Unit of observation** | First-level administrative unit observations |
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| **Rows (total)** | 82 |
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| **Columns** | 25 (6 numeric, 18 categorical, 0 datetime) |
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| **Train split** | 65 rows |
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| **Test split** | 16 rows |
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| **Geographic scope** | LBY |
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| **Publisher** | OurAirports |
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| **HDX last updated** | 2026-03-30 |
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---
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## Variables
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**Geographic** — `type` (small_airport, medium_airport, closed), `latitude_deg` (range 21.6877–32.9523), `longitude_deg` (range 9.7021–24.6061), `country_name` (Libya, #country +name), `iso_country` (LY, #country +code +iso2) and 5 others.
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**Temporal** — `last_updated`.
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**Outcome / Measurement** — `score` (range 0.0–1050.0).
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**Identifier / Metadata** — `id` (range 3218.0–602664.0), `ident` (#meta +code, LY-0011, HLRA), `name` (#loc +airport +name, Jofra Oilfield Airport, Dahra Airport), `gps_code`, `icao_code` and 4 others.
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**Other** — `elevation_ft` (range -120.0–2674.0), `continent` (AF, #region +continent +code), `scheduled_service` (range 0.0–1.0), `wikipedia_link`.
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---
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## Quick Start
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```python
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from datasets import load_dataset
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ds = load_dataset("electricsheepafrica/africa-ourairports-lby")
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train = ds["train"].to_pandas()
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test = ds["test"].to_pandas()
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print(train.shape)
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train.head()
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```
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---
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## Schema
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| Column | Type | Null % | Range / Sample Values |
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|---|---|---|---|
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| `id` | float64 | 1.2% | 3218.0 – 602664.0 (mean 149492.2346) |
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| `ident` | object | 0.0% | #meta +code, LY-0011, HLRA |
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| `type` | object | 0.0% | small_airport, medium_airport, closed |
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| `name` | object | 0.0% | #loc +airport +name, Jofra Oilfield Airport, Dahra Airport |
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| `latitude_deg` | float64 | 1.2% | 21.6877 – 32.9523 (mean 29.5833) |
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| `longitude_deg` | float64 | 1.2% | 9.7021 – 24.6061 (mean 17.6512) |
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| `elevation_ft` | float64 | 13.4% | -120.0 – 2674.0 (mean 734.4366) |
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| `continent` | object | 0.0% | AF, #region +continent +code |
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| `country_name` | object | 0.0% | Libya, #country +name |
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| `iso_country` | object | 0.0% | LY, #country +code +iso2 |
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| `region_name` | object | 0.0% | Al Wahat District, Surt District, Al Jufrah District |
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| `iso_region` | object | 0.0% | LY-WA, LY-SR, LY-JU |
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| `local_region` | object | 0.0% | WA, SR, JU |
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| `municipality` | object | 32.9% | Zillah, Ras Lanuf, Tripoli |
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| `scheduled_service` | float64 | 1.2% | 0.0 – 1.0 (mean 0.1111) |
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| `gps_code` | object | 25.6% | |
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| `icao_code` | object | 76.8% | |
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| `iata_code` | object | 76.8% | |
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| `local_code` | object | 72.0% | |
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| `wikipedia_link` | object | 68.3% | |
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| `keywords` | object | 68.3% | |
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| `score` | float64 | 1.2% | 0.0 – 1050.0 (mean 155.5556) |
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| `last_updated` | datetime64[ns, UTC] | 1.2% | |
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| `esa_source` | object | 0.0% | |
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| `esa_processed` | object | 0.0% | |
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---
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## Numeric Summary
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| Column | Min | Max | Mean | Median |
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|---|---|---|---|---|
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| `id` | 3218.0 | 602664.0 | 149492.2346 | 4609.0 |
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| `latitude_deg` | 21.6877 | 32.9523 | 29.5833 | 29.5424 |
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| `longitude_deg` | 9.7021 | 24.6061 | 17.6512 | 18.3208 |
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| `elevation_ft` | -120.0 | 2674.0 | 734.4366 | 488.0 |
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| `scheduled_service` | 0.0 | 1.0 | 0.1111 | 0.0 |
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| `score` | 0.0 | 1050.0 | 155.5556 | 50.0 |
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---
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## Curation
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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`. 1 column(s) with >80% missing values were removed: `home_link`. 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.
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---
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## Limitations
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- Data originates from OurAirports and has not been independently validated by ESA.
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- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
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- The following columns have >20% missing values and should be treated with caution in modelling: `municipality`, `gps_code`, `icao_code`, `iata_code`, `local_code`, `wikipedia_link`, `keywords`.
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- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/ourairports-lby) for the publisher's own methodology notes and caveats.
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---
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## Citation
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```bibtex
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@dataset{hdx_africa_ourairports_lby,
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title = {Airports in Libya},
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author = {OurAirports},
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year = {2026},
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url = {https://data.humdata.org/dataset/ourairports-lby},
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note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
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}
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```
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---
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*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*
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