Upload dataset folder

README.md

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+---
+license: cc-by-4.0
+language:
+- en
+task_categories:
+- tabular-classification
+- tabular-regression
+multilinguality: monolingual
+size_categories:
+- 1M<n<10M
+tags:
+- tabular
+- zip
+- africa
+- libya
+- official-statistics
+- open-data
+- population
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-00000-of-00001.parquet
+pretty_name: "Libya: High Resolution Population Density Maps + Demographic Estimates | Africa (Libya official open data)"
+---
+
+# Libya: High Resolution Population Density Maps + Demographic Estimates | Africa (Libya official open data)
+
+2,714,516 rows - 1 Africa country - 2020 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
+
+![rows](https://img.shields.io/badge/rows-2714516-blue)
+![countries](https://img.shields.io/badge/countries-1-green)
+![years](https://img.shields.io/badge/years-2020-orange)
+![indicators](https://img.shields.io/badge/indicators-0-purple)
+![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)
+
+## TL;DR
+
+This dataset packages one official `ZIP` resource from **Libya** as
+ML-ready Parquet. The source file is the provenance boundary; all usable
+indicators or tabular columns from the resource stay together in this repo.
+
+## About the source
+
+- **Source:** [Libya: High Resolution Population Density Maps + Demographic Estimates](https://data.humdata.org/dataset/highresolutionpopulationdensitymaps-lby)
+- **Publisher:** AI for Good at Meta
+- **Resource:** [lby_men_2020_csv.zip](https://data.humdata.org/dataset/3aa70182-5982-4161-8651-e68f92f1e0bc/resource/669c3d90-c998-4b51-b9c6-d5860159196b/download/lby_men_2020_csv.zip)
+- **Format:** `ZIP`
+- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Packaging mode:** `tabular_resource`
+
+## Geographic coverage
+
+1 Africa country:
+
+| Country | Rows | First year | Last year | Name |
+|---------|-----:|-----------:|----------:|------|
+| `LBY` | 2,714,516 | 2020 | 2020 | `Libya` |
+
+## Indicators or Resource Contents
+
+- This source file is packaged as a normalized tabular resource.
+
+## Schema
+
+| Column | Type | Description | Example |
+|--------|------|-------------|---------|
+| `source_record_id` | `string` | Stable row identifier for tabular resources. | `669c3d90-c998-4b51-b9c6-d5860159196b:0` |
+| `country_iso3` | `category` | ISO3 country code. | `LBY` |
+| `country_name` | `category` | Country name. | `Libya` |
+| `year` | `Int64` | Observation year. | `2020` |
+| `longitude` | `float64` | Source column. | `10.00597222237502` |
+| `latitude` | `float64` | Source column. | `34.00013888885886` |
+| `lby_men_2020` | `float64` | Source column. | `2.537482` |
+| `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `2020` |
+| `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `2020` |
+| `source_period_label` | `category` | Human-readable period inferred from source resource metadata. | `2020` |
+| `source_provider` | `category` | Publishing organization. | `AI for Good at Meta` |
+| `source_dataset` | `category` | Source package title. | `Libya: High Resolution Population Density Maps + Demographic Estimates` |
+| `source_resource` | `category` | Source resource title. | `lby_men_2020_csv.zip` |
+| `source_package_id` | `category` | CKAN package UUID. | `3aa70182-5982-4161-8651-e68f92f1e0bc` |
+| `source_resource_id` | `category` | CKAN resource UUID. | `669c3d90-c998-4b51-b9c6-d5860159196b` |
+| `source_url` | `category` | Original source resource URL. | `https://data.humdata.org/dataset/3aa70182-5982-4161-8651-e68f92f1e0bc/re` |
+| `license_id` | `category` | Source license identifier. | `cc-by` |
+| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-17T13:13:43Z` |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("electricsheepafrica/africa-libya-libya-high-resolution-population-density-maps-demographic-26fe86f4")
+df = ds["train"].to_pandas()
+print(df.head())
+```
+
+### Filter to one country
+
+```python
+sample_country = df[df["country_iso3"] == "LBY"]
+```
+
+### Work with indicators
+
+```python
+if "indicator_id" in df.columns:
+    print(df["indicator_id"].value_counts().head())
+    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
+```
+
+## Citation
+
+```bibtex
+@misc{electric_sheep_africa_africa_libya_libya_high_resolution_population_density_maps_demographic_26fe86f4_2020,
+  title        = {Libya: High Resolution Population Density Maps + Demographic Estimates | Africa (Libya official open data)},
+  author       = {AI for Good at Meta},
+  year         = {2020},
+  url          = {https://data.humdata.org/dataset/highresolutionpopulationdensitymaps-lby},
+  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-libya-libya-high-resolution-population-density-maps-demographic-26fe86f4}}
+}
+```
+
+## License
+
+Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
+
+Original data (c) AI for Good at Meta. When using this dataset, please cite both the
+original source above and the Electric Sheep Africa repackaging.
+
+## About Electric Sheep
+
+Electric Sheep Africa is part of the Electric Sheep mission: a unified,
+ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
+open sources, normalize the schemas, package as Parquet, and publish with
+consistent dataset cards so researchers and developers can use `load_dataset()`
+to start working in seconds.
+
+Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)
+
+---
+
+Provenance: ingested 2026-08-17 via the Electric Sheep pipeline. Source URL:
+https://data.humdata.org/dataset/3aa70182-5982-4161-8651-e68f92f1e0bc/resource/669c3d90-c998-4b51-b9c6-d5860159196b/download/lby_men_2020_csv.zip

data/train-00000-of-00001.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6da06ee88c57b031b8d371d7de2262051ef3f7e73700ed56d0c84769f250f4b3
+size 7897141

metadata/source_snapshot.json

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+{
+  "columns": [
+    "source_record_id",
+    "country_iso3",
+    "country_name",
+    "year",
+    "longitude",
+    "latitude",
+    "lby_men_2020",
+    "source_period_start_year",
+    "source_period_end_year",
+    "source_period_label",
+    "source_provider",
+    "source_dataset",
+    "source_resource",
+    "source_package_id",
+    "source_resource_id",
+    "source_url",
+    "license_id",
+    "retrieved_at"
+  ],
+  "generated_at": "2026-08-17T14:31:50Z",
+  "indicator_count": 0,
+  "mode": "tabular_resource",
+  "repo_id": "electricsheepafrica/africa-libya-libya-high-resolution-population-density-maps-demographic-26fe86f4",
+  "rows": 2714516,
+  "source": {
+    "api_base_url": "https://data.humdata.org/api/3/action",
+    "country_iso3": "LBY",
+    "country_name": "Libya",
+    "group_names": "lby",
+    "license_id": "cc-by",
+    "license_title": "Creative Commons Attribution International (CC BY)",
+    "license_url": "http://www.opendefinition.org/licenses/cc-by",
+    "organization_name": "meta",
+    "organization_title": "AI for Good at Meta",
+    "package_id": "3aa70182-5982-4161-8651-e68f92f1e0bc",
+    "package_name": "highresolutionpopulationdensitymaps-lby",
+    "package_notes": "The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Libya: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).",
+    "package_page_url": "https://data.humdata.org/dataset/highresolutionpopulationdensitymaps-lby",
+    "package_title": "Libya: High Resolution Population Density Maps + Demographic Estimates",
+    "portal_url": "https://data.humdata.org",
+    "resource_description": "",
+    "resource_format": "ZIP",
+    "resource_id": "669c3d90-c998-4b51-b9c6-d5860159196b",
+    "resource_last_modified": "2022-08-26T20:41:35.299038",
+    "resource_name": "lby_men_2020_csv.zip",
+    "resource_position": "6",
+    "resource_url": "https://data.humdata.org/dataset/3aa70182-5982-4161-8651-e68f92f1e0bc/resource/669c3d90-c998-4b51-b9c6-d5860159196b/download/lby_men_2020_csv.zip",
+    "tag_names": "baseline population,children,elderly,geodata,men,women,youth"
+  },
+  "year_max": 2020,
+  "year_min": 2020
+}