Upload dataset folder

README.md

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+---
+license: cc-by-sa-4.0
+language:
+- en
+task_categories:
+- tabular-classification
+- tabular-regression
+multilinguality: monolingual
+size_categories:
+- n<1K
+tags:
+- tabular
+- csv
+- africa
+- djibouti
+- official-statistics
+- open-data
+- education
+- health
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-00000-of-00001.parquet
+pretty_name: "Djibouti - Accessibility Indicators | Africa (Djibouti official open data)"
+---
+
+# Djibouti - Accessibility Indicators | Africa (Djibouti official open data)
+
+912 rows - 1 Africa country - 2020-2025 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
+
+![rows](https://img.shields.io/badge/rows-912-blue)
+![countries](https://img.shields.io/badge/countries-1-green)
+![years](https://img.shields.io/badge/years-2020-2025-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 packages one official `CSV` resource from **Djibouti** 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:** [Djibouti - Accessibility Indicators](https://data.humdata.org/dataset/djibouti-accessibility-indicators)
+- **Publisher:** HeiGIT (Heidelberg Institute for Geoinformation Technology)
+- **Resource:** [DJI_hospitals_access_long.csv](https://hot.storage.heigit.org/heigit-hdx-public/access/dji/DJI_hospitals_access_long.csv)
+- **Format:** `CSV`
+- **License:** [CC BY-SA](https://creativecommons.org/licenses/by-sa/4.0/)
+- **Packaging mode:** `tabular_resource`
+
+## Geographic coverage
+
+1 Africa country:
+
+| Country | Rows | First year | Last year | Name |
+|---------|-----:|-----------:|----------:|------|
+| `DJI` | 912 | 2020 | 2025 | `Djibouti` |
+
+## 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. | `68c21418-c7e7-4dfc-84b2-a516a4bdc48d:0` |
+| `country_iso3` | `category` | ISO3 country code. | `DJI` |
+| `country_name` | `category` | Country name. | `Djibouti` |
+| `name` | `string` | Source column. | `Ali Sabeh` |
+| `iso` | `string` | Source column. | `` |
+| `id` | `string` | Source column. | `41766387B65421474667097` |
+| `country` | `string` | Source column. | `DJI` |
+| `admin_level` | `string` | Source column. | `ADM2` |
+| `category` | `string` | Source column. | `hospitals` |
+| `range_type` | `string` | Source column. | `TIME` |
+| `range` | `int64` | Source column. | `600` |
+| `population_type` | `string` | Source column. | `adults` |
+| `population` | `int64` | Source column. | `61563` |
+| `population_share` | `float64` | Source column. | `45.42` |
+| `population_interval` | `int64` | Source column. | `61563` |
+| `population_interval_share` | `float64` | Source column. | `45.42` |
+| `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. | `2025` |
+| `source_period_label` | `category` | Human-readable period inferred from source resource metadata. | `2020-2025` |
+| `source_provider` | `category` | Publishing organization. | `HeiGIT (Heidelberg Institute for Geoinformation Technology)` |
+| `source_dataset` | `category` | Source package title. | `Djibouti - Accessibility Indicators` |
+| `source_resource` | `category` | Source resource title. | `DJI_hospitals_access_long.csv` |
+| `source_package_id` | `category` | CKAN package UUID. | `96d785fb-7c93-4e45-8a4b-991f22b2e922` |
+| `source_resource_id` | `category` | CKAN resource UUID. | `68c21418-c7e7-4dfc-84b2-a516a4bdc48d` |
+| `source_url` | `category` | Original source resource URL. | `https://hot.storage.heigit.org/heigit-hdx-public/access/dji/DJI_hospital` |
+| `license_id` | `category` | Source license identifier. | `cc-by-sa` |
+| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-16T10:32:57Z` |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("electricsheepafrica/africa-djibouti-djibouti-accessibility-indicators-2512c57e")
+df = ds["train"].to_pandas()
+print(df.head())
+```
+
+### Filter to one country
+
+```python
+sample_country = df[df["country_iso3"] == "DJI"]
+```
+
+### 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_djibouti_djibouti_accessibility_indicators_2512c57e_2025,
+  title        = {Djibouti - Accessibility Indicators | Africa (Djibouti official open data)},
+  author       = {HeiGIT (Heidelberg Institute for Geoinformation Technology)},
+  year         = {2025},
+  url          = {https://data.humdata.org/dataset/djibouti-accessibility-indicators},
+  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-djibouti-djibouti-accessibility-indicators-2512c57e}}
+}
+```
+
+## License
+
+Released under [CC BY-SA](https://creativecommons.org/licenses/by-sa/4.0/).
+
+Original data (c) HeiGIT (Heidelberg Institute for Geoinformation Technology). 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 2026-08-16 via the Electric Sheep pipeline. Source URL:
+https://hot.storage.heigit.org/heigit-hdx-public/access/dji/DJI_hospitals_access_long.csv

data/train-00000-of-00001.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bd26946d2a5872a830ed928549ab8bfefce07b1e5a9634e57dc73f0b2713efc0
+size 29010

metadata/source_snapshot.json

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+{
+  "columns": [
+    "source_record_id",
+    "country_iso3",
+    "country_name",
+    "name",
+    "iso",
+    "id",
+    "country",
+    "admin_level",
+    "category",
+    "range_type",
+    "range",
+    "population_type",
+    "population",
+    "population_share",
+    "population_interval",
+    "population_interval_share",
+    "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": "2026-08-16T11:14:32Z",
+  "indicator_count": 0,
+  "mode": "tabular_resource",
+  "repo_id": "electricsheepafrica/africa-djibouti-djibouti-accessibility-indicators-2512c57e",
+  "rows": 912,
+  "source": {
+    "api_base_url": "https://data.humdata.org/api/3/action",
+    "country_iso3": "DJI",
+    "country_name": "Djibouti",
+    "group_names": "dji",
+    "license_id": "cc-by-sa",
+    "license_title": "Creative Commons Attribution Share-Alike (CC BY-SA)",
+    "license_url": "http://www.opendefinition.org/licenses/cc-by-sa",
+    "organization_name": "heidelberg-institute-for-geoinformation-technology",
+    "organization_title": "HeiGIT (Heidelberg Institute for Geoinformation Technology)",
+    "package_id": "96d785fb-7c93-4e45-8a4b-991f22b2e922",
+    "package_name": "djibouti-accessibility-indicators",
+    "package_notes": "This dataset provides insights into spatial accessibility to healthcare and education services across Djibouti. It has been created using free and open tools such as [openrouteservice](https://openrouteservice.org/) and open data sources, primarily [OpenStreetMap](https://www.openstreetmap.org/) (OSM). To assess accessibility to education and healthcare, we use travel-time isochrones—polygons representing areas reachable within a given time or distance by car. We overlay these isochrones with [WorldPop](https://www.worldpop.org/) population data, which provides 100m-resolution estimates. This allows us to calculate the population within time intervals from 10 to 120 minutes away from hospital services and distance intervals from 5 to 50 km away from schools. The unit of analysis is defined by [geoboundaries](https://www.geoboundaries.org/) country borders, and where available we also summarise results at finer administrative levels (ADM 1–4). Data Structure: - **name**: Region or country name. - **iso**: ISO3 country code. - **id**: Unique identifier for the administrative unit. - **country**: ISO3 country code. - **admin_level**: Administrative level of the unit. - **category**: Service category — `education`, `hospitals` or `primary_healthcare`. - **range_type**: Method used for the catchment zone — `distance` or `time`. - **range**: Distance (in meters) or Time away (in seconds) from schools used to generate the polygon. - **population**: Total population within the specified range. - **school_age_population**: Number of school-age individuals within the range. - **school_age_population_share**: Cumulative percentage of school-age population. - **school_age_population_interval**: Incremental school-age population added in the current distance band. - **school_age_population_interval_share**: Proportion of new school-age population in the current interval. - **population_share**: Cumulative percentage of total population. - **population_interval**: Incremental population added in the current distance band. - **population_interval_share**: Share of the total population represented by the current interval. This dataset is one of many [HeiGIT exports on HDX](https://data.humdata.org/organization/heidelberg-institute-for-geoinformation-technology). See the [HeiGIT](https://heigit.org/) website for more information. We are looking forward to hearing about your use-case! Feel free to reach out to us and tell us about your research at [communications@heigit.org](mailto:communications@heigit.org) – we would be happy to amplify your work. References: - [Geldsetzer, P., Reinmuth, M., Ouma, P. O., Lautenbach, S. et al. (2020)](https://www.thelancet.com/journals/lanhl/article/PIIS2666-7568(20)30010-6/fulltext) - [Petricola, S., Reinmuth, M., Lautenbach, S. et al. (2022)](https://ij-healthgeographics.biomedcentral.com/articles/10.1186/s12942-022-00315-2) - [Klipper, I. G., Zipf, A., and Lautenbach, S. (2021)](https://agile-giss.copernicus.org/articles/2/4/2021/) - [Ruiz Sánchez, R., Reinmuth, M., Albornoz, C., Lautenbach, S., and Zipf, A. (2025)](https://agile-giss.copernicus.org/articles/6/10/2025/) Further Information: - [Open Access Lens](https://giscience.github.io/open-access-lens/#/) **Limitations**: * **OSM Completeness**: This analysis relies on OpenStreetMap (OSM) data. While OSM is the most complete open map of the world, data quality varies significantly by region. In areas with unmapped roads or facilities, accessibility may be underestimated. * **Population Estimates**: Population counts are derived from WorldPop top-down estimates (constrained). These are statistical models based on census projections and satellite imagery, not direct census counts, and may contain inaccuracies at the local pixel level. * **Travel Time Assumptions**: Isochrones are calculated using standard vehicle speeds for different road types. These models do not account for real-time traffic, seasonal weather conditions (e.g., flooding), or road surface degradation. * **Boundary Precision**: Administrative boundaries are sourced from geoBoundaries. These may differ slightly from official government demarcations or other schemas.",
+    "package_page_url": "https://data.humdata.org/dataset/djibouti-accessibility-indicators",
+    "package_title": "Djibouti - Accessibility Indicators",
+    "portal_url": "https://data.humdata.org",
+    "resource_description": "DJI_hospitals_access_long.csv for Djibouti",
+    "resource_format": "CSV",
+    "resource_id": "68c21418-c7e7-4dfc-84b2-a516a4bdc48d",
+    "resource_last_modified": "2026-02-25T18:23:36.528393",
+    "resource_name": "DJI_hospitals_access_long.csv",
+    "resource_position": "4",
+    "resource_url": "https://hot.storage.heigit.org/heigit-hdx-public/access/dji/DJI_hospitals_access_long.csv",
+    "tag_names": "education,health facilities,transportation"
+  },
+  "year_max": 2025,
+  "year_min": 2020
+}