Niger · Country Data Coverage
Collection
543 official ML-ready Niger open-data resources, plus related Electric Sheep Africa datasets. • 1349 items • Updated
sdg_goal int64 11 11 | sdg_target float64 11.1 11.1 | sdg_indicator timestamp[ns]date 2001-11-01 00:00:00 2001-11-01 00:00:00 | country_or_territory_name int64 562 562 | country_or_territory_name2 stringclasses 1
value | sdg_region stringclasses 1
value | sdg_sub_region stringclasses 1
value | proportion_of_urban_population_living_in_slums_or_informal_settlements_a float64 70.1 70.4 | data_units stringclasses 1
value | data_reference_year int64 2k 2.02k | data_source stringclasses 1
value | footnote stringclasses 1
value | esa_source stringclasses 1
value | esa_processed stringdate 2026-04-22 00:00:00 2026-04-22 00:00:00 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.385982 | PERCENT | 2,012 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.067048 | PERCENT | 2,001 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.414976 | PERCENT | 2,013 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.183024 | PERCENT | 2,005 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.096042 | PERCENT | 2,002 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.356988 | PERCENT | 2,011 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.44397 | PERCENT | 2,020 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.125036 | PERCENT | 2,003 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.15403 | PERCENT | 2,004 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.44397 | PERCENT | 2,018 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.44397 | PERCENT | 2,016 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.44397 | PERCENT | 2,021 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.44397 | PERCENT | 2,022 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.241012 | PERCENT | 2,007 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.327994 | PERCENT | 2,010 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.44397 | PERCENT | 2,014 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.44397 | PERCENT | 2,019 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
11 | 11.1 | 2001-11-01T00:00:00 | 562 | Niger | Sub-Saharan Africa | Western Africa | 70.212018 | PERCENT | 2,006 | (a) UN-Habitat Urban Indicators Database | (a) Proportion of urban population living in slums or informal settlements. The estimates are based on the global methodology on household deprivations where the inhabitants suffer one or more of the following ‘household deprivations’: Lack of access to improved water services, Lack of access to improved sanitation fac... | HDX | 2026-04-22 |
Africa Settlements Niger | Africa (Electric Sheep Africa metadata inventory)
Size category: n<1K - Formats: parquet - Sector: other_unclassified - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
The current Hugging Face metadata does not include a long source description, so users should inspect the files and upstream references before high-stakes use.
Dataset Profile
| Field | Value |
|---|---|
| Hugging Face repo | electricsheepafrica/africa-settlements-niger |
| Sector | other_unclassified |
| Topic tags | other_unclassified |
| Modalities | tabular, text |
| Formats | parquet |
| Size category | n<1K |
| Countries | Niger |
| ISO3 coverage | NER |
| Last modified on HF | 2026-04-22 06:17:00+00:00 |
| Inventory snapshot | 2026-07-16T16:00:34Z |
How To Read This Dataset
- Start from the repository files and the dataset viewer when available.
- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
- Preserve missing values until you have a defensible imputation rule.
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-settlements-niger")
print(ds)
split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])
Convert To Pandas When Tabular
from datasets import Dataset
first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
df = first_split.to_pandas()
print(df.head())
Data Quality Notes
- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
- Exact schema, row counts, and source files should be inspected in the repository data files.
- Metadata gaps from the inventory: sector, upstream_publisher, license, language, description.
- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
Source And Provenance
- Source context: Electric Sheep Africa metadata inventory
- Publisher/source attribution: Public dataset metadata
- License: Source-specific or other license
- Hugging Face URL: https://huggingface.co/datasets/electricsheepafrica/africa-settlements-niger
- Inventory retrieved at:
2026-07-16T16:00:34Z
Suggested Analyses
- Inspect schema and missingness before modeling.
- Profile variables by geography, time, and subgroup columns where present.
- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
Citation
@misc{electric_sheep_africa_africa_settlements_niger_2026,
title = {Africa Settlements Niger | Africa (Electric Sheep Africa metadata inventory)},
author = {Public dataset metadata},
year = {2026},
url = {https://huggingface.co/datasets/electricsheepafrica/africa-settlements-niger},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-settlements-niger}}
}
License
Released under Source-specific or other license.
Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
About Electric Sheep Africa
Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.
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