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Datasets:
electricsheepafrica
/
africa-niger-niger-humanitarian-needs-1ad2e2e3

Tasks:
Tabular Classification
Tabular Regression
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
< 1K
Tags:
tabular
csv
africa
niger
official-statistics
open-data
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
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Auto-converted to Parquet Duplicate
source_record_id
string
country_iso3
string
country_name
string
year
int64
description
string
cluster
string
population
int64
in_need
int64
targeted
int64
source_period_start_year
int64
source_period_end_year
int64
source_period_label
string
source_provider
string
source_dataset
string
source_resource
string
source_package_id
string
source_resource_id
string
source_url
string
license_id
string
retrieved_at
string
9811ff53-c5c7-405b-9f83-e1d9f770c2e6:0
NER
Niger
2,026
GHO Estimates
ALL
27,900,000
2,600,000
1,600,000
2,026
2,026
2026
OCHA Humanitarian Programme Cycle Tools (HPC Tools)
Niger: Humanitarian Needs
ner_hpc_needs_api_2026.csv
9d930b4b-f292-4032-80a0-aeaff42a3e13
9811ff53-c5c7-405b-9f83-e1d9f770c2e6
https://data.humdata.org/dataset/9d930b4b-f292-4032-80a0-aeaff42a3e13/resource/9811ff53-c5c7-405b-9f83-e1d9f770c2e6/download/ner_hpc_needs_api_2026.csv
cc-by
2026-08-14T00:35:21Z

Niger: Humanitarian Needs | Africa (Niger official open data)

1 rows - 1 Africa country - 2026 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Niger 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

Geographic coverage

1 Africa country:

Country Rows First year Last year Name
NER 1 2026 2026 Niger

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. 9811ff53-c5c7-405b-9f83-e1d9f770c2e6:0
country_iso3 category ISO3 country code. NER
country_name category Country name. Niger
year Int64 Observation year. 2026
description string Source column. GHO Estimates
cluster string Source column. ALL
population int64 Source column. 27900000
in_need int64 Source column. 2600000
targeted int64 Source column. 1600000
source_period_start_year Int64 First year inferred from source resource metadata. 2026
source_period_end_year Int64 Last year inferred from source resource metadata. 2026
source_period_label category Human-readable period inferred from source resource metadata. 2026
source_provider category Publishing organization. OCHA Humanitarian Programme Cycle Tools (HPC Tools)
source_dataset category Source package title. Niger: Humanitarian Needs
source_resource category Source resource title. ner_hpc_needs_api_2026.csv
source_package_id category CKAN package UUID. 9d930b4b-f292-4032-80a0-aeaff42a3e13
source_resource_id category CKAN resource UUID. 9811ff53-c5c7-405b-9f83-e1d9f770c2e6
source_url category Original source resource URL. https://data.humdata.org/dataset/9d930b4b-f292-4032-80a0-aeaff42a3e13/re
license_id category Source license identifier. cc-by
retrieved_at category UTC retrieval timestamp. 2026-08-14T00:35:21Z

Usage 

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-niger-niger-humanitarian-needs-1ad2e2e3")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country 

sample_country = df[df["country_iso3"] == "NER"]

Work with indicators 

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 

@misc{electric_sheep_africa_africa_niger_niger_humanitarian_needs_1ad2e2e3_2026,
  title        = {Niger: Humanitarian Needs | Africa (Niger official open data)},
  author       = {OCHA Humanitarian Programme Cycle Tools (HPC Tools)},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/niger-humanitarian-needs},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-niger-niger-humanitarian-needs-1ad2e2e3}}
}

License

Released under CC BY 4.0.

Original data (c) OCHA Humanitarian Programme Cycle Tools (HPC Tools). 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

Provenance: ingested 2026-08-14 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/9d930b4b-f292-4032-80a0-aeaff42a3e13/resource/9811ff53-c5c7-405b-9f83-e1d9f770c2e6/download/ner_hpc_needs_api_2026.csv
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