electricsheepafrica/africa-niger-niger-situation-des-inondations-404be83d

Niger : Situation des inondations | Africa (Niger official open data)

817 rows - 1 Africa country - 2023 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official XLSX 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

• Source: Niger : Situation des inondations
• Publisher: OCHA Niger
• Resource: NER_SITUATION DES INONDATIONS AU 25 SEPTEMBRE 2023 DSHU MAHGC.xlsx
• Format: XLSX
• License: CC BY 4.0
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
NER	817	2023	2023	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.	48d5da7d-fc8d-4233-afd1-2023c4ae32ef:situation-des-degats-250920-2:0
country_iso3	category	ISO3 country code.	NER
country_name	category	Country name.	Niger
source_sheet	string	Workbook sheet name, when the source is a spreadsheet.	SITUATION DES DEGATS 250920 (2)
year	Int64	Observation year.	2023
localites	string	Source column.	Agadez
nbre_de_menages_sinistres	float64	Source column.	953.0
nbre_de_pers_sinistrees	float64	Source column.	6176.0
nbre_de_maisons_effon	float64	Source column.	676.0
nbre_de_cases_endom	float64	Source column.	7.0
nbre_de_deces	float64	Source column.	5.0
nbre_de_latrines_endom	float64	Source column.	25.0
puits_ensevelis	float64	Source column.	12.0
source_period_start_year	Int64	First year inferred from source resource metadata.	2023
source_period_end_year	Int64	Last year inferred from source resource metadata.	2023
source_period_label	category	Human-readable period inferred from source resource metadata.	2023
source_provider	category	Publishing organization.	OCHA Niger
source_dataset	category	Source package title.	Niger : Situation des inondations
source_resource	category	Source resource title.	NER_SITUATION DES INONDATIONS AU 25 SEPTEMBRE 2023 DSHU MAHGC.xlsx
source_package_id	category	CKAN package UUID.	cfb9413f-1c52-4f22-9f21-297ef01ea3b0
source_resource_id	category	CKAN resource UUID.	48d5da7d-fc8d-4233-afd1-2023c4ae32ef
source_url	category	Original source resource URL.	https://data.humdata.org/dataset/cfb9413f-1c52-4f22-9f21-297ef01ea3b0/re
license_id	category	Source license identifier.	cc-by
retrieved_at	category	UTC retrieval timestamp.	2026-08-14T00:35:21Z
dosso	string	Source column.	``
d_625	float64	Source column.	``
d_4166	float64	Source column.	``
d_534	float64	Source column.	``
d_534_2	float64	Source column.	``
d_0	float64	Source column.	``
d_534_3	float64	Source column.	``
d_534_4	float64	Source column.	``
d_0_2	float64	Source column.	``
d_534_5	float64	Source column.	``
d_62_5	float64	Source column.	``
d_53_2	float64	Source column.	``
d_9_299999999999997	float64	Source column.	``
d_3125	float64	Source column.	``
d_0_3	float64	Source column.	``
d_3125_2	float64	Source column.	``
d_1562_5	float64	Source column.	``
d_350	float64	Source column.	``
d_1212_5	float64	Source column.	``
d_3125_3	float64	Source column.	``
d_700	float64	Source column.	``
d_2425	float64	Source column.	``
nbre_de_petits_ruminants	float64	Source column.	``
nbre_de_gros_ruminant	float64	Source column.	``
aires_de_cultures_inondees_ha	float64	Source column.	``
nbre_de_hangars_emportes	float64	Source column.	``
nbre_de_greniers_endom	float64	Source column.	``
nbre_de_boutiques_endom	float64	Source column.	``
nbre_des_tonnes_de_vivre_endom	float64	Source column.	``
nbre_de_magasins_endom	float64	Source column.	``
nbre_de_classe_endom	float64	Source column.	``
nbre_de_centre_de_sante_endom	float64	Source column.	``
puits_effon	float64	Source column.	``
insfrast_routieres	float64	Source column.	``
lieu_de_cultes	float64	Source column.	``
menages_sinistres	float64	Source column.	``
d_19135	float64	Source column.	``
region	string	Source column.	``
departement	string	Source column.	``
commune	string	Source column.	``
site	string	Source column.	``
partenaires	string	Source column.	``
type_d_assistance	string	Source column.	``
date	string	Observation date.	``
nombre_de_menages_assistes	float64	Source column.	``
riz_t	float64	Source column.	``
niebe_kg	float64	Source column.	``
huile_litre	float64	Source column.	``
sel_kg	string	Source column.	``
nbre_de_kits_abris	float64	Source column.	``
riz_tonnes	float64	Source column.	``
mil_tonnes	float64	Source column.	``
niebe_tonnes	string	Source column.	``
total_tonnes	string	Source column.	``
huile_litres	string	Source column.	``
lieu_prelevement	string	Source column.	``
regions	string	Source column.	``
departement_villes	string	Source column.	``
communes	string	Source column.	``
quantite_totale	float64	Source column.	``
dogondoutchi	string	Source column.	``
matankari	string	Source column.	``
garanga	string	Source column.	``
d_16	float64	Source column.	``
diffa	string	Source column.	``
maine_soroa	string	Source column.	``
maine_soroa_2	string	Source column.	``
n_guel_lamido	string	Source column.	``
d_45	float64	Source column.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-niger-niger-situation-des-inondations-404be83d")
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_situation_des_inondations_404be83d_2023,
  title        = {Niger : Situation des inondations | Africa (Niger official open data)},
  author       = {OCHA Niger},
  year         = {2023},
  url          = {https://data.humdata.org/dataset/niger-situation-des-inondations},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-niger-niger-situation-des-inondations-404be83d}}
}

License

Released under CC BY 4.0.

Original data (c) OCHA Niger. 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

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Provenance: ingested 2026-08-14 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/cfb9413f-1c52-4f22-9f21-297ef01ea3b0/resource/48d5da7d-fc8d-4233-afd1-2023c4ae32ef/download/ner_situation-des-inondations-au-25-septembre-2023-dshu-mahgc.xlsx