electricsheepafrica/africa-niger-current-situation-fewsnet-ipc-classification

Niger Current Situation FEWS NET Acute Food Insecurity Classifications Data

Publisher: FEWS NET · Source: HDX · License: cc-by · Updated: 2026-04-03

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Abstract

Niger Current Situation FEWS NET Acute Food Insecurity Classifications Data from 2011

Each row in this dataset represents first-level administrative unit observations. Temporal coverage is indicated by the projection_start, projection_end column(s). Geographic scope: NER.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Food security and nutrition
Unit of observation	First-level administrative unit observations
Rows (total)	6,821
Columns	40 (9 numeric, 23 categorical, 7 datetime)
Train split	5,456 rows
Test split	1,364 rows
Geographic scope	NER
Publisher	FEWS NET
HDX last updated	2026-04-03

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Variables

Geographic — country (Niger), country_code (NE), fewsnet_region (West Africa), unit_type (fsc_admin_lhz), specialization_type and 2 others.

Temporal — datacollectionperiod (range 158390.0–377285.0), reporting_date.

Outcome / Measurement — value (range 1.0–3.0).

Identifier / Metadata — source_organization (FEWS NET, Niger), source_document (Food Security Outlook, Niger), geographic_unit_full_name (Agropastoral Belt, Abalak, Tahoua, Niger, Southwestern Cereals with Fan-Palm Products, Gaya, Dosso, Niger, Southern Irrigated Cash Crops, Madaoua, Tahoua, Niger), geographic_unit_name (Rainfed Millet and Sorghum Belt, Agropastoral Belt, Transhumant and Nomad Pastoralism), fnid (NE2012C3050204, NE2012C3070214, NE2012C3060210) and 8 others.

Other — geographic_group (Western Africa), classification_scale, is_allowing_for_assistance, projection_start, projection_end and 12 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-niger-current-situation-fewsnet-ipc-classification")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
source_organization	object	0.0%	FEWS NET, Niger
source_document	object	0.0%	Food Security Outlook, Niger
country	object	0.0%	Niger
country_code	object	0.0%	NE
geographic_group	object	0.0%	Western Africa
fewsnet_region	object	0.0%	West Africa
geographic_unit_full_name	object	0.0%	Agropastoral Belt, Abalak, Tahoua, Niger, Southwestern Cereals with Fan-Palm Products, Gaya, Dosso, Niger, Southern Irrigated Cash Crops, Madaoua, Tahoua, Niger
geographic_unit_name	object	0.0%	Rainfed Millet and Sorghum Belt, Agropastoral Belt, Transhumant and Nomad Pastoralism
unit_type	object	0.0%	fsc_admin_lhz
fnid	object	0.0%	NE2012C3050204, NE2012C3070214, NE2012C3060210
classification_scale	object	0.0%
scenario_name	object	0.0%
preference_rating	int64	0.0%	90.0 – 90.0 (mean 90.0)
is_allowing_for_assistance	bool	0.0%
projection_start	datetime64[ns]	0.0%
projection_end	datetime64[ns]	0.0%
status	object	0.0%
value	float64	0.2%	1.0 – 3.0 (mean 1.4152)
description	object	0.2%
id	int64	0.0%	24350017.0 – 41224446.0 (mean 27552804.3935)
datacollectionperiod	int64	0.0%	158390.0 – 377285.0 (mean 212533.6596)
datacollection	int64	0.0%	168123.0 – 388211.0 (mean 223775.4724)
scenario	object	0.0%
geographic_unit	int64	0.0%	25144.0 – 257729.0 (mean 79763.6297)
datasourceorganization	int64	0.0%	2032.0 – 2032.0 (mean 2032.0)
datasourcedocument	int64	0.0%	6569.0 – 6569.0 (mean 6569.0)
dataseries	int64	0.0%	6467681.0 – 7843391.0 (mean 6598560.0733)
dataseries_name	object	0.0%
specialization_type	object	0.0%
dataseries_specialization_type	object	0.0%
data_usage_policy	object	0.0%
created	datetime64[ns]	0.0%
modified	datetime64[ns]	0.0%
status_changed	datetime64[ns]	0.0%
collection_status	object	0.0%
collection_status_changed	datetime64[ns]	0.0%
collection_schedule	object	0.0%
reporting_date	datetime64[ns]	0.0%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
preference_rating	90.0	90.0	90.0	90.0
value	1.0	3.0	1.4152	1.0
id	24350017.0	41224446.0	27552804.3935	24472794.0
datacollectionperiod	158390.0	377285.0	212533.6596	159229.0
datacollection	168123.0	388211.0	223775.4724	168604.0
geographic_unit	25144.0	257729.0	79763.6297	25348.0
datasourceorganization	2032.0	2032.0	2032.0	2032.0
datasourcedocument	6569.0	6569.0	6569.0	6569.0
dataseries	6467681.0	7843391.0	6598560.0733	6486884.0

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Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. 3 column(s) with >80% missing values were removed: pct_phase3, pct_phase4, pct_phase5. 7 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

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Limitations

• Data originates from FEWS NET and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_niger_current_situation_fewsnet_ipc_classification,
  title     = {Niger Current Situation FEWS NET Acute Food Insecurity Classifications Data},
  author    = {FEWS NET},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/niger_current_situation_fewsnet_ipc_classification},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.