electricsheepafrica/africa-nigeria-nema-flood-affected-geographical-areasnorth-east-nigeria-flood-affected-geographi

Nigeria: Flood data

Publisher: OCHA Nigeria · Source: HDX · License: cc-by · Updated: 2025-12-16

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Abstract

The dataset contains information on flood-affected people and locations in Nigeria.

Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2025-12-16. Geographic scope: NGA.

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

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Dataset Characteristics

Domain	Climate and environment
Unit of observation	Subnational administrative unit observations
Rows (total)	45
Columns	8 (4 numeric, 4 categorical, 0 datetime)
Train split	36 rows
Test split	9 rows
Geographic scope	NGA
Publisher	OCHA Nigeria
HDX last updated	2025-12-16

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Variables

Geographic — state (BORNO, YOBE, ADAMAWA), lga (DEMSA, MAGUMERI, MONGUNO), displaced_household (range 0.0–24902.0), displaced_individuals (range 0.0–128268.0).

Demographic — affected_household (range 13.0–49651.0), affected_individuals (range 60.0–250901.0).

Identifier / Metadata — esa_source (HDX), esa_processed (2026-04-04).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-nigeria-nema-flood-affected-geographical-areasnorth-east-nigeria-flood-affected-geographi")
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
state	object	0.0%	BORNO, YOBE, ADAMAWA
lga	object	0.0%	DEMSA, MAGUMERI, MONGUNO
affected_household	int64	0.0%	13.0 – 49651.0 (mean 2366.8222)
affected_individuals	int64	0.0%	60.0 – 250901.0 (mean 11489.0444)
displaced_household	int64	0.0%	0.0 – 24902.0 (mean 1208.8222)
displaced_individuals	int64	0.0%	0.0 – 128268.0 (mean 5809.0444)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-04

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Numeric Summary

Column	Min	Max	Mean	Median
affected_household	13.0	49651.0	2366.8222	600.0
affected_individuals	60.0	250901.0	11489.0444	2880.0
displaced_household	0.0	24902.0	1208.8222	112.0
displaced_individuals	0.0	128268.0	5809.0444	331.0

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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. 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 OCHA Nigeria 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_nigeria_nema_flood_affected_geographical_areasnorth_east_nigeria_flood_affected_geographi,
  title     = {Nigeria: Flood data},
  author    = {OCHA Nigeria},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/nigeria-nema-flood-affected-geographical-areasnorth-east-nigeria-flood-affected-geographical-areas},
  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.