electricsheepafrica/africa-nigeria-northeast-nigeria-3w-january-june-2021

Nigeria: Northeast Nigeria 3W (January-June 2021)

Publisher: OCHA Nigeria · Source: HDX · License: other-pd-nr · Updated: 2021-08-30

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Abstract

Northeast Nigeria 3Ws for January to June 2021

Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2021-08-30. Geographic scope: NGA.

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

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Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	Subnational administrative unit observations
Rows (total)	21,743
Columns	17 (0 numeric, 17 categorical, 0 datetime)
Train split	17,394 rows
Test split	4,348 rows
Geographic scope	NGA
Publisher	OCHA Nigeria
HDX last updated	2021-08-30

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Variables

Geographic — org_acronym (IOM, UNICEF, DRC), type_of_organization (International NGO, UN Agency, National NGO), operation_type (Reporting, Implementing, #operation+type), states (Borno, Adamawa, Yobe), state_pcode (NGA008, NGA002, NGA036) and 3 others.

Temporal — month.

Identifier / Metadata — esa_source, esa_processed.

Other — organization (International Organization for Migration, United Nations Children's Emergency Fund, Danish Refugee Council), project_sector (Protection, Nutrition, Water, Sanitation & Hygiene), activities (Nutrition Activity, Health Activities, Sensitization and community engagement), status (Ongoing, Completed, completed), ishrp and 1 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-nigeria-northeast-nigeria-3w-january-june-2021")
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
organization	object	0.0%	International Organization for Migration, United Nations Children's Emergency Fund, Danish Refugee Council
org_acronym	object	0.0%	IOM, UNICEF, DRC
type_of_organization	object	0.0%	International NGO, UN Agency, National NGO
operation_type	object	0.0%	Reporting, Implementing, #operation+type
project_sector	object	0.0%	Protection, Nutrition, Water, Sanitation & Hygiene
activities	object	0.6%	Nutrition Activity, Health Activities, Sensitization and community engagement
status	object	0.1%	Ongoing, Completed, completed
states	object	0.0%	Borno, Adamawa, Yobe
state_pcode	object	0.0%	NGA008, NGA002, NGA036
lga	object	0.0%	Maiduguri, Jere, Gwoza
lga_pcode	object	0.0%
ishrp	object	0.0%
response_type	object	0.0%
isrp	object	0.0%
month	object	0.0%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
No numeric columns.

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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. 22,888 exact duplicate rows were removed. 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_northeast_nigeria_3w_january_june_2021,
  title     = {Nigeria: Northeast Nigeria 3W (January-June 2021)},
  author    = {OCHA Nigeria},
  year      = {2021},
  url       = {https://data.humdata.org/dataset/nigeria-northeast-nigeria-3w-january-june-2021},
  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.