electricsheepafrica/africa-chad-operational-presence

Chad: Operational Presence

Publisher: OCHA Chad · Source: HDX · License: cc-by · Updated: 2026-02-18

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Abstract

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working and what they are doing in order to identify gaps and plan for future humanitarian response. This dataset includes a list of humanitarian organizations operating in Chad at admin 2 level.

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-02-18. Geographic scope: TCD.

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

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Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	First-level administrative unit observations
Rows (total)	820
Columns	9 (1 numeric, 8 categorical, 0 datetime)
Train split	656 rows
Test split	164 rows
Geographic scope	TCD
Publisher	OCHA Chad
HDX last updated	2026-02-18

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Variables

Geographic — provinces (Ouaddaï, N'Djamena, Lac), typeorganisation (ONG Internationale, ONG Nationale, Agence UN), physiquecount (range 1.0–1041.0).

Identifier / Metadata — title (TCD14, TCD18, TCD07), esa_source (HDX), esa_processed (2026-04-15).

Other — departement (N'Djamena, Assoungha, Ouara), localite (N'Djamena, Abéché, Farchana), organisation (CRT, WVI, IRC).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-chad-operational-presence")
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
provinces	object	0.0%	Ouaddaï, N'Djamena, Lac
departement	object	1.1%	N'Djamena, Assoungha, Ouara
localite	object	0.0%	N'Djamena, Abéché, Farchana
organisation	object	0.0%	CRT, WVI, IRC
typeorganisation	object	1.1%	ONG Internationale, ONG Nationale, Agence UN
title	object	0.0%	TCD14, TCD18, TCD07
physiquecount	int64	0.0%	1.0 – 1041.0 (mean 419.111)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-15

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Numeric Summary

Column	Min	Max	Mean	Median
physiquecount	1.0	1041.0	419.111	403.5

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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. 1 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 Chad 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_chad_operational_presence,
  title     = {Chad: Operational Presence},
  author    = {OCHA Chad},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/chad-operational-presence},
  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.