electricsheepafrica/africa-lake-chad-basin-fts-appeal-data

Lake Chad Basin FTS Appeal Data

Publisher: OCHA Financial Tracking System (FTS) · Source: HDX · License: cc-by-igo · Updated: 2025-04-25

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Abstract

Contains data from OCHA's Financial Tracking Service on the financial requirements and current funding levels for appeals in the Lake Chad Basin crisis countries. Data is encoded as utf-8. The second row of the CSV contains HXL tags.

Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the startdate, enddate column(s). Geographic scope: CMR, TCD, NER, NGA.

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

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Dataset Characteristics

Domain	Conflict and security
Unit of observation	Country-level aggregates
Rows (total)	38
Columns	12 (5 numeric, 5 categorical, 2 datetime)
Train split	30 rows
Test split	7 rows
Geographic scope	CMR, TCD, NER, NGA
Publisher	OCHA Financial Tracking System (FTS)
HDX last updated	2025-04-25

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Variables

Geographic — country (Chad, Niger, Nigeria), year (range 2004.0–2017.0).

Temporal — startdate, enddate.

Outcome / Measurement — totalfunding (range 261506.0–314054921.0), percentfunded (range 0.0–83.0).

Identifier / Metadata — id (range 154.0–537.0), name (West Africa 2010, Niger 2015, Chad 2015), code (CXWAF10, HNER15, HTCD15), esa_source (HDX), esa_processed (2026-04-14).

Other — revisedrequirements (range 49759871.0–1054431494.0).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-lake-chad-basin-fts-appeal-data")
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
country	object	0.0%	Chad, Niger, Nigeria
id	float64	2.6%	154.0 – 537.0 (mean 370.8108)
name	object	0.0%	West Africa 2010, Niger 2015, Chad 2015
code	object	0.0%	CXWAF10, HNER15, HTCD15
startdate	datetime64[ns]	2.6%
enddate	datetime64[ns]	2.6%
year	float64	2.6%	2004.0 – 2017.0 (mean 2011.6757)
revisedrequirements	float64	2.6%	49759871.0 – 1054431494.0 (mean 384253265.1892)
totalfunding	float64	2.6%	261506.0 – 314054921.0 (mean 148997037.3784)
percentfunded	float64	2.6%	0.0 – 83.0 (mean 43.027)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-14

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Numeric Summary

Column	Min	Max	Mean	Median
id	154.0	537.0	370.8108	379.0
year	2004.0	2017.0	2011.6757	2012.0
revisedrequirements	49759871.0	1054431494.0	384253265.1892	355277959.0
totalfunding	261506.0	314054921.0	148997037.3784	137779374.0
percentfunded	0.0	83.0	43.027	52.0

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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. 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 OCHA Financial Tracking System (FTS) and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• This dataset spans 4 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_lake_chad_basin_fts_appeal_data,
  title     = {Lake Chad Basin FTS Appeal Data},
  author    = {OCHA Financial Tracking System (FTS)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/lake-chad-basin-fts-appeal-data},
  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.