electricsheepafrica/africa-cpswg-5w-august-2016

Nigeria - Child Protection 5W for the month of August 2016

Publisher: UNICEF Nigeria (inactive) · Source: HDX · License: other-pd-nr · Updated: 2024-01-30

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Abstract

Child Protection Sub-Sector working group (CPSWG) - Who is doing what, where,when and for whom (5W) – August 2016

Each row in this dataset represents subnational administrative unit observations. Temporal coverage is indicated by the startdate, enddate column(s). 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)	159
Columns	15 (0 numeric, 13 categorical, 2 datetime)
Train split	127 rows
Test split	31 rows
Geographic scope	NGA
Publisher	UNICEF Nigeria (inactive)
HDX last updated	2024-01-30

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Variables

Geographic — activity (Provision of psychosocial activities for children, support through Inter-agency case management system, Identify separated children), state (BORNO, ADAMAWA, GOMBE), lga (Maiduguri, Funakaye, Jere), statecode (NGA008, NGA002, NGA016), lgacode.

Temporal — startdate, enddate.

Identifier / Metadata — esa_source, esa_processed.

Other — sector (Protection), sub_sector (Child Protection), lead_organisation (Save the Children, UN Children fund, International Rescue Committee), implementingpartner (Center for Community Health Development, International Rescue Committee, SMWASD Borno), need_addressed (Unaccompanied and Separated Children, Psychosocial Distress and Mental Disorder, Multiple Needs) and 1 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-cpswg-5w-august-2016")
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
sector	object	0.0%	Protection
sub_sector	object	0.0%	Child Protection
lead_organisation	object	0.0%	Save the Children, UN Children fund, International Rescue Committee
implementingpartner	object	0.0%	Center for Community Health Development, International Rescue Committee, SMWASD Borno
need_addressed	object	0.0%	Unaccompanied and Separated Children, Psychosocial Distress and Mental Disorder, Multiple Needs
activity	object	0.0%	Provision of psychosocial activities for children, support through Inter-agency case management system, Identify separated children
status	object	0.0%	Ongoing, Planned and funding secured, Completed
startdate	datetime64[ns]	0.0%
enddate	datetime64[ns]	0.0%
state	object	0.0%	BORNO, ADAMAWA, GOMBE
lga	object	0.0%	Maiduguri, Funakaye, Jere
statecode	object	0.0%	NGA008, NGA002, NGA016
lgacode	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. 217 exact duplicate rows were removed. 2 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 UNICEF Nigeria (inactive) 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_cpswg_5w_august_2016,
  title     = {Nigeria - Child Protection 5W for the month of August 2016},
  author    = {UNICEF Nigeria (inactive)},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/cpswg-5w-august-2016},
  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.