electricsheepafrica/africa-nigeria-child-protection-5w-for-month-of-june-2016

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

Publisher: UNICEF Nigeria (inactive) · Source: HDX · License: cc-by · Updated: 2024-01-30

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Abstract

Nigeria, Child Protection 5W for month of June 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)	140
Columns	13 (0 numeric, 11 categorical, 2 datetime)
Train split	112 rows
Test split	28 rows
Geographic scope	NGA
Publisher	UNICEF Nigeria (inactive)
HDX last updated	2024-01-30

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Variables

Geographic — activity (Provide psychosocial activities for children in Child Friendly Spaces /child clubs, Identify separated children, Identify unaccompanied children), lga (Maiduguri, Yola south, Jere), statecode (NGA008, NGA002, NGA016), lgacode (NGA008021, NGA002021, NGA008013).

Temporal — startdate, enddate.

Identifier / Metadata — esa_source (HDX), esa_processed.

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

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-nigeria-child-protection-5w-for-month-of-june-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
subsector	object	0.0%	Child Protection
leadorganisation	object	0.0%	International Rescue Committee, Save the Children, UN Children fund
implementingpartner	object	0.0%	International Rescue Committee, Center for Community Health Development, SMWASD Borno
needaddressed	object	0.0%	Unaccompanied and Separated Children, Psychosocial Distress and Mental Disorder, Multiple Needs
activity	object	0.0%	Provide psychosocial activities for children in Child Friendly Spaces /child clubs, Identify separated children, Identify unaccompanied children
startdate	datetime64[ns]	0.0%
enddate	datetime64[ns]	0.0%
lga	object	0.0%	Maiduguri, Yola south, Jere
statecode	object	0.0%	NGA008, NGA002, NGA016
lgacode	object	0.0%	NGA008021, NGA002021, NGA008013
esa_source	object	0.0%	HDX
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. 214 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_nigeria_child_protection_5w_for_month_of_june_2016,
  title     = {Nigeria - Child Protection 5W for the month of June 2016},
  author    = {UNICEF Nigeria (inactive)},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/nigeria-child-protection-5w-for-month-of-june-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.