electricsheepafrica/africa-child-protection-response-monitoring-as-of-7th-may

Child protection response monitoring as of 7th May

Publisher: OCHA Mozambique · Source: HDX · License: cc-by · Updated: 2025-04-25

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Abstract

Child protection operational presence, activities and beneficiaries for Sofala and Manica Provinces at Postos level.

Each row in this dataset represents subnational administrative unit observations. Temporal coverage is indicated by the start_date column(s). Geographic scope: MOZ.

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	24 (4 numeric, 19 categorical, 1 datetime)
Train split	127 rows
Test split	31 rows
Geographic scope	MOZ
Publisher	OCHA Mozambique
HDX last updated	2025-04-25

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Variables

Geographic — leading_organization_type (ONGs internacionais, Agências das Nações Unidas, #org +lead +type +name), implementing_organization_type (ONGs internacionais, ONGs nacionais, Agências das Nações Unidas), activity (3.4. Organization of activities in Child Friendly Spaces and in other socio-recreational centers/Organização de actividades em Espaços Amigos da Criança e outros centros de socio-recreação, 3.3. Establishment of Child Friendly Spaces and in other recreational centers/Estabelecimento de Espaços Amigos da Criança e outros centros de socio-recreação, 3.1. Capacity strenghthening of families, political and religious leaders/Fortalecimento da capacidade de famílias, líderes políticos e religiosos), province (Sofala, Manica, Zambezia), province_pcode (MZ09, MZ04, MZ11) and 6 others.

Temporal — start_date.

Identifier / Metadata — postos_pcode, esa_source, esa_processed.

Other — leading_organization (United Nation's Children Fund, Plan International, World Vision International), implementing_organization (International Child Developing Programme, Plan International, World Vision International), cluster_aor (Proteção da criancia, #sector +cluster +name, proteção da criancia), response_domain (3. Psychosocial support services/Serviços de Apoio Psicosocial, 2. Protective communities/Comunidades protectivas, 1. Case management/Gestão de Casos), indicator (3.4.1. # of girls and boys participating in psychosocial activities through CFS/# de meninas e meninos participando em actividades de apoio psicosocial atravéz de CFS, 3.3.1. # of CFS or recreational centers established/# de CFS o centros de recreação estabelecidos , 3.1.1. # of women and men non-child protection workers trained on CP approaches/# de mulheres e homens não funcionarios e proteção da criança treinados na matéria de Protecção da Criança) and 4 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-child-protection-response-monitoring-as-of-7th-may")
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
leading_organization	object	0.0%	United Nation's Children Fund, Plan International, World Vision International
leading_organization_type	object	0.0%	ONGs internacionais, Agências das Nações Unidas, #org +lead +type +name
implementing_organization	object	0.0%	International Child Developing Programme, Plan International, World Vision International
implementing_organization_type	object	0.6%	ONGs internacionais, ONGs nacionais, Agências das Nações Unidas
cluster_aor	object	0.0%	Proteção da criancia, #sector +cluster +name, proteção da criancia
response_domain	object	3.8%	3. Psychosocial support services/Serviços de Apoio Psicosocial, 2. Protective communities/Comunidades protectivas, 1. Case management/Gestão de Casos
activity	object	3.8%	3.4. Organization of activities in Child Friendly Spaces and in other socio-recreational centers/Organização de actividades em Espaços Amigos da Criança e outros centros de socio-recreação, 3.3. Establishment of Child Friendly Spaces and in other recreational centers/Estabelecimento de Espaços Amigos da Criança e outros centros de socio-recreação, 3.1. Capacity strenghthening of families, political and religious leaders/Fortalecimento da capacidade de famílias, líderes políticos e religiosos
indicator	object	3.8%	3.4.1. # of girls and boys participating in psychosocial activities through CFS/# de meninas e meninos participando em actividades de apoio psicosocial atravéz de CFS, 3.3.1. # of CFS or recreational centers established/# de CFS o centros de recreação estabelecidos , 3.1.1. # of women and men non-child protection workers trained on CP approaches/# de mulheres e homens não funcionarios e proteção da criança treinados na matéria de Protecção da Criança
province	object	0.0%	Sofala, Manica, Zambezia
province_pcode	object	0.0%	MZ09, MZ04, MZ11
district	object	0.0%
district_pcode	object	0.0%
postos	object	2.5%
postos_pcode	object	5.7%
location	object	22.0%
type_of_beneficiaries	object	25.2%
children_targeted	float64	67.3%	22.0 – 2500.0 (mean 634.7885)
boys_reached	float64	64.2%	0.0 – 471.0 (mean 116.193)
girls_reached	float64	62.9%	1.0 – 606.0 (mean 134.4407)
other_units_cfs_ccpc_etc	float64	72.3%	1.0 – 5.0 (mean 1.6136)
activity_status	object	18.9%
start_date	datetime64[ns]	70.4%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
children_targeted	22.0	2500.0	634.7885	350.0
boys_reached	0.0	471.0	116.193	79.0
girls_reached	1.0	606.0	134.4407	86.0
other_units_cfs_ccpc_etc	1.0	5.0	1.6136	1.0

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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. 8 column(s) with >80% missing values were removed: donor, output, modality, adults_targeted, children_with_disabilities_reached, men_reached.... 7 exact duplicate rows were removed. 5 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 Mozambique and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• The following columns have >20% missing values and should be treated with caution in modelling: location, type_of_beneficiaries, children_targeted, boys_reached, girls_reached, other_units_cfs_ccpc_etc, start_date.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_child_protection_response_monitoring_as_of_7th_may,
  title     = {Child protection response monitoring as of 7th May},
  author    = {OCHA Mozambique},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/child-protection-response-monitoring-as-of-7th-may},
  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.