electricsheepafrica/africa-mauritius-number-of-reported-cases-registered-at-the-child-developme-167b4301

Number of Reported Cases Registered At the Child Developme | Africa (MDPA)

47 rows - 1 Africa country/area - 2008-2019 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 47 rows from MDPA, covering Number of Reported Cases Registered At the Child Developme. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Labour and workforce datasets help analysts study employment, participation, skills, sectoral structure, and the movement of people through work and livelihoods.

Source-provided context: The data shows number of reported cases registered at the Child Development Unit (CDU) by nature of problem & year, Island of Mauritius for the year 2008 - 2019

How To Read This Dataset

• One row means: one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
• Primary geography column: country_iso3.
• Best time column: not detected.
• Time coverage basis: source metadata.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	47
Countries/areas	1
First period	2008
Last period	2019
Indicators	0
Columns	52
Source format	XLSX

Geographic Coverage

Top areas shown below, sorted by row count when available:

Area	Rows	First year	Last year	Name
MU	47	2008	2019	Mauritius

Indicators, Variables, Or Resource Contents

• This repo preserves one source tabular resource with its usable columns kept together.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa engineering.	672ab9a9-4869-4a74-b6ef-481891a2c7e6:table-4a:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	MU
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	Mauritius
source_sheet	string	Source column from the original resource.	Table 4a
burnt_by_both_step_parents	string	Source column from the original resource.	Burnt by others
column	string	Source column from the original resource.	-
column_2	double	Source column from the original resource.	``
column_3	double	Source column from the original resource.	``
column_4	string	Source column from the original resource.	5
column_5	string	Source column from the original resource.	6
column_6	double	Source column from the original resource.	11.0
column_7	string	Source column from the original resource.	4
column_8	double	Source column from the original resource.	4.0
column_9	double	Source column from the original resource.	8.0
column_10	string	Source column from the original resource.	4
column_11	double	Source column from the original resource.	5.0
column_12	double	Source column from the original resource.	9.0
column_13	string	Source column from the original resource.	4
column_14	double	Source column from the original resource.	3.0
column_15	double	Source column from the original resource.	7.0
column_16	string	Source column from the original resource.	4
column_17	double	Source column from the original resource.	2.0
column_18	double	Source column from the original resource.	6.0
column_19	string	Source column from the original resource.	2
column_20	double	Source column from the original resource.	7.0
column_21	double	Source column from the original resource.	9.0
column_22	string	Source column from the original resource.	4
column_23	string	Source column from the original resource.	4
column_24	string	Source column from the original resource.	8
column_25	string	Source column from the original resource.	3
column_26	double	Source column from the original resource.	1.0
column_27	double	Source column from the original resource.	4.0
column_28	string	Source column from the original resource.	2
column_29	string	Source column from the original resource.	3
column_30	double	Source column from the original resource.	5.0
column_31	string	Source column from the original resource.	3
column_32	double	Source column from the original resource.	5.0
column_33	double	Source column from the original resource.	8.0
column_34	string	Source column from the original resource.	1
column_35	double	Source column from the original resource.	4.0
column_36	double	Source column from the original resource.	5.0
source_period_start_year	int64	Start year inferred from source metadata.	2008
source_period_end_year	int64	End year inferred from source metadata.	2019
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2008-2019
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	MDPA
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Number of reported cases registered at the Child Development Unit
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Source_file_0.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	8794f9ec-9a80-4f09-8c33-2d4f36fecc15
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	672ab9a9-4869-4a74-b6ef-481891a2c7e6
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/8794f9ec-9a80-4f09-8c33-2d4f36fecc15/r...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	CC-BY-SA-4.0
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-08T16:26:20Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-number-of-reported-cases-registered-at-the-child-developme-167b4301")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

print(df.info())
print(df.head())

Filter By Geography

if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "MU"]

Time-Series Pattern

if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

• No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
• Missing values are preserved rather than silently imputed.
• Column names are standardized for machine use; source meanings are preserved where known.
• Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

• Source: MDPA
• Publisher: MDPA
• Portal: https://data.govmu.org
• Resource: Source_file_0.xlsx
• License: CC BY-SA 4.0
• Retrieved/generated: 2026-08-08T17:12:02Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-number-of-reported-cases-registered-at-the-child-developme-167b4301

Transformations Applied

• Converted the source table to Parquet for efficient analytics and ML workflows.
• Added or preserved source provenance columns where available.
• Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
• Preserved source-reported values without analytical imputation.

Suggested Analyses

• Track workforce composition over time
• Compare employment patterns across groups
• Join with education, population, and sector data
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_mauritius_number_of_reported_cases_registered_at_the_child_developme_167b_2019,
  title        = {Number of Reported Cases Registered At the Child Developme | Africa (MDPA)},
  author       = {MDPA},
  year         = {2019},
  url          = {https://data.govmu.org/dataset/number-reported-cases-registered-child-development-unit},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-number-of-reported-cases-registered-at-the-child-developme-167b4301}}
}

License

Released under CC BY-SA 4.0.

Original data is published by MDPA. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

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Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/number-reported-cases-registered-child-development-unit