electricsheepafrica/africa-chad-chad-gender-d818b3bb

Chad Gender | Africa (World Bank Group)

4,366 rows - 1 Africa country/area - 1960-2025 - 1 indicator - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 4,366 rows from World Bank Group, covering Chad Gender. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Demographic datasets help analysts understand population structure, household conditions, migration, gender, age, and settlement patterns.

Source-provided context: csv containing Gender indicators Indicators: Access to anti-retroviral drugs, Adjusted net enrollment rate, Adolescent fertility rate, Age at first marriage, Age population, Births attended by skilled health staff, Children in employment, Children out of school, Condom use, Contraceptive prevalence, Contributing family workers, Decision maker about Visits to her family or relatives, Decision maker about a woman's own health care, Decision maker about a woman's visits to her family or relatives, Decision maker about major household purchases, Demand for family planning satisfied by any methods, Educational attainment, Employers, Employment in agriculture, Employment in industry, Employment in services, Employment to population ratio, Female headed households, Female migrants, Fertility rate, Firms with female participation in ownership, Firms with female top manager, Gross intake ratio in first grade of primary education, Households with water 30 minutes or longer away round trip.

How To Read This Dataset

• One row means: one indicator observation for one geography, time period, and optional source dimensions.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3, year, indicator_id.

Coverage

Dimension	Value
Rows	4,366
Countries/areas	1
First period	1960
Last period	2025
Indicators	1
Columns	22
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
TCD	4,366	1960	2025	Chad

Indicators, Variables, Or Resource Contents

• chad-gender-170c1be0 - Chad - Gender(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	chad-gender-170c1be0
indicator_name	string	Human-readable indicator name.	Chad - Gender
country_iso3	string	ISO3 country or area code.	TCD
country_name	string	Country or area name.	Chad
year	int64	Observation year.	2023
value	double	Numeric observation value.	8.512759209
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_country_name	string	Source dimension retained during long-form normalization.	Chad
dimension_country_iso3	string	Source dimension retained during long-form normalization.	TCD
dimension_indicator_name	string	Source dimension retained during long-form normalization.	Firms with female top manager (% of firms)
dimension_indicator_code	string	Source dimension retained during long-form normalization.	IC.FRM.FEMM.ZS
source_period_start_year	int64	Start year inferred from source metadata.	2015
source_period_end_year	int64	End year inferred from source metadata.	2023
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2015-2023
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	World Bank Group
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Chad - Gender
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Gender Indicators for Chad
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	1e632548-db8f-4040-bd20-3308d2ce92f9
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	dc253a20-a3fd-4447-9b57-dbddbcdb847c
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/1e632548-db8f-4040-bd20-3308d2ce92f9...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-10T22:51:43Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-chad-chad-gender-d818b3bb")
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"] == "TCD"]

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

• Canonical time field: year.
• 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: World Bank Group
• Publisher: World Bank Group
• Portal: https://data.humdata.org
• Resource: Gender Indicators for Chad
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T23:00:34Z
• Hugging Face repo: electricsheepafrica/africa-chad-chad-gender-d818b3bb

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

• Build demographic profiles
• Normalize indicators per capita
• Join with service-delivery datasets
• Build time-series views and period-over-period comparisons
• Pivot to geography x period or indicator x period matrices
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_chad_chad_gender_d818b3bb_2025,
  title        = {Chad Gender | Africa (World Bank Group)},
  author       = {World Bank Group},
  year         = {2025},
  url          = {https://data.humdata.org/dataset/world-bank-gender-indicators-for-chad},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-chad-chad-gender-d818b3bb}}
}

License

Released under CC BY 4.0.

Original data is published by World Bank Group. 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.humdata.org/dataset/world-bank-gender-indicators-for-chad