electricsheepafrica/africa-cote-d-ivoire-repartition-des-localites-selon-le-type-urbain-rural-rgph-494d4df6

Repartition Des Localites Selon Le Type Urbain Rural Rgph | Africa (Cote d'Ivoire DataFair)

4 rows - 1 Africa country/area - 2021 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 4 rows from Cote d'Ivoire DataFair, covering Repartition Des Localites Selon Le Type Urbain Rural Rgph. 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: Normalized CSV export exposed by the Data Fair API.

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: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	4
Countries/areas	1
First period	2021
Last period	2021
Indicators	0
Columns	21
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
CIV	4	2021	2021	Côte d'Ivoire

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.	mdvckpshoprasa4thjbwf29y:full:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	CIV
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	Côte d'Ivoire
year	int64	Observation year.	2021
type_de_localite	string	Source column from the original resource.	Localités urbaines
nombre_de_localites	int64	Source column from the original resource.	447
du_total	double	Source column from the original resource.	5.1
population	double	Source column from the original resource.	15749434.0
population_2	double	Source column from the original resource.	53.6
population_moyenne_par_localite	double	Source column from the original resource.	35234.0
source_period_start_year	int64	Start year inferred from source metadata.	2021
source_period_end_year	int64	End year inferred from source metadata.	2021
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2021
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	Agence Nationale de la statistique (ANStat)
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Répartition des localités selon le type Urbain Rural RGPH 2021
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Répartition des localités selon le type Urbain Rural RGPH 2021 CSV ex...
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	mdvckpshoprasa4thjbwf29y
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	mdvckpshoprasa4thjbwf29y:full
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.gouv.ci/data-fair/api/v1/datasets/repartition-des-locali...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	other-open
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-27T10:23:33Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-cote-d-ivoire-repartition-des-localites-selon-le-type-urbain-rural-rgph-494d4df6")
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"] == "CIV"]

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: Cote d'Ivoire DataFair
• Publisher: Agence Nationale de la statistique (ANStat)
• Portal: https://data.gouv.ci
• Resource: Répartition des localités selon le type Urbain Rural RGPH 2021 CSV export
• License: other-open
• Retrieved/generated: 2026-07-27T10:23:41Z
• Hugging Face repo: electricsheepafrica/africa-cote-d-ivoire-repartition-des-localites-selon-le-type-urbain-rural-rgph-494d4df6

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
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_cote_d_ivoire_repartition_des_localites_selon_le_type_urbain_rural_rgph_4_2021,
  title        = {Repartition Des Localites Selon Le Type Urbain Rural Rgph | Africa (Cote d'Ivoire DataFair)},
  author       = {Agence Nationale de la statistique (ANStat)},
  year         = {2021},
  url          = {https://data.gouv.ci/datasets/repartition-des-localites-selon-le-type-urbain-rural-rgph-2021},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-cote-d-ivoire-repartition-des-localites-selon-le-type-urbain-rural-rgph-494d4df6}}
}

License

Released under other-open.

Original data is published by Agence Nationale de la statistique (ANStat). 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.

---

Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.gouv.ci/datasets/repartition-des-localites-selon-le-type-urbain-rural-rgph-2021