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Datasets:
electricsheepafrica
/
africa-mali-global-subnational-population-statistics-bcb84504

Tasks:
Tabular Regression
Time Series Forecasting
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
100K - 1M
Tags:
tabular
csv
africa
mali
official-statistics
open-data
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
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metadata 
license: cc-by-4.0
language:
  - en
task_categories:
  - tabular-regression
  - time-series-forecasting
multilinguality: monolingual
size_categories:
  - 100K<n<1M
tags:
  - tabular
  - csv
  - africa
  - mali
  - official-statistics
  - open-data
  - population
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-00000-of-00001.parquet
pretty_name: Global - Subnational Population Statistics | Africa (Mali official open data)

Global - Subnational Population Statistics | Africa (Mali official open data)

671,091 rows - 1 Africa country - 2011-2024 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Mali as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

Geographic coverage

1 Africa country:

Country Rows First year Last year Name
MLI 671,091 2011 2024 Mali

Indicators or Resource Contents

  • global-subnational-population-statistics-age-min-ef3103d3 - Global - Subnational Population Statistics - age min
  • global-subnational-population-statistics-age-max-4a4e285b - Global - Subnational Population Statistics - age max
  • global-subnational-population-statistics-population-5029d495 - Global - Subnational Population Statistics - population

Schema

Column Type Description Example
indicator_id string Stable indicator identifier. global-subnational-population-statistics-age-min-ef3103d3
indicator_name string Human-readable indicator name. Global - Subnational Population Statistics - age min
country_iso3 string ISO3 country code. MLI
country_name string Country name. Mali
year Int64 Observation year. 2022
value float64 Numeric observation value. 0.0
unit string Measurement unit, when available. source_units_unspecified
dimension_iso3 string Source dimension. BGD
dimension_country string Source dimension. Bangladesh
dimension_adm1_pcode string Source dimension. BD10
dimension_adm1_name string Source dimension. Barisal
dimension_adm2_pcode string Source dimension. BD1004
dimension_adm2_name string Source dimension. Barguna
dimension_adm3_pcode string Source dimension. BD100409
dimension_adm3_name string Source dimension. Amtali
dimension_population_group string Source dimension. F_00_04
dimension_gender string Source dimension. f
dimension_age_range string Source dimension. 0-4
dimension_source string Source dimension. UNFPA and US Census Bureau (USCB)
dimension_contributor string Source dimension. UNFPA
source_period_start_year Int64 First year inferred from source resource metadata. ``
source_period_end_year Int64 Last year inferred from source resource metadata. ``
source_period_label string Human-readable period inferred from source resource metadata. ``
source_provider category Publishing organization. HDX
source_dataset category Source package title. Global - Subnational Population Statistics
source_resource category Source resource title. cod_population_admin3.csv
source_package_id category CKAN package UUID. 27e3d1c6-c57a-4159-85a4-adb6b7aca6b9
source_resource_id category CKAN resource UUID. 3a58aef6-7884-40fc-8a0f-5bca8886e358
source_url category Original source resource URL. https://data.humdata.org/dataset/27e3d1c6-c57a-4159-85a4-adb6b7aca6b9/re
license_id category Source license identifier. cc-by
retrieved_at category UTC retrieval timestamp. 2026-08-12T23:12:09Z

Usage 

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mali-global-subnational-population-statistics-bcb84504")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country 

sample_country = df[df["country_iso3"] == "MLI"]

Work with indicators 

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation 

@misc{electric_sheep_africa_africa_mali_global_subnational_population_statistics_bcb84504_2024,
  title        = {Global - Subnational Population Statistics | Africa (Mali official open data)},
  author       = {HDX},
  year         = {2024},
  url          = {https://data.humdata.org/dataset/cod-ps-global},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mali-global-subnational-population-statistics-bcb84504}}
}

License

Released under CC BY 4.0.

Original data (c) HDX. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

Provenance: ingested 2026-08-13 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/27e3d1c6-c57a-4159-85a4-adb6b7aca6b9/resource/3a58aef6-7884-40fc-8a0f-5bca8886e358/download/cod_population_admin3.csv