Hugging Face's logo

Datasets:
electricsheepafrica
/
africa-namibia-namibia-languages-1b71e7aa

Tasks:
Tabular Regression
Time Series Forecasting
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
< 1K
Tags:
tabular
csv
africa
namibia
official-statistics
open-data
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
 Community
africa-namibia-namibia-languages-1b71e7aa / README.md
Kossiesa's picture
Kossiesa
Upload dataset folder
f5a57db verified
preview code
|
Raw
History Blame Contribute Delete
6.8 kB
metadata 
license: cc-by-sa-4.0
language:
  - en
task_categories:
  - tabular-regression
  - time-series-forecasting
multilinguality: monolingual
size_categories:
  - n<1K
tags:
  - tabular
  - csv
  - africa
  - namibia
  - official-statistics
  - open-data
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-00000-of-00001.parquet
pretty_name: 'Namibia: Languages | Africa (Namibia official open data)'

Namibia: Languages | Africa (Namibia official open data)

404 rows - 1 Africa country - 2015 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Namibia 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
NAM 404 2015 2015 Namibia

Indicators or Resource Contents

  • namibia-languages-location-level-d7d3bbd2 - Namibia: Languages - location level
  • namibia-languages-language-rank-95faabb7 - Namibia: Languages - language rank
  • namibia-languages-proportion-value-8f7d1278 - Namibia: Languages - proportion value
  • namibia-languages-reliability-score-3be58fe3 - Namibia: Languages - reliability score

Schema

Column Type Description Example
indicator_id string Stable indicator identifier. namibia-languages-location-level-d7d3bbd2
indicator_name string Human-readable indicator name. Namibia: Languages - location level
country_iso3 string ISO3 country code. NAM
country_name string Country name. Namibia
date string Observation date. 2015-09-24
year Int64 Observation year. 2015
value float64 Numeric observation value. 1.0
unit string Measurement unit, when available. source_units_unspecified
dimension_location_code string Source dimension. NA04
dimension_location_name string Source dimension. Karas
dimension_language_code string Source dimension. here1253
dimension_language_name string Source dimension. Herero
dimension_dataset_name string Source dimension. Namibia Round 6 data (2014)
dimension_url string Source dimension. https://www.afrobarometer.org/wp-content/uploads/2022/02/nam_r6_data.sav
dimension_source string Source dimension. AfroBarometer
dimension_date_creation string Source dimension. 01-29-2025 13:14:38
dimension_representivity_rating string Source dimension. moderate
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. CLEAR Global (previously Translators without Borders)
source_dataset category Source package title. Namibia: Languages
source_resource category Source resource title. clearglobal_language_use_NAM_admin1.csv
source_package_id category CKAN package UUID. 48739309-96ad-455b-afb6-e152f9eabe39
source_resource_id category CKAN resource UUID. 4d286ab9-2db6-41cf-8020-0061fe99cc7a
source_url category Original source resource URL. https://data.humdata.org/dataset/48739309-96ad-455b-afb6-e152f9eabe39/re
license_id category Source license identifier. cc-by-sa
retrieved_at category UTC retrieval timestamp. 2026-08-30T05:38:32Z

Usage 

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-namibia-namibia-languages-1b71e7aa")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country 

sample_country = df[df["country_iso3"] == "NAM"]

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_namibia_namibia_languages_1b71e7aa_2015,
  title        = {Namibia: Languages | Africa (Namibia official open data)},
  author       = {CLEAR Global (previously Translators without Borders)},
  year         = {2015},
  url          = {https://data.humdata.org/dataset/namibia-languages},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-namibia-namibia-languages-1b71e7aa}}
}

License

Released under CC BY-SA.

Original data (c) CLEAR Global (previously Translators without Borders). 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 2026-08-30 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/48739309-96ad-455b-afb6-e152f9eabe39/resource/4d286ab9-2db6-41cf-8020-0061fe99cc7a/download/clearglobal_language_use_nam_admin1.csv