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electricsheepafrica/africa-namibia-small-business-surveys-aggregated-data-d5a0d9ee

Small Business Surveys - Aggregated Data | Africa (Namibia official open data) 15,705 rows - 1 Africa country - 2019 - Repackaged by Electric Sheep Africa 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 Source: Small Business Surveys - Aggregated Data… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-namibia-small-business-surveys-aggregated-data-d5a0d9ee.

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Dataset Card

Small Business Surveys - Aggregated Data | Africa (Namibia official open data)

15,705 rows - 1 Africa country - 2019 - 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:

CountryRowsFirst yearLast yearName
NAM15,70520192019Namibia

Indicators or Resource Contents

  • —This source file is packaged as a normalized tabular resource.

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier for tabular resources.70ab61fd-97f6-464d-8803-91b84f68f463:0
country_iso3categoryISO3 country code.NAM
country_namecategoryCountry name.Namibia
yearInt64Observation year.2019
variablestringSource column.bus_cdt
valuestringNumeric observation value.I'm not sure
popstringSource column.overall_owner_manager
logged_iso2stringSource column.AE
mean_wfloat64Source column.0.061929057
se_wfloat64Source column.0.024771643
countint64Source column.17
question_nint64Source column.183
source_period_start_yearInt64First year inferred from source resource metadata.2019
source_period_end_yearInt64Last year inferred from source resource metadata.2019
source_period_labelcategoryHuman-readable period inferred from source resource metadata.2019
source_providercategoryPublishing organization.AI for Good at Meta
source_datasetcategorySource package title.Small Business Surveys - Aggregated Data
source_resourcecategorySource resource title.fob_2019_december_data_aggregate_weighted_smb.csv
source_package_idcategoryCKAN package UUID.8bd3d109-d33d-4349-90c4-464c9d7ccb66
source_resource_idcategoryCKAN resource UUID.70ab61fd-97f6-464d-8803-91b84f68f463
source_urlcategoryOriginal source resource URL.https://data.humdata.org/dataset/8bd3d109-d33d-4349-90c4-464c9d7ccb66/re
license_idcategorySource license identifier.cc-by
retrieved_atcategoryUTC retrieval timestamp.2026-08-30T05:38:32Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-namibia-small-business-surveys-aggregated-data-d5a0d9ee")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

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

Work with indicators

python
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

bibtex
@misc{electric_sheep_africa_africa_namibia_small_business_surveys_aggregated_data_d5a0d9ee_2019,
  title        = {Small Business Surveys - Aggregated Data | Africa (Namibia official open data)},
  author       = {AI for Good at Meta},
  year         = {2019},
  url          = {https://data.humdata.org/dataset/future-of-business-survey-aggregated-data},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-namibia-small-business-surveys-aggregated-data-d5a0d9ee}}
}

License

Released under CC BY 4.0.

Original data (c) AI for Good at Meta. 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/8bd3d109-d33d-4349-90c4-464c9d7ccb66/resource/70ab61fd-97f6-464d-8803-91b84f68f463/download/fob2019decemberdataaggregateweightedsmb.csv