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Datasets:
electricsheepafrica
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africa-ghana-five-year-summary-report-of-business-company-registration-be46ee7a

Tasks:
Tabular Classification
Tabular Regression
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
100K - 1M
Tags:
tabular
csv
africa
ghana
official-statistics
open-data
Libraries:
Datasets
pandas
Polars
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metadata 
license: cc-by-4.0
language:
  - en
task_categories:
  - tabular-classification
  - tabular-regression
multilinguality: monolingual
size_categories:
  - 100K<n<1M
tags:
  - tabular
  - csv
  - africa
  - ghana
  - official-statistics
  - open-data
pretty_name: >-
  FIVE YEAR SUMMARY REPORT OF BUSINESS/ COMPANY REGISTRATION IN GHANA | Africa
  (Ghana official open data)

FIVE YEAR SUMMARY REPORT OF BUSINESS/ COMPANY REGISTRATION IN GHANA | Africa (Ghana official open data)

131,546 rows - 1 Africa country - 2015-2016 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Ghana 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
GHA 131,546 2015 2016 Ghana

Indicators or Resource Contents

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

Schema

Column Type Description Example
source_record_id string Stable row identifier for tabular resources. dd5bc7f6-001c-4632-a860-103b67ea6381:0
country_iso3 string ISO3 country code. GHA
country_name string Country name. Ghana
business_name string Source column. BNJ ENTERPRISE
business_type string Source column. Sole Proprietor
month_of_registration string Source column. Jan
year_of_registration int64 Source column. 2015
nature_of_business string Source column. Commerce
principal_activity string Source column. GENERAL TRADING
city string Source column. CAPE COAST
region string Source column. CENTRAL
source_period_start_year Int64 First year inferred from source resource metadata. 2015
source_period_end_year Int64 Last year inferred from source resource metadata. 2016
source_period_label string Human-readable period inferred from source resource metadata. 2015-2016
source_provider string Publishing organization. Official government open data portal
source_dataset string Source package title. FIVE YEAR SUMMARY REPORT OF BUSINESS/ COMPANY REGISTRATION IN GHANA
source_resource string Source resource title. Summary reports of business/company registration 2015-2016
source_package_id string CKAN package UUID. 31627199-a44b-4b48-914a-b7950f7486df
source_resource_id string CKAN resource UUID. dd5bc7f6-001c-4632-a860-103b67ea6381
source_url string Original source resource URL. http://data.gov.gh/sites/default/files/2015_2016%20Registrations%20by%20
license_id string Source license identifier. cc-by
retrieved_at string UTC retrieval timestamp. 2026-07-18T20:11:31Z

Usage 

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-ghana-five-year-summary-report-of-business-company-registration-be46ee7a")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country 

sample_country = df[df["country_iso3"] == "GHA"]

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_ghana_five_year_summary_report_of_business_company_registration_be46ee7a_2016,
  title        = {FIVE YEAR SUMMARY REPORT OF BUSINESS/ COMPANY REGISTRATION IN GHANA | Africa (Ghana official open data)},
  author       = {Official government open data portal},
  year         = {2016},
  url          = {http://data.gov.gh/dataset/five-year-summary-report-business-company-registration-ghana-2},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-ghana-five-year-summary-report-of-business-company-registration-be46ee7a}}
}

License

Released under CC BY 4.0.

Original data (c) Official government open data portal. 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 2026-07-18 via the Electric Sheep pipeline. Source URL: http://data.gov.gh/sites/default/files/2015_2016%20Registrations%20by%20Region%2CDistrict%20and%20Sector.csv