Datasets:

electricsheepafrica
/

africa-ghana-2018-2019-business-and-company-registration-data-55f332af

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: >-
  2018 - 2019 Business and Company registration data | Africa (Ghana official
  open data)

2018 - 2019 Business and Company registration data | Africa (Ghana official open data)

113,001 rows - 1 Africa country - 2018-2019 - Repackaged by Electric Sheep Africa

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

Source: 2018 - 2019 Business and Company registration data
Publisher: Official government open data portal
Resource: 2018 - 2019 Business and Company registration data
Format: CSV
License: CC BY 4.0
Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
`GHA`	113,001	2018	2019	`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.	`35079484-3dd0-4419-94e1-a6ef7d292fdd:0`
`country_iso3`	`string`	ISO3 country code.	`GHA`
`country_name`	`string`	Country name.	`Ghana`
`businessname`	`string`	Source column.	`QUAJOES ENTERPRISE`
`businesstype`	`string`	Source column.	`Sole Proprietor`
`monthofregistration`	`string`	Source column.	`Jan`
`registrationyear`	`float64`	Source column.	`2018.0`
`nature_of_business`	`string`	Source column.	`Commerce`
`principal_activity`	`string`	Source column.	`1. SALE OF BUILDING MATERIALS 2. SERVICING OF HEAVY DUTY EQUIPMENTS 3. S`
`city`	`string`	Source column.	`TARKWA`
`region`	`string`	Source column.	`WESTERN`
`source_period_start_year`	`Int64`	First year inferred from source resource metadata.	`2018`
`source_period_end_year`	`Int64`	Last year inferred from source resource metadata.	`2019`
`source_period_label`	`string`	Human-readable period inferred from source resource metadata.	`2018-2019`
`source_provider`	`string`	Publishing organization.	`Official government open data portal`
`source_dataset`	`string`	Source package title.	`2018 - 2019 Business and Company registration data`
`source_resource`	`string`	Source resource title.	`2018 - 2019 Business and Company registration data`
`source_package_id`	`string`	CKAN package UUID.	`5a31280f-5e6c-4983-9690-8b29d5d914b5`
`source_resource_id`	`string`	CKAN resource UUID.	`35079484-3dd0-4419-94e1-a6ef7d292fdd`
`source_url`	`string`	Original source resource URL.	`http://data.gov.gh/sites/default/files/2018_2019%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-2018-2019-business-and-company-registration-data-55f332af")
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_2018_2019_business_and_company_registration_data_55f332af_2019,
  title        = {2018 - 2019 Business and Company registration data | Africa (Ghana official open data)},
  author       = {Official government open data portal},
  year         = {2019},
  url          = {http://data.gov.gh/dataset/2018-2019-business-and-company-registration-data},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-ghana-2018-2019-business-and-company-registration-data-55f332af}}
}

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/2018_2019%20Registrations%20by%20Region%2CDistrict%20and%20Sector.csv