Dataset

abuja-housing-prices-v1

Abuja Housing Prices — Groundwork Data v1 Dataset Description This is the first public, structured dataset of Abuja residential property prices — covering both rental and sale listings across 16 areas of Nigeria's Federal Capital Territory. Collected by Groundwork Data, a Nigerian civic data project building the structured, domain-specific datasets that Nigerian ML engineers, researchers, and star

Open on Hugging Face

Data preview

Subset

Loading preview...

Dataset card

Abuja Housing Prices v1 is a small tabular dataset of residential rental and sale listings across 16 areas of Nigeria's Federal Capital Territory, published by Groundwork Data on Kaggle. It is offered under a CC BY 4.0 license and totals 481 rows, making it a baseline rather than an ongoing feed.

What this dataset contains

The file groundwork_abuja_housing_v1.csv holds 481 property listings drawn from public postings, each tagged as either "rent" or "sale" in the listing_type column. The price_ngn field is an integer price in Nigerian naira, and area enumerates 16 districts within the FCT, with neighbourhood, bedrooms, bathrooms, toilets, and property_type giving finer property detail. A free-text description and a source_url complete each row.

Structure and fields

Schema columns are title, price_ngn, listing_type, area, neighbourhood, address, bedrooms, bathrooms, toilets, property_type, description, pid, date_added, last_updated, and source_url, mixing string, int64, and float64 dtypes. Datetime fields are stored as strings, and pid serves as a listing identifier. The single split is a train set of 481 rows, with no separate test partition.

How analysts use it

The dataset is suited to tabular regression on price_ngn and simple groupwise comparisons, for example median prices by area or by listing_type. Investors and fund managers covering Nigerian real estate could use it as a reference sample of asking-price levels across Abuja districts, though its small size and one-off scrape limit any claim of representativeness. It is best treated as a teaching or prototyping resource rather than a live market signal.

Documentation & references 1