---
license: cc-by-4.0
language:
- en
tags:
- nigeria
- africa
- real-estate
- housing
- abuja
- prices
- tabular
- web-scraping
pretty_name: Abuja Housing Prices — Groundwork Data v1
size_categories:
- n<1K
task_categories:
- tabular-regression
---

# 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 startups actually need.

Nigeria has a severe structured data gap. If you want to build something that touches how Nigerians live, rent, buy, or move — you will hit a wall. Every time. This project is fixing that.

- **Homepage:** https://www.kaggle.com/datasets/ayoolaokunlola/abuja-housing-prices-groundwork-data-v1
- **License:** CC BY 4.0
- **Version:** v1 (April 2026)

---

## Dataset Summary

| | |
|---|---|
| Listings | 481 |
| Rental listings | 250 |
| Sale listings | 231 |
| Areas covered | 16 |
| Property types | 7 |
| Price range | ₦800,000 – ₦5,000,000,000 |
| Source | PropertyPro.ng |
| Scraped | April 2026 |

---

## Data Fields

| Column | Type | Description |
|---|---|---|
| title | string | Listing headline as displayed on PropertyPro.ng |
| price_ngn | int | Listed price in Nigerian Naira. Annual rent for rental listings, asking price for sale listings |
| listing_type | string | "rent" or "sale" |
| area | string | Broad Abuja area/district. 16 unique values |
| neighbourhood | string | Sub-area within district. 17 unique values |
| address | string | Street-level address string as listed |
| bedrooms | int | Number of bedrooms. Range: 1–10 |
| bathrooms | float | Number of bathrooms. Range: 1–10. ~2% missing |
| toilets | float | Number of toilets. Range: 1–10. ~18% missing |
| property_type | string | Flat/Apartment, Detached Duplex, Terraced Duplex, Semi-Detached Duplex, Bungalow, House, Mansion |
| description | string | Note: all entries contain a generic PropertyPro safety disclaimer — not property-specific |
| pid | string | Unique PropertyPro listing ID. Use for deduplication |
| date_added | string | Date listing was first published. Format: DD-Mon-YY |
| last_updated | string | Date listing was last updated. Format: DD-Mon-YY. 3 missing |
| source_url | string | Full URL of original PropertyPro.ng listing |

---

## Key Findings

- Median annual rent across Abuja: ~₦8M. Maitama and Asokoro exceed ₦50M median.
- Median sale price: ~₦250M. Asokoro (₦1.1B) and Wuse 2 (₦950M) are the most expensive markets.
- A 3-bedroom property in Asokoro has a median sale price 13x higher than the same spec in Kubwa.
- Bedrooms and area location are the dominant price predictors.
- Flat/Apartment is the most common property type at 36% of listings.
- Baseline Random Forest models: CV R² = 0.79 (rent), 0.71 (sale).

---

## Known Limitations

- **No property size (sqm):** Not consistently listed on PropertyPro. Most significant missing feature for modelling.
- **No geo-coordinates:** Area names only, no lat/lng.
- **Single source:** v1 covers PropertyPro.ng only. NigeriaPropertyCentre added in v2.
- **Snapshot:** Single scrape from April 2026. Not a time series.
- **Description field:** Generic disclaimer text only — not useful as a feature.

---

## Usage

```python
import pandas as pd
df = pd.read_csv("groundwork_abuja_housing_v1.csv")

# Separate rent and sale
rent = df[df.listing_type == "rent"]
sale = df[df.listing_type == "sale"]

# Median price by area
print(rent.groupby("area")["price_ngn"].median().sort_values(ascending=False))
```

Full baseline model notebook available on Kaggle:
https://www.kaggle.com/datasets/ayoolaokunlola/abuja-housing-prices-groundwork-data-v1/code

---

## Citation

```
@dataset{groundworkdata2026abuja,
  author    = {Groundwork Data},
  title     = {Abuja Housing Prices v1},
  year      = {2026},
  publisher = {Kaggle},
  url       = {https://www.kaggle.com/datasets/ayoolaokunlola/abuja-housing-prices-groundwork-data-v1}
}
```

---

## About Groundwork Data

Groundwork Data is building Nigerian civic data infrastructure — scraping, cleaning, structuring, and publishing the domain-specific datasets that local engineers and researchers need to build things that actually work for Nigerian problems.

Follow on Kaggle and Hugging Face: **Groundwork Data**

Coming next: Lagos Housing Prices v1, Nigerian Schools by LGA.