boliga-api

Query Danish real estate data from Boliga.dk as pandas DataFrames. Use when the user asks about Danish property prices, real estate searches, market statistics, or housing analysis in Denmark.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/boliga-api

SKILL.md

Boliga API

Query Danish real estate data via scripts/boliga.py.

Usage

python

import sys
sys.path.insert(0, '<skill-path>/scripts')
from boliga import get_properties, Municipality, PropertyType, SortOrder

# Search properties
df = get_properties(
    municipality=Municipality.ROSKILDE,
    property_type=PropertyType.TERRACED,
    price_max=5000000
)

# Analyze with pandas
avg_sqm = df['sqm_price'].mean()
df.groupby('zip_code')['price'].median()

Functions

Function	Returns	Description
`get_properties(...)`	DataFrame	Active listings with filters
`get_sold_properties(...)`	DataFrame	Historical sales
`get_estate_details(id)`	dict	Property details
`get_property_history(id)`	DataFrame	Property sale history
`get_market_statistics()`	dict	National price trends
`search_location(query)`	DataFrame	Location autocomplete
`get_new_construction(...)`	DataFrame	New construction projects

Key Parameters

Municipalities: Municipality.COPENHAGEN, ROSKILDE, AARHUS, ODENSE, FREDERIKSBERG, GENTOFTE

Property types: PropertyType.VILLA, TERRACED, APARTMENT, HOLIDAY, COOPERATIVE, FARM

Sort: SortOrder.PRICE_ASC, PRICE_DESC, SQM_PRICE_ASC, DAYS_FOR_SALE_ASC

DataFrame Columns

get_properties() returns: id, street, city, zip_code, price, sqm_price, size, rooms, build_year, property_type, days_for_sale, lot_size, energy_class, lat, lon, views