name: boliga-api description: 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.
Boliga API
Query Danish real estate data via scripts/boliga.py.
Usage
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