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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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| 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. |
Query Danish real estate data via scripts/boliga.py.
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()
| 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 |
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
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