run2-travel-data-extraction

name	run2_travel-data-extraction
description	Extract and validate travel data from CSV/TXT databases ensuring city-specific matching and constraint compliance.

Travel Data Extraction (Improved)

Data Sources

• data/background/citySet_with_states.txt - Tab-separated city/state pairs
• data/accommodations/clean_accommodations_2022.csv - Columns: index, NAME, room type, price, minimum nights, review rate number, house_rules, maximum occupancy, city
• data/restaurants/clean_restaurant_2022.csv - Columns: index, Name, City, Cuisines, Average Cost, Aggregate Rating
• data/attractions/attractions.csv - Columns: Name, Latitude, Longitude, Address, Phone, Website, City
• data/googleDistanceMatrix/distance.csv - Columns: origin, destination, cost, duration, distance

Critical: City-Specific Validation

When searching for entities, ALWAYS verify the city column matches. Names can appear in multiple cities:

# WRONG - may match wrong city
grep "Restaurant Name" restaurants.csv
# RIGHT - verify city match
grep "Restaurant Name.*TargetCity" restaurants.csv

Pet-Friendly Accommodations

Filter: rows where house_rules does NOT contain "No pets". Also check:

• maximum_occupancy >= party size (2 for couples)
• minimum_nights <= planned stay length
• Price fits within budget

Cuisine Matching

The Cuisines field is comma-separated. Match keywords: American, Mediterranean, Chinese, Italian. Ensure all 4 cuisine types appear across the itinerary's meals.

Distance Data

• Self-driving cost column is always empty
• Duration format: "X hours Y mins" or "X mins"
• Distance format: "X,XXX km" with comma separators