travel-data-querying

name: travel-data-querying description: Querying travel planning datasets (cities, restaurants, accommodations, attractions, distances) for itinerary generation.

Travel Data Querying

Dataset Structure

All data lives under /app/data/ with these files:

Cities

• background/citySet_with_states.txt — Tab-separated: CityName\tState
• background/citySet.txt — City names only
• background/stateSet.txt — State names only

Restaurants

• restaurants/clean_restaurant_2022.csv
• Columns: index, Name, City, Cuisines, Average Cost, Aggregate Rating
• Cuisines is a comma-separated string (e.g., "Tea, Pizza, Indian, Seafood")
• Average Cost is per meal (numeric)

Accommodations

• accommodations/clean_accommodations_2022.csv
• Columns: index, NAME, room type, price, minimum nights, review rate number, house_rules, maximum occupancy, city
• house_rules contains constraints like "No pets", "No smoking", "No parties", "No children under 10", "No visitors"
• Price is per night

Attractions

• attractions/attractions.csv
• Columns: Name, Latitude, Longitude, Address, Phone, Website, City

Distances

• googleDistanceMatrix/distance.csv
• Columns: origin, destination, cost, duration, distance
• cost column is empty for driving (only populated for flights)
• Duration is human-readable (e.g., "3 hours 11 mins")
• Distance in km

Flights

• flights/clean_Flights_2022.csv — Not used when flights are excluded

Querying Patterns

Find cities in a state

grep -i "ohio" data/background/citySet_with_states.txt

Find restaurants by city and cuisine

grep -i "cleveland" data/restaurants/clean_restaurant_2022.csv | grep -i "italian"

Find pet-friendly accommodations (exclude "No pets")

grep -i "cleveland" data/accommodations/clean_accommodations_2022.csv | grep -iv "no pets"

Find driving distances between cities

grep -E "^Cleveland,Dayton," data/googleDistanceMatrix/distance.csv