2018 U.S. Domestic Airline Flights with Ticket Prices, 9 Million Rows

Over 9 million rows of U.S. domestic flight data from 2018, originally sourced from the Bureau of Transportation Statistics and refined by a data science student for a price prediction project. The dataset includes 13 columns covering origin, destination, miles flown, airline, and price per ticket. It aggregates data from all four quarters of 2018, derived from an original source of over 27 million rows.

Use Cases

• Predicting flight ticket prices based on features like origin, destination, miles, and airline.
• Analyzing airline market share and pricing strategies across different U.S. states and territories.
• Modeling travel demand and ticket purchase volumes across different quarters of 2018.
• Studying the relationship between flight distance (miles) and ticket price for domestic routes.

Strengths

• Contains over 9 million rows of flight data, providing substantial volume for analysis.
• Includes a clear target variable (PricePerTicket) for supervised learning tasks.
• Data covers all four quarters of 2018, offering a full year of temporal coverage.
• Origin and destination are encoded with both city names and standardized World Area Codes for geographic analysis.

Limitations

• Row count for the final dataset is an estimate ('9M+'), not a precise figure.
• Documentation is informal and references external personal pages (GitHub, portfolio) for full details.
• Data is from 2018 and may not reflect current airline pricing or market conditions.

Provenance

Source

Bureau of Transportation Statistics, processed by an individual data science student.

Collection Method

Downloaded and aggregated from Q1-Q4 2018 data, then filtered and renamed columns.

Time Range

2018 (all four quarters).

Freshness

Data is from 2018; last update date is unknown.

Geography

United States, including contiguous states, Alaska, Hawaii, and territories.