egupta/atl-intl-flight-data-sql-db

International Round-Trip Flight Prices Dataset (SQLite)

This project collects international round-trip flight pricing data over a defined date range and duration from Atlanta (ATL) to 9 international destinations. It saves this structured flight information to a SQLite database and enables flexible downstream querying and visualization. Each entry represents a real flight quote retrieved from a travel search API under fixed conditions. The data is structured, time-stamped, and ready for time-series, pricing trend, or travel modeling tasks.

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Contents

• dataDB_intl.db: SQLite3 database containing the full dataset

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Dataset Summary

• Trip Type: Round-trip international flights
• Traveler Type: 1 adult, economy class, no checked bags, 1 carry-on bag
• Directionality: Both outbound and return flights captured
• Data Granularity: Each row = 1 flight option on a specific round-trip itinerary
• Size: Millions of records across many city pairs and durations

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How the Dataset Was Created

The code for generating this dataset is in https://github.com/EkanshGupta/flights The dataset was programmatically generated using a flight search wrapper over an airfare API over a period of months. The pipeline involves itinerary generation, flight search, parsing, and storage.

Parameters Used

• City Pairs:

  • ATL ↔ LHR (London)
  • ATL ↔ CDG (Paris)
  • ATL ↔ FCO (Rome)
  • ATL ↔ FRA (Frankfurt)
  • ATL ↔ DEL (New Delhi)
  • ATL ↔ ATH (Athens)
  • ATL ↔ CUN (Cancun)
  • ATL ↔ HND (Tokyo)
  • ATL ↔ CAI (Cairo)

• Trip Durations:

  • 5 days, 7 days, 9 days, 10 days, and other combinations (dependent on city)

• Date Range:

  • Departure: 100 days randomly sampled from 1 to 365 days in the future
  • Return: Departure date + specified duration

• Number of Itineraries:

  • All the itineraries returned by google flights are recorded

• Passenger Settings:

  • Adults: 1
  • Children / Infants: 0
  • Bags: 1 carry-on
  • Seat: Economy

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Database Schema

The SQLite database contains one table: data_table

Column	Type	Description
id	INTEGER PRIMARY KEY	Unique row ID
origin	TEXT	IATA code for the departure airport (e.g., ATL)
destination	TEXT	IATA code for the return airport (e.g., LON)
name	TEXT	Airline name (may include multiple airlines for stopovers)
days	INTEGER	Total duration of the round-trip (e.g., 7)
price	TEXT	Total round-trip price as string (e.g., "$728")
today	TEXT	Date when the query was made (YYYY-MM-DD)
days_ahead	INTEGER	Number of days between the query date and the departure date
flight_duration	TEXT	Duration of the outbound flight (e.g., "8h 45m")
flight_depart	TEXT	Departure time of outbound flight (e.g., "17:10")
flight_arrive	TEXT	Arrival time of outbound flight (e.g., "08:25")
stops	TEXT	Number of stops in the outbound flight (e.g., "1")
stops_info	TEXT	Description of layovers and stop details (e.g., "1 stop via JFK")
departure_date	TEXT	Date of departure for outbound flight (YYYY-MM-DD)

Note: Return flight times are not included but are implicit in the duration and round-trip structure.

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How to Load and Use

import sqlite3
import pandas as pd

# Load into DataFrame
conn = sqlite3.connect("dataDB_intl.db")
df = pd.read_sql_query("SELECT * FROM data_table", conn)
conn.close()

print(df.head())