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EaseMyTrip Airfare Data
Aerospace & Aviation
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Free
About
This dataset provides flight fare data collected from the EaseMyTrip website. Its primary purpose is to offer information that can assist users in making informed decisions regarding when and where to buy flight tickets. By analysing flight fare patterns over time, individuals can potentially identify optimal booking periods and achieve cost savings. Furthermore, this data serves as a valuable resource for researchers and analysts, enabling the development of more precise pricing models and facilitating studies into trends within the aviation travel industry.
Columns
- Date_of_journey: The specific date on which the flight is scheduled to depart, formatted as yyyy-mm-dd.
- Journey_day: The day of the week for the flight's departure, a categorical feature with seven distinct values.
- Airline: The name of the airline company operating the flight, a categorical feature representing nine unique airlines.
- Flight_code: The unique flight identification code for the aircraft, a categorical feature with 1405 unique codes.
- Class: The class of the flight seat, a categorical feature with four distinct values: Economy, Business, Premium Economy, and First Class.
- Source: The city from which the flight originates, a categorical feature listing seven unique cities.
- Departure: A derived categorical feature indicating the departure time, grouped into four unique time labels.
- Total_stops: The number of layovers between the origin and destination cities, a categorical feature with three distinct values, including '1-stop' and 'non-stop'.
- Arrival: A derived categorical feature indicating the arrival time, grouped into four unique time labels.
- Destination: The city where the flight lands, a categorical feature listing seven unique cities.
- Duration_in_hours: A continuous feature showing the total travel time between cities in hours.
- Days_left: A derived characteristic calculated by subtracting the journey date from the booking date.
- Fare: The target variable, representing the flight ticket price in Indian Rupees (INR), inclusive of all taxes.
Distribution
The dataset is provided in CSV format (
Cleaned_dataset.csv) and has a size of 49.15 MB. It comprises 13 columns and contains approximately 452,000 valid records.Usage
This dataset is ideal for:
- Helping individuals make smarter flight ticket purchases.
- Predicting flight fares to identify the best times for booking.
- Developing accurate pricing models for air travel.
- Conducting exploratory data analysis and data cleaning tasks.
- Performing regression analysis for price prediction.
- Studying trends and patterns within the travel industry, particularly in aviation.
Coverage
The dataset focuses on flights departing from a specific set of the top 7 busiest airports in India. The time range for the collected data spans from 16th January 2023 to 6th March 2023. It currently does not include variations in aviation fuel prices or demand and supply data, as this information is not publicly available on booking websites. Future enhancements could include additional features such as current aviation fuel prices, distance between source and destination (using longitude and latitude), an expanded number of airlines and airports, and details on flight cancellations, delays, and passenger experience quality.
License
CC0: Public Domain
Who Can Use It
- Travellers and Consumers: To inform their flight ticket purchase decisions and save money.
- Data Scientists and Machine Learning Engineers: For building and refining flight fare prediction models.
- Market Researchers and Analysts: To understand and track trends in the Indian aviation sector.
- Academics and Students: For research, case studies, and learning about time series analysis, regression, and data productisation.
Dataset Name Suggestions
- Indian Flight Fare Prediction Dataset
- EaseMyTrip Airfare Data
- India Flight Pricing Dynamics
- Aviation Fare Trends India
- Flight Ticket Data India
Attributes
Original Data Source: EaseMyTrip Airfare Data
QUALITY