ddecosmo/HW1_Tabular_Dataset

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This dataset covers 30 flights leaving Pittsburgh International Airport between 9/7 and 9/27. It includes information on the airline, weekday, flight time, layovers, days from departure, and price

Dataset Details

Dataset Description

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• Curated by: Carnegie Mellon University: 24-679
• Shared by [optional]: Devin DeCosmo
• Language(s) (NLP): English
• License: MIT

Dataset Sources [optional]

• Repository: {{ repo | default("[More Information Needed]", true)}}

Uses

The main use was to train tabular machine learning models to predict the price of tickets based on the outlined features.

Direct Use

The direct use would be price prediction for airline flights.

Out-of-Scope Use

This could be used to predict other features or future prices, locations, or airlines in Pittsburgh.

Dataset Structure

This dataset is in a tabular format with features Airline, Destination, Day of the Week, Days from Departure, Flight_Time_Minutes, and Price

The two splits are original and augmented The original has 30 rows. The augmented has 300rows.

Dataset Creation

Curation Rationale

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Source Data

Source data is from Google Flights

Data Collection and Processing

Data for this was collected directly through Google Flights then tabulated by Google Gemini

Who are the source data producers?

Data was initially produced by Google Flights.

Bias, Risks, and Limitations

This is a very small data set and will likely have issues with training and fitting, especially for specific regression problems surrounding price.

Recommendations

This dataset probably has limited accuracy as a first draft but may be useful for learning how to train tabular models.