Dataset

airline-otp-data

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The airline-otp-data dataset is a large-scale, public-style tabular repository of U.S. domestic flight records covering on-time performance, delay attribution and cancellation outcomes. Published on Hugging Face under an unstated license, it contains roughly 30 million rows in CSV format and is aimed at analysts working with airline operations data.

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What this dataset contains

Each row represents a single flight leg with operational timestamps and delay causes. Fields cover the carrier, aircraft TailNumber, FlightNumber, Origin and Dest airports, scheduled versus actual departure and arrival times, DepDelay and ArrDelay in minutes, and flags for Cancelled and Diverted status. The dataset also separates delay minutes by cause through LateAircraftDelay, CarrierDelay, WeatherDelay, NASDelay and SecurityDelay, alongside flown Distance.

Structure and fields

The data is delivered as a single train split of 30,292,120 rows in CSV. Identifiers such as FlightDate, Carrier, TailNumber, Origin and Dest are stored as strings, while time-of-day columns like SchedDep and SchedArr are integer-formatted HHMM values, and timestamps with minute resolution (ActualDep, ActualArr) appear as floats. Delay magnitudes, Distance, and the cause-specific delay fields are stored as float64, and Cancelled, Diverted and FlightNumber are int64, making the schema well suited to pandas, Polars, Dask or MLCroissant readers.

How analysts use it

Equity analysts can aggregate on-time arrival rates and weather-driven delay minutes to gauge operational reliability of carriers and hub airports relevant to airline, aerospace and travel-exposed names. Infrastructure, logistics and credit analysts can map delay distributions and cancellation rates by Origin, Dest and Carrier to stress-test cargo, hospitality and consumer-spending models during disruption periods.

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