NYC Green Taxi Trip Records for December 2016 with Tip Prediction Target

Trip record data from the New York City Taxi and Limousine Commission for green taxi trips in December 2016, used in a tabular data benchmark. The dataset was transformed for regression tasks, with 'tip_amount' selected as the target variable and trips filtered to credit card payments only. String datetime information was extracted to numeric columns, and certain fare-related variables were removed to increase the importance of categorical location IDs.

Use Cases

• Predicting taxi tip amounts based on trip details and location IDs.
• Benchmarking regression model performance on a real-world, mixed-feature dataset.
• Analyzing temporal patterns in New York City green taxi trips for a specific month.
• Studying the relationship between payment type, location, and tipping behavior.

Strengths

• Data originates from the official New York City Taxi and Limousine Commission, a primary source.
• Specifically prepared for a regression benchmark, indicating a defined task and target variable.
• Focuses on credit card payment trips, which likely provides more reliable tip data.

Limitations

• Row count and file size are unknown, limiting suitability assessment for large-scale projects.
• Column-level documentation is absent; field semantics must be inferred from the original TLC data dictionary after download.
• Data is limited to a single taxi line (green) and a single month, which may not be representative of broader patterns.

Provenance

Source

New York City Taxi and Limousine Commission (TLC)

Collection Method

Original trip record data was downloaded and transformed for a benchmark, with specific variables removed or selected.

Time Range

December 2016

Geography

New York City, USA