Analysis of Temporal and Spatial Patterns of TTC Subway Delays in Toronto Based on Delay Data

Abstract

This study examines the temporal and spatial patterns of Toronto Transit Commission (TTC) subway delays in Toronto using the TTC Subway Delay Data. The dataset contains 28,191 delay records from January 1, 2025, to January 31, 2026, and the 2025 records are selected for analysis. Descriptive statistics and data visualization are used to examine hourly and station-level delay patterns. A random forest classification model is developed to predict whether at least one delay incident will be recorded during a specific date-hour period at Union Station. The results show that TTC subway delays are unevenly distributed across time and stations. Delay incidents are more frequent around 22:00, while several major stations, including the Kennedy Bloor-Danforth Line (BD), Bloor, Finch, Kipling, and Union Station, record relatively high numbers of delay incidents. The classification model achieves relatively high recall but low precision, indicating that it identifies many date-hour periods containing recorded delay incidents.