An R package for reading, analyzing, and visualizing public transit data in GTFS format using tidyverse and sf.
tidytransit is an R package that provides tools for working with General Transit Feed Specification (GTFS) data, the standard format for public transportation schedules and geographic information. It reads GTFS feeds into R, converts them into tidyverse and simple features data frames, and enables analysis such as travel time calculation, frequency analysis, and feed validation. The package solves the problem of efficiently processing and analyzing transit data within the R ecosystem for transportation research and planning.
Transportation planners, researchers, data analysts, and R users who need to analyze public transit data, map transit networks, calculate service metrics, or validate GTFS feeds. It is particularly useful for those working in urban planning, transit agencies, or academic research involving transportation systems.
Developers choose tidytransit because it seamlessly integrates GTFS data into the popular tidyverse and sf ecosystems in R, making transit analysis more accessible and reproducible. Its focus on tidy data principles and spatial capabilities provides a consistent workflow for mapping, validation, and performance analysis compared to lower-level GTFS parsing tools.
R package for working with GTFS data
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Seamlessly reads GTFS feeds into tidyverse-compatible data frames, enabling consistent data manipulation with dplyr and other tidyverse tools, as highlighted in the README's emphasis on tidy data principles.
Converts stops and routes to simple features (sf) data frames for easy mapping and spatial analysis in R, with specific functions like gtfs_as_sf documented in the vignettes.
Provides built-in functions for travel time calculation, frequency analysis, and feed validation, supporting various transit planning tasks as shown in the key features and linked vignettes.
Actively maintained with CRAN availability, continuous integration badges, and detailed vignettes for guidance, indicating reliable support and updates.
Exclusively designed for R, making it unsuitable for projects or teams using other programming languages, which limits cross-platform integration and forces dependency on the R environment.
Primarily handles static GTFS schedule data without built-in support for real-time transit updates (GTFS-realtime), a limitation for modern transit applications requiring dynamic data.
Requires users to be proficient with the tidyverse and sf packages, adding a learning curve for those new to these R ecosystems, and installation depends on sf which can have complex setup on some systems.