Transportation Module¶

The transportation module provides functions for processing GTFS (General Transit Feed Specification) data and creating transportation network graphs.

GTFS Processing¶

Transportation Network Analysis Module.

This module provides comprehensive functionality for processing General Transit Feed Specification (GTFS) data and creating transportation network representations. It specializes in converting public transit data into graph structures suitable for network analysis and accessibility studies.

All functions return ready-to-use pandas/GeoPandas objects or NetworkX graphs that can be seamlessly integrated into analysis pipelines, notebooks, or model training workflows.

Functions:

Name	Description
`load_gtfs`	Parse a GTFS zip file and enrich stops/shapes with geometry.
`get_od_pairs`	Materialise origin-destination pairs for every trip and service day.

load_gtfs ¶

load_gtfs(path)

Parse a GTFS zip file and enrich stops/shapes with geometry.

This function loads a GTFS (General Transit Feed Specification) zip file and converts it into a dictionary of pandas/GeoPandas DataFrames. Stop locations and route shapes are automatically converted to geometric objects for spatial analysis.

Parameters:

Name	Type	Description	Default
`path`	`str or Path`	Location of the zipped GTFS feed (e.g. `"./rome_gtfs.zip"`).	required

Returns:

Type	Description
`dict[str, DataFrame or GeoDataFrame]`	Keys are the original GTFS file names (without extension) and values are pandas or GeoPandas DataFrames ready for analysis.

get_od_pairs ¶

get_od_pairs(gtfs, start_date=None, end_date=None, include_geometry=True)

Materialise origin-destination pairs for every trip and service day.

This function creates a comprehensive dataset of all origin-destination pairs for transit trips within the specified date range, optionally including geometric information for spatial analysis.

Parameters:

Name	Type	Description	Default
`gtfs`	`dict`	Dictionary returned by :func:`load_gtfs`.	required
`start_date`	`str or None`	Restrict the calendar expansion to the closed interval `[start_date, end_date]` (format YYYYMMDD). When None the period is inferred from `calendar.txt`.	`None`
`end_date`	`str or None`	Restrict the calendar expansion to the closed interval `[start_date, end_date]` (format YYYYMMDD). When None the period is inferred from `calendar.txt`.	`None`
`include_geometry`	`bool`	If True the result is a GeoDataFrame whose geometry is a straight LineString connecting the two stops.	`True`

Returns:

Type	Description
`DataFrame or GeoDataFrame`	One row per trip-day-leg with departure / arrival timestamps, travel time in seconds and, optionally, geometry.

Graph Construction¶

Transportation Network Analysis Module.

This module provides comprehensive functionality for processing General Transit Feed Specification (GTFS) data and creating transportation network representations. It specializes in converting public transit data into graph structures suitable for network analysis and accessibility studies.

All functions return ready-to-use pandas/GeoPandas objects or NetworkX graphs that can be seamlessly integrated into analysis pipelines, notebooks, or model training workflows.

Functions:

Name	Description
`travel_summary_graph`	Aggregate stop-to-stop travel time & frequency into an edge list.

travel_summary_graph ¶

travel_summary_graph(
    gtfs,
    start_time=None,
    end_time=None,
    calendar_start=None,
    calendar_end=None,
    as_nx=False,
)

Aggregate stop-to-stop travel time & frequency into an edge list.

This function analyzes GTFS data to create a network representation of transit connections, computing average travel times and service frequencies between consecutive stops.

Parameters:

Name	Type	Description	Default
`gtfs`	`dict`	A dictionary produced by :func:`load_gtfs` - must contain at least `stop_times` and `stops`.	required
`start_time`	`str or None`	Consider only trips whose departure falls inside `[start_time, end_time]` (format HH:MM:SS). When None the whole service day is used.	`None`
`end_time`	`str or None`	Consider only trips whose departure falls inside `[start_time, end_time]` (format HH:MM:SS). When None the whole service day is used.	`None`
`calendar_start`	`str or None`	Period over which service-days are counted (format YYYYMMDD). If omitted it spans the native range in `calendar.txt`.	`None`
`calendar_end`	`str or None`	Period over which service-days are counted (format YYYYMMDD). If omitted it spans the native range in `calendar.txt`.	`None`
`as_nx`	`bool`	If True return a NetworkX graph, otherwise two GeoDataFrames `(nodes_gdf, edges_gdf)`. The latter follow the convention used in utils.py.	`False`

Returns:

Type	Description
`tuple[GeoDataFrame, GeoDataFrame] or Graph`	• Nodes - every stop with a valid geometry. • Edges - columns = `from_stop_id, to_stop_id, travel_time_sec, frequency, geometry`.