Route Stats¶
-
gtfs_utils.core_computations.
compute_route_stats
(trip_stats_subset: pandas.core.frame.DataFrame, date: datetime.date, source_files_base_name: List[str], headway_start_time: str = '07:00:00', headway_end_time: str = '19:00:00') → pandas.core.frame.DataFrame¶ Compute stats for the given subset of trips stats.
Parameters: - trip_stats_subset – Subset of the output of
compute_trip_stats()
- date – The original schedule date
- source_files_base_name – The original zips the data is based on (GTFS, Tariff, etc.)
- headway_start_time – HH:MM:SS time string indicating the start time for computing headway stats
- headway_end_time – HH:MM:SS time string indicating the end time for computing headway stats
Returns: A DataFrame with columns as described below
Route stats table has the following columns:
agency_id
- Same as ingtfs_utils.compute_trip_stats()
agency_name
- Same as ingtfs_utils.compute_trip_stats()
all_start_time
- All of the start times (formatted as HH:MM:SS) in which the trips in the route start, separated by semicolonsall_stop_code
- Same as ingtfs_utils.compute_trip_stats()
all_stop_desc_city
- Same as ingtfs_utils.compute_trip_stats()
all_stop_id
- Same as ingtfs_utils.compute_trip_stats()
all_stop_latlon
- Same as ingtfs_utils.compute_trip_stats()
all_stop_name
- Names of all stops of the trip (as described in stop_name field in stops.txt file), separated by semicolonsall_trip_id
- All of the identifiers (trip_id
, as specified in trips.txt file) of the trips in the route, separated by semicolonsall_trip_id_to_date
- all thetrip_id_to_date
ids that match this route, separated by semicoloncluster_id
- Same as ingtfs_utils.compute_trip_stats()
cluster_name
- Same as ingtfs_utils.compute_trip_stats()
cluster_sub_desc
- Same as ingtfs_utils.compute_trip_stats()
date
- Same as ingtfs_utils.compute_trip_stats()
end_stop_city
- Same as ingtfs_utils.compute_trip_stats()
end_stop_desc
- Same as ingtfs_utils.compute_trip_stats()
end_stop_id
- Same as ingtfs_utils.compute_trip_stats()
end_stop_lat
- Same as ingtfs_utils.compute_trip_stats()
end_stop_lon
- Same as ingtfs_utils.compute_trip_stats()
end_stop_name
- Same as ingtfs_utils.compute_trip_stats()
end_time
- Same as ingtfs_utils.compute_trip_stats()
, referring to the last trip of the routeend_zone
- Same as ingtfs_utils.compute_trip_stats()
source_files
- Same as ingtfs_utils.compute_trip_stats()
is_bidirectional
- 1 if the route has trips in both directions, otherwise 0is_loop
- Same as ingtfs_utils.compute_trip_stats()
line_type
- Same as ingtfs_utils.compute_trip_stats()
line_type_desc
- Same as ingtfs_utils.compute_trip_stats()
max_headway
- The maximal duration (in minutes) between trip starts on the route betweenheadway_start_time
andheadway_end_time
mean_headway
- The mean duration (in minutes) between trip starts on the route betweenheadway_start_time
andheadway_end_time
mean_trip_distance
- The full travel distance of each trip on the route in meters, which is the maximal shape_dist_traveled, as specified in stop_times.txt file (calculated as service_distance/num_trips)mean_trip_duration
- Duration of each trip on the route in hours (calculated as service_duration/num_trips)min_headway
- The minimal duration (in minutes) between trip starts on the route betweenheadway_start_time
andheadway_end_time
num_stops
- Same as ingtfs_utils.compute_trip_stats()
num_trip_ends
- Number of trips on the route in the subset with non-null end times before 23:59:59num_trip_starts
- Number of trips on the route in the subset with non-null start timesnum_trips
- Number of trips on the route in the subsetnum_zones
- Same as ingtfs_utils.compute_trip_stats()
num_zones_missing
- Same as ingtfs_utils.compute_trip_stats()
peak_end_time
- End time of first longest period during which the peak number of trips (peak_num_trips
) occurspeak_num_trips
- Maximal number of simultaneous trips in the service (for a given direction)peak_start_time
- Start time of first longest period during which the peak number of trips (peak_num_trips
) occursroute_alternative
- Same as ingtfs_utils.compute_trip_stats()
route_direction
- Same as ingtfs_utils.compute_trip_stats()
route_id
- Same as ingtfs_utils.compute_trip_stats()
route_long_name
- Same as ingtfs_utils.compute_trip_stats()
route_mkt
- Same as ingtfs_utils.compute_trip_stats()
route_short_name
- Same as ingtfs_utils.compute_trip_stats()
route_type
- Same as ingtfs_utils.compute_trip_stats()
service_distance
- The full travel distance of all trips on the route in meters, which is the maximal shape_dist_traveled, as specified in stop_times.txt file.service_duration
- Total duration of all trips on the route in hoursservice_speed
- Average speed each trip on the route in km/hsource_files
- base name of the files the data is based on (as they are saved on S3).start_stop_city
- Same as ingtfs_utils.compute_trip_stats()
start_stop_desc
- Same as ingtfs_utils.compute_trip_stats()
start_stop_id
- Same as ingtfs_utils.compute_trip_stats()
start_stop_lat
- Same as ingtfs_utils.compute_trip_stats()
start_stop_lon
- Same as ingtfs_utils.compute_trip_stats()
start_stop_name
- Same as ingtfs_utils.compute_trip_stats()
start_time
- Same as ingtfs_utils.compute_trip_stats()
, referring to the first trip of the routestart_zone
- Same as ingtfs_utils.compute_trip_stats()
If
trip_stats_subset
is empty, return an empty DataFrame.- trip_stats_subset – Subset of the output of