I am working with a gtfs file with shapely and shape id and I am trying to calculate the total unique length of the routes passing by a stop.

I have a list of routes that goes through the stop and I am going through a loop where it finds the multiple routes(or whatever the quantity is) for each stop and shape id for it to create a line string geometry I have used the buffer to buf the line and find the combined length of the route but the problem is some of the routes don't total up properly. Maybe I am doing something wrong or missing a step. Any help would be awesome

enter image description here

       line = LineString(shapes['geometry'].tolist())
       buffer = line.buffer(0.0001)
       combine = unary_union(dilate)
       length = combine.area

This is basically the result it is adding the total length of the final route so i am not even sure if it is combining. Basically I have a list of all the route ids that pass through the stop id and I have a (geodataframe for shape id geometry(x,y) where it holds the shape coord) it then filters through the shape id and creates a linestring and I am trying buffer the linestring so that it adds all the routes that passes the stop id.

enter image description here Here is some screenshot of the lines

  • I have the link to the dataset here transitfeeds.com/p/mta/82/20230104 some of the lines are displaying weirdly not sure what the case is
    – OwO
    Apr 28 at 18:23
  • Can you add a reproducable code snippet using the link dataset as input? There's to much unknown to be able to attempt an answer
    – BERA
    Apr 29 at 14:55

1 Answer 1


If the shape_id values in the shapes.txt files are used to recognize the routes then:

import pandas as pd
from shapely.geometry import LineString
import geopandas as gpd
sh = pd.read_csv("shapes.txt")
shape_id     shape_pt_lat  shape_pt_lon     shape_pt_sequence
0  M010024     40.720670    -73.997748              10001
1  M010024     40.720692    -73.997729              10002
2  M010024     40.720812    -73.997659              10003

# group by shape_id column
grs = sh.groupby(['shape_id'])
# as the data have a shape_pt_sequence in each group, it is possible to 
# get a line/route per group
lines = []
id =  []
for k in list(grs.groups.keys()):
  gr = gr.get_group(k)
routes = gpd.GeoDataFrame({'shape_id':id,'geometry':lines})
routes = gdf.set_crs('epsg:4326')
    shape_id                    geometry
0  M010024  LINESTRING (-73.99775 40.72067, -73.99773 40.7...
1  M010028  LINESTRING (-73.99037 40.73135, -73.99021 40.7...
2  M010029  LINESTRING (-73.99775 40.72067, -73.99773 40.7...

Result with Matplotlib

enter image description here

With Folium

enter image description here

shape_id = SBS603231

enter image description here

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