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Problems with this dataset? Open an issue.
You may also take a look at the source code.
The networks in this dataset can be loaded directly from graph-tool with:
import graph_tool.all as gt
g = gt.collection.ns["urban_streets/ahmedabad"]
(and likewise for the other networks available.)

urban_streets — Urban street networks (2017)

Description

20 urban street networks, corresponding to 1-square-mile maps of 20 cities around the world.

Tags
Transportation Roads Unweighted Metadata
Citation
Upstream URL OK
https://www.complex-networks.net/datasets.html#chap8
Networks
Tip: click on the table header to sort the list. Hover your mouse over it to obtain a legend.
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
ahmedabad 2,870 4,387 3.06 0.61 2.28 1823.51 0.01 0.04 86 1.00 Undirected Unipartite pos length 95 KiB 122 KiB 113 KiB 96 KiB
barcelona 210 323 3.08 1.22 2.67 104.54 -0.04 0.03 24 1.00 Undirected Unipartite pos length 7 KiB 9 KiB 8 KiB 7 KiB
bologna 541 773 2.86 0.95 2.32 272.44 0.01 0.03 38 1.00 Undirected Unipartite pos length 19 KiB 23 KiB 21 KiB 19 KiB
brasilia 179 230 2.57 1.06 2.25 174.37 -0.06 0.07 22 1.00 Undirected Unipartite pos length 6 KiB 8 KiB 7 KiB 6 KiB
cairo 1,496 2,255 3.01 0.65 2.30 887.34 -0.01 0.04 51 1.00 Undirected Unipartite pos length 51 KiB 64 KiB 59 KiB 50 KiB
irvine1 32 36 2.25 1.32 1.87 17.25 -0.14 0.08 8 1.00 Undirected Unipartite pos length 1 KiB 2 KiB 1 KiB 1 KiB
irvine2 217 227 2.09 1.08 1.58 413.16 -0.24 0.02 23 0.82 Undirected Unipartite pos length 7 KiB 9 KiB 8 KiB 7 KiB
london 488 730 2.99 0.93 2.41 286.56 -0.03 0.02 33 1.00 Undirected Unipartite pos length 17 KiB 22 KiB 20 KiB 17 KiB
los-angeles 240 340 2.83 1.27 2.47 167.58 -0.05 0.00 22 1.00 Undirected Unipartite pos length 8 KiB 11 KiB 10 KiB 8 KiB
new-delhi 252 334 2.65 1.01 2.14 168.90 -0.09 0.03 25 1.00 Undirected Unipartite pos length 9 KiB 11 KiB 10 KiB 8 KiB
new-york 248 419 3.38 0.81 2.69 115.08 0.16 0.03 24 1.00 Undirected Unipartite pos length 9 KiB 12 KiB 10 KiB 9 KiB
paris 335 494 2.95 1.07 2.52 185.78 -0.01 0.05 28 1.00 Undirected Unipartite pos length 12 KiB 15 KiB 13 KiB 12 KiB
richmond 697 1,086 3.12 0.91 2.56 490.36 0.06 0.06 49 1.00 Undirected Unipartite pos length 24 KiB 30 KiB 28 KiB 24 KiB
san-francisco 169 271 3.21 1.18 2.77 111.81 0.06 0.00 21 1.00 Undirected Unipartite pos length 6 KiB 8 KiB 7 KiB 6 KiB
savannah 584 958 3.28 0.78 2.55 443.49 0.16 0.00 39 1.00 Undirected Unipartite pos length 19 KiB 24 KiB 22 KiB 19 KiB
seoul 869 1,307 3.01 0.83 2.38 518.79 0.05 0.04 50 1.00 Undirected Unipartite pos length 29 KiB 37 KiB 33 KiB 29 KiB
venice 1,840 2,407 2.62 1.02 2.43 4647.90 -0.10 0.04 102 1.00 Undirected Unipartite pos length 60 KiB 77 KiB 72 KiB 60 KiB
vienna 467 692 2.96 0.96 2.52 231.25 0.02 0.01 32 1.00 Undirected Unipartite pos length 16 KiB 21 KiB 19 KiB 16 KiB
walnut-creek 169 197 2.33 1.11 1.81 150.67 -0.13 0.00 22 1.00 Undirected Unipartite pos length 6 KiB 8 KiB 7 KiB 6 KiB
washington 192 303 3.16 1.29 2.83 73.15 -0.04 0.04 21 1.00 Undirected Unipartite pos length 7 KiB 9 KiB 8 KiB 7 KiB
Ridiculograms
ahmedabad drawing
ahmedabad
barcelona drawing
barcelona
bologna drawing
bologna
brasilia drawing
brasilia
cairo drawing
cairo
irvine1 drawing
irvine1
irvine2 drawing
irvine2
london drawing
london
los-angeles drawing
los-angeles
new-delhi drawing
new-delhi
new-york drawing
new-york
paris drawing
paris
richmond drawing
richmond
san-francisco drawing
san-francisco
savannah drawing
savannah
seoul drawing
seoul
venice drawing
venice
vienna drawing
vienna
walnut-creek drawing
walnut-creek
washington drawing
washington