Contents

Prepare ARTURO dataset

Prepare ARTURO dataset

Important

Please see here for more details

import geopandas, pandas
import momepy
from shapely import wkt

Source data

  • Street layout

full = geopandas.read_file(
    "http://arturo.300000kms.net/data/model.geojson.zip"
)

  • Scores

scores = pandas.read_json(
    "http://www.atnight.ws/_imperdible/out/votes.json"
)

Convert IDs to strings:

scores["dm_id"] = scores["dm_id"].astype(str)

Extract point locations

  • Pull out points

parser = lambda s: wkt.loads(s.split(";")[1])
pts = geopandas.GeoSeries(
    full["geom_pu"].apply(parser),
    crs = "EPSG:25830"
)

  • Attach as columns

full["X"] = pts.x
full["Y"] = pts.y

Trim variables

vars_to_keep = [
    "OGC_FID", 
    "dm_id", 
    "dist_barri", 
    "average_quality", 
    "population_density", 
    "X", 
    "Y", 
    "geometry"
]

Join

db = full[vars_to_keep].join(
    scores.set_index("dm_id"), on="dm_id"
).rename({"value": "arturo_score"})

Write out

Note we convert to Spanish projection in metres

db.to_crs(epsg=25830)\
  .to_file("arturo_streets.gpkg", driver="GPKG")