Map of a country by regions | scatter_mapbox | plotly

Thanks to Rob Raymond for the previos work. The aim is to represent the regions of a country with scatter_mapbox, I got this situation of the map (Spain is the example):

import requests
import plotly.express as px
import pandas as pd

# get Spain municipal boundaries
res = requests.get(
    "https://raw.githubusercontent.com/codeforgermany/click_that_hood/main/public/data/spain-provinces.geojson"
)

# get some cities in Spain
df = (
    pd.json_normalize(
        requests.get(
            "https://opendata.arcgis.com/datasets/6996f03a1b364dbab4008d99380370ed_0.geojson"
        ).json()["features"]
    )
    .loc[
        lambda d: d["properties.CNTRY_NAME"].eq("Spain"),
        ["properties.CITY_NAME", "geometry.coordinates"],
    ]
    .assign(
        lon=lambda d: d["geometry.coordinates"].apply(lambda v: v[0]),
        lat=lambda d: d["geometry.coordinates"].apply(lambda v: v[1]),
    )
)

# scatter the cities and add layer that shows municiple boundary
px.scatter_mapbox(df, lat="lat", lon="lon", hover_name="properties.CITY_NAME").update_layout(
    mapbox={
        "style": "carto-positron",
        "zoom": 3.5,
        "layers": [
            {
                "source": res.json(),
                "type": "line",
                "color": "green",
                "line": {"width": 1},
            }
        ],
    }
)

How to change cities by regions?

Solution

using geopandas https://plotly.com/python/mapbox-county-choropleth/#using-geopandas-data-frames
have created a column measure to define colorscale of province
simple case of doing choropleth instead of scatter
same can be achieved without geopandas referencing geojson and using pandas

import plotly.express as px
import numpy as np
import geopandas as gpd


gdf = gpd.read_file(
    "https://raw.githubusercontent.com/codeforgermany/click_that_hood/main/public/data/spain-provinces.geojson",
    crs="epsg:4326",
)
# for choropleth...
gdf["measure"] = np.random.randint(1, 1000, len(gdf))

px.choropleth_mapbox(
    gdf, geojson=gdf["geometry"].__geo_interface__, locations=gdf.index, color="measure", hover_name="name"
).update_layout(
    mapbox={
        "style": "carto-positron",
        "center": {
            "lon": sum(gdf.total_bounds[[0, 2]]) / 2,
            "lat": sum(gdf.total_bounds[[1, 3]]) / 2,
        },
        "zoom":4
    },
    margin={"l":0,"r":0,"t":0,"b":0}
)