Borderless choroplethΒΆ

Metropolitan France alone, with no chrome around the map: no ocean panel, no frame and no drop shadow. Leaving facecolor unset and border_radius=0 places the choropleth directly on the page background, for a clean figure to drop into a document.

Hover a department to read its value.

Source: Sante publique France (ODISSE) Deaths / 100,000 inhabitants 25 42 46 50 54 71 Mortality from heart failure Metropolitan France, standardised rate
from pathlib import Path

import pandas as pd

from mappyng import Map, ChoroplethLayer
from mappyng.data import load_france_departments

deps = load_france_departments().to_crs(2154)
# Metropolitan France only: its department codes have two characters,
# while every overseas department or collectivity has three.
deps = deps[deps["COD_GEO"].str.len() == 2]
df = pd.read_csv(Path("data") / "cardio_mortalite_dep.csv", dtype={"code_dep": str})
deps = deps.merge(df, left_on="COD_GEO", right_on="code_dep", how="left")

m = Map(deps, width=820, height="auto", border_radius=0)
m.add(ChoroplethLayer(deps, column="taux_mortalite", cmap="Reds",
                      method="Quantiles", num_classes=5, stroke_width=0.2,
                      legend={"title": "Deaths / 100,000 inhabitants",
                              "orientation": "horizontal", "decimals": 0,
                              "nodata_label": "No data"}))

m.title("Mortality from heart failure",
        subtitle="Metropolitan France, standardised rate")
m.source("Source: Sante publique France (ODISSE)")

# Hover tooltips. The gallery embeds an interactive SVG from this dict; the
# same call also yields a standalone HTML file.
TOOLTIP = {"columns": ["LIB_GEO", "taux_mortalite"],
           "aliases": {"LIB_GEO": "Department", "taux_mortalite": "Rate"}}
interactive = m.to_interactive(**TOOLTIP)
# interactive.save("choropleth_borderless.html")

Total running time of the script: (0 minutes 0.139 seconds)

Gallery generated by Sphinx-Gallery