.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "gallery/plot_18_border_contrast.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_plot_18_border_contrast.py: Borders between similar colours =============================== In a choropleth, two neighbours of similar colour (both pale, or both dark) merge into one patch when the outline is close to them in tone: the border between them disappears. ``border_contrast`` finds those shared borders and redraws **only them**, in a colour that stands out; the polygons keep their own outline. The same map is drawn three times with a pale outline (``stroke="#eeeeee"``) on a blue palette: * without the option, where the pale departments run together; * with ``border_contrast="check"``, which reveals the weak borders in magenta (and warns with their number); * with ``border_contrast=True``, which redraws them dark. Data: mortality from heart failure, rate per 100,000 inhabitants (Sante publique France, ODISSE). .. GENERATED FROM PYTHON SOURCE LINES 22-63 .. raw:: html .. raw:: html .. raw:: html .. code-block:: Python import warnings from pathlib import Path import pandas as pd import mappyng as mp from mappyng.data import load_france_departments deps = load_france_departments().to_crs(2154) deps = deps[deps["COD_GEO"].str.len() == 2] # metropolitan France 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") def build(title, **options): return ( mp.Map(deps, width=620, height="auto", border_radius=0) + mp.Choropleth( deps, column="taux_mortalite", cmap="Blues", method="Quantiles", num_classes=5, stroke="#eeeeee", stroke_width=0.6, legend=mp.Legend("Deaths / 100,000", orientation="horizontal", decimals=0, swatch_width=18, fontsize=7, label_rotation=0, nodata_label="No data"), **options, ) + mp.Title(title) ) # Without the option: pale neighbours run together. m_off = build("Without border_contrast") # Check: the weak borders in magenta. The warning that counts them is silenced # here only to keep the example output short. with warnings.catch_warnings(): warnings.simplefilter("ignore") m_check = build("border_contrast='check'", border_contrast="check") # Fix: only those shared borders are redrawn, dark on pale areas. m_fix = build("border_contrast=True", border_contrast=True) .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.298 seconds) .. _sphx_glr_download_gallery_plot_18_border_contrast.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_18_border_contrast.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_18_border_contrast.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_18_border_contrast.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_