.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "gallery/plot_02b_choropleth_yaml.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_02b_choropleth_yaml.py: The same choropleth, from YAML ============================== This is the :doc:`Choropleth ` example rebuilt from a single YAML document instead of Python. Every parameter -- the framing ``bbox``, the overseas ``cartouche_params``, the drop shadow lifting France, the layers, the legend and the chrome -- lives in the document. The data is fetched declaratively too: each ``data:`` block names a built-in ``dataset`` (reprojected with ``crs``) and the choropleth layer ``join``\s its values from a CSV. No glue code runs. :meth:`mappyng.Map.from_yaml` resolves the sources and returns a ready :class:`~mappyng.Map`; from a shell the same file renders with:: python -m mappyng choropleth.yaml -o choropleth.svg # or .png/.pdf/.html Hover a department to read its value. .. GENERATED FROM PYTHON SOURCE LINES 20-109 .. raw:: html .. code-block:: Python from mappyng import Map # A complete map: configuration, layers (each with its own data source), # a declarative drop shadow, and chrome. Compare it line for line with the # Python of the Choropleth example -- it is the same map, declared. YAML = """ mappyng: 1 map: width: 900 height: 1000 padding: 25 facecolor: "#B9D9EB" border_radius: 10 box_shadow: {dx: 3, dy: 3, blur: 6, opacity: 0.2} bbox: [90000, 6040000, 1280000, 7150000] # Lambert-93 mainland frame cartouche_spacing: 15 data: {dataset: europe, crs: 2154} # base geometry (background) cartouche_params: 0: {bbox: [-6890454, 1780151, -6799589, 1874186], crs: 3857, cartouche_title: Guadeloupe, cartouche_title_size: 7, border_radius: 6, box_shadow: true} 1: {bbox: [-6826862, 1609607, -6759494, 1685367], crs: 3857, cartouche_title: Martinique, cartouche_title_size: 7, border_radius: 6, box_shadow: true} 2: {bbox: [-6136680, 235261, -5707791, 671780], crs: 3857, cartouche_title: French Guiana, cartouche_title_size: 7, border_radius: 6, box_shadow: true} 3: {bbox: [6136383, -2448160, 6226316, -2366992], crs: 3857, cartouche_title: Reunion, cartouche_title_size: 7, border_radius: 6, box_shadow: true} 4: {bbox: [5006226, -1459183, 5050208, -1416184], crs: 3857, cartouche_title: Mayotte, cartouche_title_size: 7, border_radius: 6, box_shadow: true} layers: - type: BasemapLayer data: {in_memory: false} params: {} - type: VectorLayer data: {dataset: france_regions, crs: 2154} params: {stroke: "#4d4d4d", stroke_width: 0.1, on_cartouches: true} - type: ChoroplethLayer data: dataset: france_departments crs: 2154 join: path: data/cardio_mortalite_dep.csv left_on: COD_GEO right_on: code_dep dtype: {code_dep: str} params: column: taux_mortalite cmap: Reds method: Quantiles num_classes: 5 stroke_width: 0.15 on_cartouches: true legend: title: "Deaths / 100,000 inhabitants" orientation: horizontal decimals: 0 nodata_label: "No data" - type: VectorLayer data: {dataset: france_regions, crs: 2154} params: {stroke: "#333333", stroke_width: 0.4, position: top, on_cartouches: true} shadows: - data: {dataset: europe, crs: 2154} params: {query: "code_pays_iso3=='FRA'", on_cartouches: true} chrome: title: text: Mortality from heart failure subtitle: Standardised rate, 2020-2022 average scale_bar: length: 100000 label: 100 km position: {x: 0.46, y: 0.9} opacity: 0.8 source: {text: "Source: Sante publique France (ODISSE)"} """ # Relative paths (the join CSV) resolve against base_dir. m = Map.from_yaml(YAML, base_dir=".") # Tooltips for the interactive SVG embedded by the gallery (and the HTML # that the ``python -m mappyng ... -o choropleth.html`` CLI would write). TOOLTIP = {"columns": ["LIB_GEO", "taux_mortalite"], "aliases": {"LIB_GEO": "Department", "taux_mortalite": "Rate"}} interactive = m.to_interactive(**TOOLTIP) # interactive.save("choropleth.html") .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.442 seconds) .. _sphx_glr_download_gallery_plot_02b_choropleth_yaml.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_02b_choropleth_yaml.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_02b_choropleth_yaml.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_02b_choropleth_yaml.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_