Static and interactive visualization

A map is a derived analytical artifact. It can misstate units, hide missing data, expose exact locations, or contact third-party services even when the underlying geometry operations are correct.

Privacy gate

Before plotting:

1. classify coordinates, addresses, trajectories, parcels, facilities, and small-area attributes for sensitivity;
2. decide whether the audience needs exact geometry;
3. aggregate, suppress small groups, jitter only with a defensible privacy model, or generalize at an appropriate scale;
4. remove direct identifiers and sensitive tooltip/popup fields;
5. inspect the output itself—HTML, SVG, PDF, and GeoJSON can preserve exact coordinates or attributes even when the image looks coarse.

The bundled scripts/sensitive_coordinates_checklist.py provides a conservative release gate. It does not claim legal or privacy compliance.

Static plotting

GeoPandas .plot() uses Matplotlib:

import matplotlib.pyplot as plt

fig, ax = plt.subplots(figsize=(8, 6))
gdf.plot(
    ax=ax,
    column="rate",
    cmap="viridis",
    legend=True,
    missing_kwds={
        "color": "lightgrey",
        "edgecolor": "black",
        "hatch": "///",
        "label": "Missing",
    },
)
ax.set_title("Synthetic rate by region")
ax.set_axis_off()
fig.savefig("derived/map.png", dpi=300, bbox_inches="tight")

Pin Matplotlib and optional mapping dependencies in the project lock. The GeoPandas 1.2 tagged source requires Matplotlib >=3.9 for plotting and mapclassify >=2.7 for classifications. Static examples were exercised with Matplotlib 3.11.2; the optional classification, interactive, and tile examples are illustrative unless those dependencies are installed and tested.

GeoPandas 1.2 rewrote static plotting: categorical palettes/styles accept dictionaries, legends reflect geometry types, and layered maps can use ax.legend(). CRS-based axis labels are enabled by default (add_labels=False disables them). scheme= supports vmin/vmax and can use legend_kwds={"colorbar": True} for a classified colorbar. Inspect existing figures after migration; Matplotlib collection layout is not a stable contract.

Choropleth correctness

State in the title/caption or metadata:

• variable definition, units, date, and source;
• whether values are counts, rates, densities, or percentages;
• normalization denominator and treatment of zero/missing denominators;
• classification method, number of bins, and explicit boundaries;
• color-map direction and meaning;
• missing/suppressed/out-of-scope styling;
• CRS/projection and any geographic generalization.

Raw counts over unequal polygon areas often communicate population size rather than rate. Compute an appropriate rate/density first and retain numerator and denominator.

scheme= delegates classification to mapclassify:

ax = gdf.plot(
    column="rate",
    scheme="quantiles",
    k=5,
    cmap="viridis",
    legend=True,
)

Quantiles balance feature counts but can place almost equal values in different bins. Equal intervals can leave sparse bins; natural breaks are data-dependent and make cross-map comparisons difficult. For comparisons, reuse explicit boundaries and a common normalization.

Missing data

GeoPandas ignores missing values by default. That can make missing areas look like background or water. Always count missing values and use missing_kwds when they are meaningful. Distinguish:

• missing attribute;
• missing geometry;
• empty geometry;
• suppressed value;
• zero;
• outside the study area.

Do not coerce missing values to zero for visual convenience.

Categorical maps

Use categorical=True for categories and a qualitative palette. Verify category order and legend labels; do not imply magnitude with a sequential palette. For example, the following explicit palette is supported in 1.2:

ax = gdf.plot(
    column="category", categorical=True,
    cmap={"A": "#4477AA", "B": "#EE6677"},
    legend=True, tiles=False,
)

Keep the palette complete for the data's categories. The earlier 1.1.4 fix for custom categorical/boolean explore() legend labels is included.

Layering

fig, ax = plt.subplots(figsize=(8, 6))
areas.plot(ax=ax, facecolor="none", edgecolor="0.4", zorder=1)
generalized_points.plot(ax=ax, color="black", markersize=8, zorder=2)

• Reproject every layer to a common CRS.
• Use facecolor="none" for transparent polygon faces; Python None means something different.
• Choose zorder, alpha, and line width deliberately.
• Confirm no layer is hidden by a filled polygon.
• Keep a stable visual scale when comparing panels.

Projection and extent

Choose a map projection for the communication goal:

• equal-area for area comparisons;
• local conformal for local shape/angles;
• Web Mercator only when required by a web tile system;
• a suitable global projection for world views.

GeoPandas may set a latitude-dependent aspect for geographic plots, but that is not a replacement for a chosen projection. Exact metric scale bars require a projected CRS with known linear units and limited distortion.

Antimeridian-crossing geometries must be split/wrapped before plotting; changing axis limits does not repair a line drawn across the map.

Basemaps are network and licensing dependencies

GeoPandas 1.2 static plot(tiles=...), contextily, and explore(tiles=...) can send viewport, zoom, IP, and timing information to a provider and can disclose the study area. They also introduce attribution, terms-of-use, caching, availability, and reproducibility requirements.

Static plots default to tiles=False; interactive drafts use tiles=None. Do not fetch tiles automatically. If a user explicitly approves a provider:

• verify its official URL, license, attribution, and usage limits;
• generalize sensitive overlays before the request;
• record provider, style, retrieval date, zoom, and tile hashes/cache;
• do not put credentials in source or generated HTML;
• use a vetted cache for reproducible/offline output where permitted.

Interactive explore

GeoDataFrame.explore() returns a folium.Map. Background tiles require CRS metadata and normally cause network requests. Start with a no-tile, no-attribute local draft:

interactive = generalized_gdf.explore(
    tiles=None,
    tooltip=False,
    popup=False,
    style_kwds={"fillOpacity": 0.5, "weight": 1},
)
interactive.save("derived/local-draft.html")

Even tiles=None HTML can reference CDN-hosted JavaScript/CSS depending on the Folium configuration. Inspect the generated HTML and use an approved offline asset strategy before sensitive or air-gapped use.

Privacy hazards:

• popup=True can expose all columns;
• tooltip lists can expose addresses or unique IDs;
• coordinates are embedded in the HTML/GeoJSON;
• layer names and filenames can disclose project context;
• user-added tile URLs can leak tokens and viewport;
• sharing the HTML shares data, not just a screenshot.

For multiple layers, add only generalized/allowlisted columns and explicit names. Do not use the interactive map as a data-access control boundary.

Geometry and plotting edge cases

• Empty/missing geometries are not visible; report their counts.
• Invalid polygons can render inconsistently; validate first.
• Mixed geometry types need explicit styles per type.
• Polygon holes and ring orientation should be checked after repair/export.
• Z/M are ignored by 2D plotting.
• Marker size is in display units, not map units, unless explicitly transformed.
• Alpha blending can create misleading dark areas from duplicated/overlapping features; audit duplicate geometry and join multiplication.
• Tiny overlay slivers can dominate outlines; fix/audit topology rather than merely hiding them.

Accessibility and honest design

• Prefer perceptually uniform, color-vision-aware palettes.
• Include text labels/patterns when color alone is insufficient.
• Keep legend order, labels, precision, and units consistent with the data.
• Avoid rainbow palettes and excessive classes.
• Use adequate contrast and minimum line/marker sizes.
• Include alt text/caption summarizing the main pattern and missing/suppressed data.
• Do not imply uncertainty-free precision; display uncertainty or caveats.

Reproducible output

Record:

• source/output hashes and privacy/generalization decision;
• package versions, CRS, projection, extent, and antimeridian handling;
• plotted column, normalization, classification/bins, palette, missing style;
• layer order and styling;
• figure size, DPI, and format;
• tile provider/license/retrieval metadata or explicit tiles=None;
• tooltip/popup allowlist and HTML external-resource audit.

Raster PNG reduces direct coordinate extraction compared with SVG/HTML but is not anonymization. Check metadata and visual landmarks before release.

Sources (verified 2026-10-01)

• GeoPandas mapping and plotting guide.
• GeoPandas interactive mapping guide.
• GeoDataFrame.plot API.
• GeoDataFrame.explore API.
• GeoPandas 1.1.4 release notes — released 2026-06-26.
• GeoPandas 1.1.0 release notes — plotting and dependency changes.

• GeoPandas 1.2.0 plotting implementation.