disable state border plotting due to missing data

Dockerfile

@@ -4,7 +4,7 @@ ARG PLZ_DATA=Postleitzahlengebiete_-_OSM.geojson
 ARG PLZ_HIGHLIGHT=wtf_member_plz_prefixes.json
 
 # Set up environment with dependencies
-RUN apt-get update && apt-get install libblas-dev python3-pip libgeos-dev wget optipng imagemagick -y
+RUN apt-get update && apt-get install libblas-dev python3-pip libgeos-dev libgdal-dev wget optipng imagemagick -y
 COPY requirements.txt ./
 RUN pip install -r requirements.txt
 

main.py

@@ -28,27 +28,23 @@ def main(
         data.loc[data["plz"].str.startswith(plz_prefix), "highlighted"] = True
 
     # TODO: This should instead be a proper geo spatial projection
-    coordinate_transform = np.array([[1.0, 1.6]]).T
+    coordinate_transform = np.array([[1.0, 1.0]]).T
 
     ax = plt.axes(aspect="equal")
-    for bundesland in data["bundesland"].unique():
-        bundesland_df = data[data["bundesland"] == bundesland]
-        union = bundesland_df.unary_union
+    union = data.unary_union
+    for geom in getattr(union, "geoms", [union]):
+        ax.fill(
+            *geom.exterior.xy,
+            fc=map_background_color,
+            ec=image_background_color,
+            linewidth=0.1,
+        )
+
+    if any(data["highlighted"]):
+        union = data[data["highlighted"]].unary_union
         for geom in getattr(union, "geoms", [union]):
             ax.fill(
-                *(geom.exterior.xy * coordinate_transform),
-                fc=map_background_color,
-                ec=image_background_color,
-                linewidth=0.1,
-            )
-
-        if not any(bundesland_df["highlighted"]):
-            continue
-
-        union = bundesland_df[bundesland_df["highlighted"]].unary_union
-        for geom in getattr(union, "geoms", [union]):
-            ax.fill(
-                *(geom.exterior.xy * coordinate_transform),
+                *geom.exterior.xy,
                 fc=map_accent_color,
                 ec=None,
             )

requirements.txt

@@ -1,2 +1,3 @@
+numpy==1.26.4
 geopandas==0.11.1
 matplotlib==3.6.2