feat(altair): implement choropleth-basic (#3106)

## Implementation: `choropleth-basic` - altair

Implements the **altair** version of `choropleth-basic`.

**File:** `plots/choropleth-basic/implementations/altair.py`

**Parent Issue:** #3069

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:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20620324848)*

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plots/choropleth-basic/implementations/altair.py

@@ -0,0 +1,52 @@
+""" pyplots.ai
+choropleth-basic: Choropleth Map with Regional Coloring
+Library: altair 6.0.0 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-31
+"""
+
+import altair as alt
+from vega_datasets import data
+
+
+# Data - US unemployment rate by county
+counties = alt.topo_feature(data.us_10m.url, "counties")
+unemployment = data.unemployment()
+
+# Create choropleth map
+chart = (
+    alt.Chart(counties)
+    .mark_geoshape(stroke="white", strokeWidth=0.3)
+    .encode(
+        color=alt.Color(
+            "rate:Q",
+            scale=alt.Scale(scheme="blues", domain=[0, 0.25]),
+            legend=alt.Legend(
+                title="Unemployment (%)",
+                titleFontSize=20,
+                labelFontSize=16,
+                gradientLength=400,
+                gradientThickness=25,
+                titleLimit=200,
+            ),
+        ),
+        tooltip=[
+            alt.Tooltip("id:O", title="County ID"),
+            alt.Tooltip("rate:Q", title="Unemployment Rate (%)", format=".1%"),
+        ],
+    )
+    .transform_lookup(lookup="id", from_=alt.LookupData(unemployment, "id", ["rate"]))
+    .project(type="albersUsa")
+    .properties(
+        width=1500,
+        height=950,
+        title=alt.Title(
+            text="US County Unemployment · choropleth-basic · altair · pyplots.ai", fontSize=28, anchor="middle"
+        ),
+    )
+    .configure_view(strokeWidth=0)
+    .configure_legend(orient="right", offset=30, padding=10)
+)
+
+# Save as PNG and HTML
+chart.save("plot.png", scale_factor=3.0)
+chart.save("plot.html")

plots/choropleth-basic/metadata/altair.yaml

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+library: altair
+specification_id: choropleth-basic
+created: '2025-12-31T13:54:48Z'
+updated: '2025-12-31T14:05:55Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20620324848
+issue: 3069
+python_version: 3.13.11
+library_version: 6.0.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/choropleth-basic/altair/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/choropleth-basic/altair/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/choropleth-basic/altair/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent use of Altair's declarative grammar for geographic visualization with
+    topo_feature and transform_lookup
+  - Clean, readable code following KISS principle with proper structure
+  - Uses real-world vega_datasets unemployment data providing authentic, meaningful
+    visualization
+  - Well-configured legend with appropriate font sizes and gradient dimensions
+  - Appropriate Albers USA projection for US county-level maps
+  - Good color scheme (blues) that is colorblind-accessible and appropriate for sequential
+    data
+  weaknesses:
+  - Legend labels show decimal values (0.04, 0.08) which represent percentages but
+    could be clearer as 4%, 8% for better readability
+  - Missing explicit handling for missing data counties (spec suggests showing as
+    gray)
+  - Could leverage Altair's interactive features (.interactive() for zoom/pan or selection
+    highlights) to better showcase library strengths