feat(letsplot): implement choropleth-basic (#3115)

## Implementation: `choropleth-basic` - letsplot

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

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

**Parent Issue:** #3069

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20620327888)*

---------

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Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/choropleth-basic/implementations/letsplot.py

@@ -0,0 +1,118 @@
+""" pyplots.ai
+choropleth-basic: Choropleth Map with Regional Coloring
+Library: letsplot 4.8.2 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-31
+"""
+
+import pandas as pd
+from lets_plot import *  # noqa: F403
+from lets_plot.export import ggsave as export_ggsave
+from lets_plot.geo_data import geocode_countries
+
+
+LetsPlot.setup_html()  # noqa: F405
+
+# Data: GDP per capita by European countries (in thousands USD)
+data = {
+    "country": [
+        "Germany",
+        "France",
+        "Italy",
+        "Spain",
+        "Poland",
+        "Netherlands",
+        "Belgium",
+        "Sweden",
+        "Austria",
+        "Switzerland",
+        "Norway",
+        "Denmark",
+        "Finland",
+        "Ireland",
+        "Portugal",
+        "Czech Republic",
+        "Greece",
+        "Hungary",
+        "Romania",
+        "Bulgaria",
+        "Slovakia",
+        "Croatia",
+        "Slovenia",
+        "Lithuania",
+        "Latvia",
+        "Estonia",
+        "Luxembourg",
+    ],
+    "gdp_per_capita": [
+        48.7,
+        42.3,
+        34.5,
+        30.1,
+        17.8,
+        57.0,
+        51.2,
+        55.7,
+        53.3,
+        92.4,
+        89.2,
+        67.8,
+        53.2,
+        100.2,
+        24.5,
+        27.0,
+        20.2,
+        18.8,
+        15.1,
+        13.9,
+        21.3,
+        18.5,
+        28.4,
+        24.0,
+        21.8,
+        28.3,
+        126.4,
+    ],
+}
+df = pd.DataFrame(data)
+
+# Get country boundaries
+countries = geocode_countries(df["country"].tolist()).get_boundaries()
+df_geo = countries.merge(df, left_on="found name", right_on="country", how="left")
+
+# Create choropleth map with European focus
+plot = (
+    ggplot()  # noqa: F405
+    + geom_map(  # noqa: F405
+        aes(fill="gdp_per_capita"),  # noqa: F405
+        data=df,
+        map=df_geo,
+        map_join=["country", "found name"],
+        color="#404040",
+        size=0.6,
+        alpha=0.95,
+    )
+    + scale_fill_gradient(  # noqa: F405
+        low="#FFD43B", high="#306998", name="GDP per Capita\n(thousands USD)", na_value="#E0E0E0"
+    )
+    + labs(title="European GDP per Capita · choropleth-basic · letsplot · pyplots.ai")  # noqa: F405
+    + coord_cartesian(xlim=[-12, 32], ylim=[35, 71])  # noqa: F405
+    + ggsize(1600, 900)  # noqa: F405
+    + theme_minimal()  # noqa: F405
+    + theme(  # noqa: F405
+        plot_title=element_text(size=26, face="bold"),  # noqa: F405
+        legend_title=element_text(size=18),  # noqa: F405
+        legend_text=element_text(size=16),  # noqa: F405
+        legend_position=[0.88, 0.35],
+        axis_title=element_blank(),  # noqa: F405
+        axis_text=element_blank(),  # noqa: F405
+        axis_ticks=element_blank(),  # noqa: F405
+        panel_grid=element_blank(),  # noqa: F405
+        plot_background=element_rect(fill="white"),  # noqa: F405
+    )
+)
+
+# Save as PNG (scale 3x for 4800 × 2700 px)
+export_ggsave(plot, "plot.png", path=".", scale=3)
+
+# Save interactive HTML
+export_ggsave(plot, "plot.html", path=".")

plots/choropleth-basic/metadata/letsplot.yaml

@@ -0,0 +1,27 @@
+library: letsplot
+specification_id: choropleth-basic
+created: '2025-12-31T13:57:47Z'
+updated: '2025-12-31T14:09:44Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20620327888
+issue: 3069
+python_version: 3.13.11
+library_version: 4.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/choropleth-basic/letsplot/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/choropleth-basic/letsplot/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/choropleth-basic/letsplot/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent use of lets-plot geocode_countries() for automatic boundary retrieval
+  - Clean professional appearance with appropriate coordinate limits focusing on Europe
+  - Good colorblind-accessible yellow-blue color scheme
+  - Proper missing data handling with na_value parameter
+  - Well-structured theme with appropriate removal of axes/grid for map visualization
+  - Generates both PNG and HTML outputs for interactive capability
+  weaknesses:
+  - Legend could be larger and more prominent for better readability at full size
+  - Some European countries missing from data (UK, Iceland, Southern Europe) - more
+    coverage recommended
+  - Extreme outlier (Luxembourg 126.4k) compresses color scale making mid-range countries
+    harder to distinguish