feat(plotnine): implement linked-views-selection

plots/linked-views-selection/implementations/python/plotnine.py

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+"""anyplot.ai
+linked-views-selection: Multiple Linked Views with Selection Sync
+Library: plotnine | Python 3.13
+Quality: pending | Created: 2026-05-17
+"""
+
+import os
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+from matplotlib import pyplot as plt
+from matplotlib.patches import Patch
+
+
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+
+# Okabe-Ito palette
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2", "#CC79A7"]
+BRAND = OKABE_ITO[0]
+
+# Data
+np.random.seed(42)
+n = 300
+x = np.random.normal(50, 15, n)
+y = x * 0.7 + np.random.normal(0, 10, n)
+categories = np.random.choice(["Group A", "Group B", "Group C", "Group D"], n)
+df = pd.DataFrame({"x": x, "y": y, "category": categories})
+
+# Highlight one category to demonstrate linked views concept
+highlighted_category = "Group A"
+is_selected = df["category"] == highlighted_category
+
+# Plot
+fig = plt.figure(figsize=(16, 9), facecolor=PAGE_BG)
+gs = fig.add_gridspec(2, 3, hspace=0.3, wspace=0.3)
+
+ax_scatter = fig.add_subplot(gs[:, 0:2])
+ax_hist_x = fig.add_subplot(gs[0, 2])
+ax_hist_y = fig.add_subplot(gs[1, 2])
+
+# Set background for all axes
+ax_scatter.set_facecolor(PAGE_BG)
+ax_hist_x.set_facecolor(PAGE_BG)
+ax_hist_y.set_facecolor(PAGE_BG)
+
+# Scatter plot: full data with deemphasized points, selected highlighted
+ax_scatter.scatter(df["x"], df["y"], alpha=0.15, s=100, color=INK_SOFT, edgecolors="none")
+ax_scatter.scatter(
+    df[is_selected]["x"], df[is_selected]["y"], alpha=0.8, s=150, color=BRAND, edgecolors=PAGE_BG, linewidth=0.5
+)
+
+ax_scatter.set_xlabel("X Dimension", fontsize=20, color=INK)
+ax_scatter.set_ylabel("Y Dimension", fontsize=20, color=INK)
+ax_scatter.set_title("Scatter Plot", fontsize=18, color=INK_SOFT)
+ax_scatter.tick_params(axis="both", labelsize=16, colors=INK_SOFT)
+ax_scatter.spines["top"].set_visible(False)
+ax_scatter.spines["right"].set_visible(False)
+for s in ("left", "bottom"):
+    ax_scatter.spines[s].set_color(INK_SOFT)
+ax_scatter.yaxis.grid(True, alpha=0.10, linewidth=0.8, color=INK)
+
+# Histogram of X dimension
+bins = np.linspace(df["x"].min(), df["x"].max(), 20)
+ax_hist_x.hist(df["x"], bins=bins, alpha=0.15, color=INK_SOFT, edgecolor="none")
+ax_hist_x.hist(df[is_selected]["x"], bins=bins, alpha=0.8, color=BRAND, edgecolor="none")
+ax_hist_x.set_xlabel("X", fontsize=16, color=INK)
+ax_hist_x.set_ylabel("Count", fontsize=16, color=INK)
+ax_hist_x.set_title("X Distribution", fontsize=18, color=INK_SOFT)
+ax_hist_x.tick_params(axis="both", labelsize=14, colors=INK_SOFT)
+ax_hist_x.spines["top"].set_visible(False)
+ax_hist_x.spines["right"].set_visible(False)
+for s in ("left", "bottom"):
+    ax_hist_x.spines[s].set_color(INK_SOFT)
+
+# Histogram of Y dimension
+bins = np.linspace(df["y"].min(), df["y"].max(), 20)
+ax_hist_y.hist(df["y"], bins=bins, alpha=0.15, color=INK_SOFT, edgecolor="none")
+ax_hist_y.hist(df[is_selected]["y"], bins=bins, alpha=0.8, color=BRAND, edgecolor="none")
+ax_hist_y.set_xlabel("Y", fontsize=16, color=INK)
+ax_hist_y.set_ylabel("Count", fontsize=16, color=INK)
+ax_hist_y.set_title("Y Distribution", fontsize=18, color=INK_SOFT)
+ax_hist_y.tick_params(axis="both", labelsize=14, colors=INK_SOFT)
+ax_hist_y.spines["top"].set_visible(False)
+ax_hist_y.spines["right"].set_visible(False)
+for s in ("left", "bottom"):
+    ax_hist_y.spines[s].set_color(INK_SOFT)
+
+# Main title
+fig.suptitle("linked-views-selection · plotnine · anyplot.ai", fontsize=24, fontweight="medium", color=INK, y=0.98)
+
+# Add legend to explain highlighting
+legend_elements = [
+    Patch(facecolor=INK_SOFT, alpha=0.15, label="Other data"),
+    Patch(facecolor=BRAND, alpha=0.8, label=f"Selected: {highlighted_category}"),
+]
+fig.legend(
+    handles=legend_elements,
+    loc="lower center",
+    fontsize=16,
+    frameon=True,
+    fancybox=False,
+    shadow=False,
+    bbox_to_anchor=(0.5, -0.02),
+    facecolor=ELEVATED_BG,
+    edgecolor=INK_SOFT,
+)
+
+script_dir = Path(__file__).parent
+output_path = script_dir / f"plot-{THEME}.png"
+plt.savefig(output_path, dpi=300, bbox_inches="tight", facecolor=PAGE_BG)
+plt.close()

plots/linked-views-selection/metadata/python/plotnine.yaml

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+# Per-library metadata for plotnine implementation of linked-views-selection
+# Auto-generated by impl-generate.yml
+
+library: plotnine
+language: python
+specification_id: linked-views-selection
+created: '2026-05-17T00:36:38Z'
+updated: '2026-05-17T00:36:38Z'
+generated_by: claude-haiku
+workflow_run: 25976934580
+issue: 3344
+language_version: 3.13.13
+library_version: 0.15.4
+preview_url_light: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/plotnine/plot-light.png
+preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/plotnine/plot-dark.png
+preview_html_light: null
+preview_html_dark: null
+quality_score: null
+review:
+  strengths: []
+  weaknesses: []