feat(plotnine): implement dumbbell-basic (#5420)

## Implementation: `dumbbell-basic` - python/plotnine

Implements the **python/plotnine** version of `dumbbell-basic`.

**File:** `plots/dumbbell-basic/implementations/python/plotnine.py`

**Parent Issue:** #945

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/24945231415)*

---------

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

Author: github-actions[bot]

plots/dumbbell-basic/implementations/python/plotnine.py

@@ -1,13 +1,17 @@
-""" pyplots.ai
+""" anyplot.ai
 dumbbell-basic: Basic Dumbbell Chart
-Library: plotnine 0.15.2 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-23
+Library: plotnine 0.15.3 | Python 3.14.4
+Quality: 89/100 | Updated: 2026-04-26
 """
 
+import os
+
 import pandas as pd
 from plotnine import (
     aes,
     element_blank,
+    element_line,
+    element_rect,
     element_text,
     geom_point,
     geom_segment,
@@ -20,24 +24,27 @@
 )
 
 
+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 = ["#009E73", "#D55E00", "#0072B2", "#CC79A7", "#E69F00", "#56B4E9", "#F0E442"]
+
 # Data: Employee satisfaction scores before and after workplace policy changes
 categories = ["Engineering", "Marketing", "Sales", "HR", "Finance", "Operations", "Customer Support", "Product"]
 before_scores = [65, 58, 72, 45, 68, 52, 40, 75]
 after_scores = [82, 71, 78, 73, 75, 68, 62, 88]
 
-# Calculate differences and sort by largest improvement first
 differences = [a - b for a, b in zip(after_scores, before_scores, strict=True)]
-sorted_data = sorted(
-    zip(categories, before_scores, after_scores, differences, strict=True), key=lambda x: x[3], reverse=True
-)
+sorted_data = sorted(zip(categories, before_scores, after_scores, differences, strict=True), key=lambda x: x[3])
 categories = [d[0] for d in sorted_data]
 before_scores = [d[1] for d in sorted_data]
 after_scores = [d[2] for d in sorted_data]
+differences = [d[3] for d in sorted_data]
 
-# Create DataFrame for segments (connecting lines)
-df_segments = pd.DataFrame({"category": categories, "start": before_scores, "end": after_scores})
-
-# Create DataFrame for points (long format for legend)
+df_segments = pd.DataFrame({"category": categories, "start": before_scores, "end": after_scores, "diff": differences})
 df_points = pd.DataFrame(
     {
         "category": categories * 2,
@@ -46,32 +53,40 @@
     }
 )
 
-# Create ordered categorical for proper y-axis ordering
 df_segments["category"] = pd.Categorical(df_segments["category"], categories=categories, ordered=True)
 df_points["category"] = pd.Categorical(df_points["category"], categories=categories, ordered=True)
+df_points["period"] = pd.Categorical(df_points["period"], categories=["Before", "After"], ordered=True)
 
-# Plot
 plot = (
     ggplot()
-    # Connecting lines (thin and subtle)
     + geom_segment(
-        aes(x="start", xend="end", y="category", yend="category"), data=df_segments, color="#888888", size=1.5
+        aes(x="start", xend="end", y="category", yend="category"), data=df_segments, color=INK_SOFT, size=1.5, alpha=0.6
+    )
+    + geom_point(aes(x="value", y="category", color="period"), data=df_points, size=7)
+    + scale_color_manual(values={"Before": OKABE_ITO[0], "After": OKABE_ITO[1]})
+    + scale_x_continuous(limits=(30, 100), breaks=[30, 40, 50, 60, 70, 80, 90, 100])
+    + labs(
+        x="Satisfaction Score",
+        y="Department",
+        title="Employee Satisfaction · dumbbell-basic · plotnine · anyplot.ai",
+        color="",
     )
-    # Dots with distinct colors for before/after
-    + geom_point(aes(x="value", y="category", color="period"), data=df_points, size=6, stroke=0.5)
-    + scale_color_manual(values={"Before": "#306998", "After": "#FFD43B"})
-    + scale_x_continuous(limits=(30, 100))
-    + labs(x="Satisfaction Score", y="Department", title="dumbbell-basic · plotnine · pyplots.ai", color="")
     + theme_minimal()
     + theme(
         figure_size=(16, 9),
-        plot_title=element_text(size=24),
-        axis_title=element_text(size=20),
-        axis_text=element_text(size=16),
-        legend_text=element_text(size=16),
+        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+        panel_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+        plot_title=element_text(size=24, color=INK, weight="bold"),
+        axis_title=element_text(size=20, color=INK),
+        axis_text=element_text(size=16, color=INK_SOFT),
+        legend_text=element_text(size=16, color=INK_SOFT),
+        legend_title=element_text(color=INK),
+        legend_background=element_rect(fill=ELEVATED_BG, color=ELEVATED_BG),
         legend_position="right",
+        panel_grid_major_x=element_line(color=INK, size=0.3, alpha=0.10),
+        panel_grid_minor=element_blank(),
         panel_grid_major_y=element_blank(),
     )
 )
 
-plot.save("plot.png", dpi=300, verbose=False)
+plot.save(f"plot-{THEME}.png", dpi=300, verbose=False)