feat(matplotlib): implement lollipop-basic (#9595)

## Implementation: `lollipop-basic` - python/matplotlib

Implements the **python/matplotlib** version of `lollipop-basic`.

**File:** `plots/lollipop-basic/implementations/python/matplotlib.py`

**Parent Issue:** #934

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/28496285913)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>

Author: github-actions[bot]

plots/lollipop-basic/implementations/python/matplotlib.py

@@ -1,12 +1,13 @@
 """ anyplot.ai
 lollipop-basic: Basic Lollipop Chart
-Library: matplotlib 3.10.9 | Python 3.14.4
-Quality: 88/100 | Updated: 2026-04-26
+Library: matplotlib 3.11.0 | Python 3.13.14
+Quality: 87/100 | Updated: 2026-07-01
 """
 
 import os
 
 import matplotlib.pyplot as plt
+import matplotlib.ticker as mticker
 import numpy as np
 
 
@@ -15,10 +16,12 @@
 ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
 INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
 INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
 
+# Imprint palette — first series always brand green
 BRAND_GREEN = "#009E73"
 
-# Data: Product sales by category
+# Data: retail category sales (thousands)
 categories = [
     "Electronics",
     "Clothing",
@@ -33,27 +36,58 @@
 ]
 values = [87, 72, 65, 58, 52, 45, 41, 38, 32, 25]
 
-# Sort by value descending for clear ranking
-sorted_indices = np.argsort(values)[::-1]
-categories = [categories[i] for i in sorted_indices]
-values = [values[i] for i in sorted_indices]
+# Sort descending for clear ranking story
+order = np.argsort(values)[::-1]
+categories = [categories[i] for i in order]
+values = np.array([values[i] for i in order])
 
-fig, ax = plt.subplots(figsize=(16, 9), facecolor=PAGE_BG)
+avg_val = values.mean()
+
+fig, ax = plt.subplots(figsize=(8, 4.5), dpi=400, facecolor=PAGE_BG)
 ax.set_facecolor(PAGE_BG)
 
-x_positions = np.arange(len(categories))
-ax.vlines(x_positions, ymin=0, ymax=values, color=BRAND_GREEN, linewidth=2.5)
-ax.scatter(x_positions, values, color=BRAND_GREEN, s=300, zorder=3, edgecolors=PAGE_BG, linewidths=1.5)
+x = np.arange(len(categories))
+
+# Stems
+ax.vlines(x, ymin=0, ymax=values, color=BRAND_GREEN, linewidth=2.0, zorder=2)
+
+# Markers — slightly larger for the top performer to create focal point
+marker_sizes = np.where(x == 0, 120, 80)
+ax.scatter(x, values, color=BRAND_GREEN, s=marker_sizes, zorder=3, edgecolors=PAGE_BG, linewidths=1.0)
+
+# Value labels above each marker
+for xi, v in zip(x, values, strict=False):
+    ax.text(xi, v + 2.5, f"{v}K", ha="center", va="bottom", fontsize=8, color=INK_SOFT, fontweight="medium")
+
+# Average reference line — structural anchor for context
+ax.axhline(avg_val, color=INK_MUTED, linewidth=0.9, linestyle="--", zorder=1)
+ax.text(len(x) - 0.5, avg_val + 1.5, f"avg {avg_val:.0f}K", ha="right", va="bottom", fontsize=7.5, color=INK_MUTED)
+
+# Callout annotation on the top performer using matplotlib's annotation API
+ax.annotate(
+    "Top performer",
+    xy=(x[0], values[0]),
+    xytext=(x[0] + 0.9, values[0] + 13),
+    fontsize=6.5,
+    color=INK,
+    ha="center",
+    arrowprops={"arrowstyle": "->", "color": INK_MUTED, "lw": 0.8},
+    bbox={"facecolor": ELEVATED_BG, "edgecolor": INK_SOFT, "boxstyle": "round,pad=0.3", "linewidth": 0.6},
+)
+
+title = "lollipop-basic · python · matplotlib · anyplot.ai"
+ax.set_title(title, fontsize=12, fontweight="medium", color=INK, pad=8)
+ax.set_xlabel("Product Category", fontsize=10, color=INK)
+ax.set_ylabel("Sales (thousands)", fontsize=10, color=INK)
 
-ax.set_xlabel("Product Category", fontsize=20, color=INK)
-ax.set_ylabel("Sales (thousands)", fontsize=20, color=INK)
-ax.set_title("lollipop-basic · matplotlib · anyplot.ai", fontsize=24, fontweight="medium", color=INK)
+ax.set_xticks(x)
+ax.set_xticklabels(categories, rotation=45, ha="right", fontsize=8)
+ax.tick_params(axis="both", labelsize=8, colors=INK_SOFT, labelcolor=INK_SOFT)
 
-ax.set_xticks(x_positions)
-ax.set_xticklabels(categories, rotation=45, ha="right", fontsize=16)
-ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT, labelcolor=INK_SOFT)
+ax.set_ylim(0, max(values) * 1.38)
 
-ax.set_ylim(0, max(values) * 1.1)
+# Tidy y-axis numeric labels via FuncFormatter
+ax.yaxis.set_major_formatter(mticker.FuncFormatter(lambda v, _: f"{v:.0f}"))
 
 ax.spines["top"].set_visible(False)
 ax.spines["right"].set_visible(False)
@@ -63,5 +97,6 @@
 ax.yaxis.grid(True, alpha=0.15, color=INK, linewidth=0.8)
 ax.set_axisbelow(True)
 
-plt.tight_layout()
-plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)
+# Manual margins — bbox_inches must stay None (default) to preserve exact canvas size
+fig.subplots_adjust(left=0.10, right=0.97, top=0.91, bottom=0.26)
+plt.savefig(f"plot-{THEME}.png", dpi=400, facecolor=PAGE_BG)