update(bullet-basic): matplotlib — comprehensive quality review

Comprehensive quality review improving visual design, data quality, spec compliance, and library feature usage.

Author: MarkusNeusinger

plots/bullet-basic/implementations/matplotlib.py

@@ -1,110 +1,128 @@
-""" pyplots.ai
+"""pyplots.ai
 bullet-basic: Basic Bullet Chart
-Library: matplotlib 3.10.8 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-23
+Library: matplotlib 3.10.8 | Python 3.14.3
+Quality: /100 | Updated: 2026-02-22
 """
 
+import matplotlib.patheffects as pe
 import matplotlib.pyplot as plt
 from matplotlib.lines import Line2D
-from matplotlib.patches import Patch
+from matplotlib.patches import FancyBboxPatch, Patch
 
 
-# Data - Multiple KPIs with actual values, targets, and qualitative ranges
+# Data - Quarterly KPI dashboard with percentage-based metrics for consistent comparison
 metrics = [
-    {"label": "Revenue", "actual": 275, "target": 250, "ranges": [150, 200, 300], "unit": "$K"},
-    {"label": "Profit", "actual": 45, "target": 50, "ranges": [20, 40, 60], "unit": "%"},
-    {"label": "New Customers", "actual": 85, "target": 100, "ranges": [50, 75, 120], "unit": ""},
-    {"label": "Satisfaction", "actual": 4.2, "target": 4.5, "ranges": [3.0, 4.0, 5.0], "unit": "/5"},
+    {"label": "Revenue", "actual": 92, "target": 85, "ranges": [40, 70, 100]},
+    {"label": "Profit Margin", "actual": 38, "target": 45, "ranges": [20, 40, 60]},
+    {"label": "Customer Growth", "actual": 71, "target": 80, "ranges": [30, 60, 100]},
+    {"label": "Satisfaction", "actual": 84, "target": 90, "ranges": [50, 75, 100]},
+    {"label": "On-Time Delivery", "actual": 96, "target": 95, "ranges": [60, 80, 100]},
 ]
 
 # Qualitative band colors (grayscale: poor -> satisfactory -> good)
-band_colors = ["#d9d9d9", "#bfbfbf", "#a6a6a6"]
+band_colors = ["#e0e0e0", "#c8c8c8", "#b0b0b0"]
+actual_color = "#306998"
+target_color = "#1a1a1a"
 
 # Create plot (4800x2700 px)
 fig, ax = plt.subplots(figsize=(16, 9))
 
-bar_height = 0.4
-spacing = 1.5
+bar_height = 0.32
+band_height = bar_height * 2.4
+spacing = 1.2
 y_positions = [i * spacing for i in range(len(metrics))]
 
 for i, metric in enumerate(metrics):
     y = y_positions[i]
     ranges = metric["ranges"]
-    max_range = ranges[-1]
 
-    # Draw qualitative range bands (background bands from low to high)
+    # Draw qualitative range bands using FancyBboxPatch for rounded corners
     band_starts = [0] + ranges[:-1]
-    band_ends = ranges
-
-    for j, (start, end) in enumerate(zip(band_starts, band_ends, strict=True)):
+    for j, (start, end) in enumerate(zip(band_starts, ranges, strict=True)):
         width = end - start
-        ax.barh(y, width, left=start, height=bar_height * 2.2, color=band_colors[j], edgecolor="none", zorder=1)
-
-    # Draw actual value bar (the main measure)
-    ax.barh(y, metric["actual"], height=bar_height, color="#306998", edgecolor="none", zorder=2)
+        box = FancyBboxPatch(
+            (start, y - band_height / 2),
+            width,
+            band_height,
+            boxstyle="round,pad=0,rounding_size=0.08",
+            facecolor=band_colors[j],
+            edgecolor="none",
+            zorder=1,
+        )
+        ax.add_patch(box)
+
+    # Draw actual value bar
+    actual_bar = FancyBboxPatch(
+        (0, y - bar_height / 2),
+        metric["actual"],
+        bar_height,
+        boxstyle="round,pad=0,rounding_size=0.06",
+        facecolor=actual_color,
+        edgecolor="none",
+        zorder=2,
+    )
+    ax.add_patch(actual_bar)
 
-    # Draw target marker (vertical line)
+    # Draw target marker (diamond with white outline for visibility)
     ax.plot(
-        [metric["target"], metric["target"]],
-        [y - bar_height * 0.7, y + bar_height * 0.7],
-        color="#1a1a1a",
-        linewidth=4,
-        solid_capstyle="butt",
+        metric["target"],
+        y,
+        marker="D",
+        markersize=11,
+        color=target_color,
         zorder=3,
+        path_effects=[pe.withStroke(linewidth=3, foreground="white")],
     )
 
-    # Add actual value as text label (positioned after the max range for consistency)
-    label_x = max_range + max_range * 0.03
+    # Actual value label to the right of the max range
     ax.text(
-        label_x,
+        ranges[-1] + 2,
         y,
-        f"{metric['actual']}{metric['unit']}",
+        f"{metric['actual']}%",
         va="center",
         ha="left",
         fontsize=16,
         fontweight="bold",
-        color="#306998",
+        color=actual_color,
         zorder=4,
     )
 
 # Y-axis labels (metric names)
 ax.set_yticks(y_positions)
-ax.set_yticklabels([m["label"] for m in metrics], fontsize=18)
+ax.set_yticklabels([m["label"] for m in metrics], fontsize=18, fontweight="bold")
 
-# X-axis styling - no label since metrics have different units
+# X-axis label — all metrics share a percentage scale
+ax.set_xlabel("Performance (%)", fontsize=20)
 ax.tick_params(axis="x", labelsize=16)
-ax.tick_params(axis="y", labelsize=18)
+ax.tick_params(axis="y", length=0)
 
 # Title
-ax.set_title("bullet-basic · matplotlib · pyplots.ai", fontsize=24, pad=20)
+ax.set_title("bullet-basic \u00b7 matplotlib \u00b7 pyplots.ai", fontsize=24, fontweight="medium", pad=20)
 
 # Grid on x-axis only, subtle
-ax.xaxis.grid(True, alpha=0.3, linestyle="--", zorder=0)
+ax.xaxis.grid(True, alpha=0.2, linewidth=0.8, linestyle="--", zorder=0)
 ax.set_axisbelow(True)
 
 # Remove spines for cleaner look
-ax.spines["top"].set_visible(False)
-ax.spines["right"].set_visible(False)
-ax.spines["left"].set_visible(False)
-
-# Set x-axis to start at 0
-ax.set_xlim(left=0)
+for spine in ["top", "right", "left"]:
+    ax.spines[spine].set_visible(False)
 
-# Adjust y-axis limits for padding
-ax.set_ylim(-spacing * 0.4, y_positions[-1] + spacing * 0.4)
+# Set axis limits
+ax.set_xlim(left=0, right=112)
+ax.set_ylim(-spacing * 0.5, y_positions[-1] + spacing * 0.5)
 
 # Invert y-axis so first metric is at top
 ax.invert_yaxis()
 
-# Add legend
+# Legend
 legend_elements = [
-    Patch(facecolor="#306998", edgecolor="none", label="Actual"),
-    Line2D([0], [0], color="#1a1a1a", linewidth=4, label="Target"),
-    Patch(facecolor="#a6a6a6", edgecolor="none", label="Good"),
-    Patch(facecolor="#bfbfbf", edgecolor="none", label="Satisfactory"),
-    Patch(facecolor="#d9d9d9", edgecolor="none", label="Poor"),
+    Patch(facecolor=actual_color, edgecolor="none", label="Actual"),
+    Line2D([0], [0], marker="D", color="w", markerfacecolor=target_color, markersize=8, label="Target"),
+    Patch(facecolor=band_colors[2], edgecolor="none", label="Good"),
+    Patch(facecolor=band_colors[1], edgecolor="none", label="Satisfactory"),
+    Patch(facecolor=band_colors[0], edgecolor="none", label="Poor"),
 ]
-ax.legend(handles=legend_elements, loc="lower right", fontsize=14, framealpha=0.9)
+ax.legend(handles=legend_elements, loc="upper center", bbox_to_anchor=(0.5, -0.08), ncol=5, fontsize=14, frameon=False)
 
 plt.tight_layout()
 plt.savefig("plot.png", dpi=300, bbox_inches="tight")

plots/bullet-basic/metadata/matplotlib.yaml

@@ -1,16 +1,16 @@
 library: matplotlib
 specification_id: bullet-basic
 created: '2025-12-23T09:18:21Z'
-updated: '2025-12-23T09:20:35Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-22T12:00:00+00:00'
+generated_by: claude-opus-4-6
 workflow_run: 20456603104
 issue: 0
-python_version: 3.13.11
+python_version: 3.14.3
 library_version: 3.10.8
 preview_url: https://storage.googleapis.com/pyplots-images/plots/bullet-basic/matplotlib/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/bullet-basic/matplotlib/plot_thumb.png
 preview_html: null
-quality_score: 92
+quality_score: null
 impl_tags:
   dependencies: []
   techniques:

plots/bullet-basic/specification.yaml

@@ -6,7 +6,7 @@ title: Basic Bullet Chart
 
 # Specification tracking
 created: 2025-12-15T20:44:46Z
-updated: 2025-12-15T20:44:46Z
+updated: 2026-02-22T12:00:00Z
 issue: 999
 suggested: MarkusNeusinger
 
@@ -15,10 +15,13 @@ tags:
   plot_type:
     - bullet
     - bar
+    - gauge
   data_type:
     - numeric
+    - categorical
   domain:
     - business
+    - general
   features:
     - basic
     - comparison