feat(matplotlib): implement point-basic (#2578)

## Implementation: `point-basic` - matplotlib

Implements the **matplotlib** version of `point-basic`.

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

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20593348785)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/point-basic/implementations/matplotlib.py

@@ -0,0 +1,79 @@
+""" pyplots.ai
+point-basic: Point Estimate Plot
+Library: matplotlib 3.10.8 | Python 3.13.11
+Quality: 99/100 | Created: 2025-12-30
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+# Data - Customer satisfaction scores by department with 95% confidence intervals
+np.random.seed(42)
+
+departments = ["Customer Service", "Technical Support", "Sales", "Billing", "Shipping", "Product Quality", "Returns"]
+
+# Simulated mean satisfaction scores (1-10 scale) with varying confidence intervals
+estimates = np.array([7.8, 6.2, 7.1, 5.4, 8.3, 6.9, 5.8])
+# Different CI widths show varying sample sizes/uncertainty
+ci_lower = np.array([7.2, 5.4, 6.5, 4.6, 7.9, 6.2, 5.1])
+ci_upper = np.array([8.4, 7.0, 7.7, 6.2, 8.7, 7.6, 6.5])
+
+# Calculate errors for errorbar (asymmetric)
+lower_errors = estimates - ci_lower
+upper_errors = ci_upper - estimates
+
+# Plot
+fig, ax = plt.subplots(figsize=(16, 9))
+
+# Create horizontal point estimate plot with error bars
+y_positions = np.arange(len(departments))
+
+ax.errorbar(
+    estimates,
+    y_positions,
+    xerr=[lower_errors, upper_errors],
+    fmt="o",
+    color="#306998",
+    markersize=14,
+    markeredgecolor="white",
+    markeredgewidth=2,
+    capsize=8,
+    capthick=2.5,
+    elinewidth=2.5,
+    ecolor="#306998",
+)
+
+# Add reference line at overall mean
+overall_mean = np.mean(estimates)
+ax.axvline(x=overall_mean, color="#FFD43B", linestyle="--", linewidth=2.5, alpha=0.8)
+ax.text(
+    overall_mean + 0.05,
+    len(departments) - 0.3,
+    f"Overall Mean: {overall_mean:.1f}",
+    fontsize=16,
+    color="#B8860B",
+    fontweight="bold",
+)
+
+# Styling
+ax.set_yticks(y_positions)
+ax.set_yticklabels(departments)
+ax.set_xlabel("Satisfaction Score (1-10)", fontsize=20)
+ax.set_ylabel("Department", fontsize=20)
+ax.set_title("point-basic \u00b7 matplotlib \u00b7 pyplots.ai", fontsize=24)
+ax.tick_params(axis="both", labelsize=16)
+
+# Set x-axis limits with padding
+ax.set_xlim(3.5, 9.5)
+ax.set_ylim(-0.5, len(departments) - 0.5)
+
+# Grid - subtle horizontal lines
+ax.grid(True, axis="x", alpha=0.3, linestyle="--")
+ax.set_axisbelow(True)
+
+# Invert y-axis so first category is at top
+ax.invert_yaxis()
+
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")

plots/point-basic/metadata/matplotlib.yaml

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+library: matplotlib
+specification_id: point-basic
+created: '2025-12-30T09:32:00Z'
+updated: '2025-12-30T09:42:17Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20593348785
+issue: 0
+python_version: 3.13.11
+library_version: 3.10.8
+preview_url: https://storage.googleapis.com/pyplots-images/plots/point-basic/matplotlib/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/point-basic/matplotlib/plot_thumb.png
+preview_html: null
+quality_score: 99
+review:
+  strengths:
+  - Excellent horizontal layout following spec recommendation for readable category
+    labels
+  - Clear visual hierarchy with well-sized markers and error bar caps
+  - Reference line adds valuable context (overall mean) as suggested in spec
+  - Varying confidence interval widths demonstrate real-world uncertainty patterns
+  - Clean, professional appearance suitable for publication
+  weaknesses:
+  - Could add alpha transparency to markers for even better visual distinction (minor)