feat(matplotlib): implement gantt-basic (#2386)

## Implementation: `gantt-basic` - matplotlib

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

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

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20543281362)*

---------

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

Author: github-actions[bot]

plots/gantt-basic/implementations/matplotlib.py

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+""" pyplots.ai
+gantt-basic: Basic Gantt Chart
+Library: matplotlib 3.10.8 | Python 3.13.11
+Quality: 95/100 | Created: 2025-12-27
+"""
+
+from datetime import datetime, timedelta
+
+import matplotlib.dates as mdates
+import matplotlib.pyplot as plt
+from matplotlib.patches import Patch
+
+
+# Data - Software Development Project
+tasks = [
+    {
+        "task": "Requirements Analysis",
+        "start": datetime(2025, 1, 6),
+        "end": datetime(2025, 1, 17),
+        "category": "Planning",
+    },
+    {"task": "System Design", "start": datetime(2025, 1, 13), "end": datetime(2025, 1, 31), "category": "Planning"},
+    {"task": "Database Setup", "start": datetime(2025, 1, 27), "end": datetime(2025, 2, 7), "category": "Development"},
+    {
+        "task": "Backend Development",
+        "start": datetime(2025, 2, 3),
+        "end": datetime(2025, 3, 7),
+        "category": "Development",
+    },
+    {
+        "task": "Frontend Development",
+        "start": datetime(2025, 2, 10),
+        "end": datetime(2025, 3, 14),
+        "category": "Development",
+    },
+    {"task": "API Integration", "start": datetime(2025, 3, 3), "end": datetime(2025, 3, 21), "category": "Development"},
+    {"task": "Unit Testing", "start": datetime(2025, 3, 10), "end": datetime(2025, 3, 28), "category": "Testing"},
+    {
+        "task": "Integration Testing",
+        "start": datetime(2025, 3, 24),
+        "end": datetime(2025, 4, 11),
+        "category": "Testing",
+    },
+    {
+        "task": "User Acceptance Testing",
+        "start": datetime(2025, 4, 7),
+        "end": datetime(2025, 4, 18),
+        "category": "Testing",
+    },
+    {"task": "Documentation", "start": datetime(2025, 3, 17), "end": datetime(2025, 4, 11), "category": "Deployment"},
+    {"task": "Deployment Prep", "start": datetime(2025, 4, 14), "end": datetime(2025, 4, 25), "category": "Deployment"},
+    {"task": "Go Live", "start": datetime(2025, 4, 28), "end": datetime(2025, 5, 2), "category": "Deployment"},
+]
+
+# Category colors (Python Blue variations + complementary)
+category_colors = {
+    "Planning": "#306998",  # Python Blue
+    "Development": "#FFD43B",  # Python Yellow
+    "Testing": "#4B8BBE",  # Light Python Blue
+    "Deployment": "#646464",  # Neutral Gray
+}
+
+# Create plot
+fig, ax = plt.subplots(figsize=(16, 9))
+
+# Sort tasks by start date for logical ordering
+tasks_sorted = sorted(tasks, key=lambda x: x["start"], reverse=True)
+
+# Draw bars
+bar_height = 0.6
+y_positions = range(len(tasks_sorted))
+
+for i, task in enumerate(tasks_sorted):
+    start = task["start"]
+    duration = (task["end"] - task["start"]).days
+    color = category_colors[task["category"]]
+
+    ax.barh(i, duration, left=start, height=bar_height, color=color, edgecolor="white", linewidth=1.5, alpha=0.9)
+
+# Y-axis: task names
+ax.set_yticks(y_positions)
+ax.set_yticklabels([t["task"] for t in tasks_sorted], fontsize=16)
+
+# X-axis: dates
+ax.xaxis.set_major_locator(mdates.WeekdayLocator(byweekday=mdates.MO, interval=2))
+ax.xaxis.set_major_formatter(mdates.DateFormatter("%b %d"))
+ax.tick_params(axis="x", labelsize=14, rotation=45)
+
+# Set x-axis limits with padding
+all_starts = [t["start"] for t in tasks]
+all_ends = [t["end"] for t in tasks]
+ax.set_xlim(min(all_starts) - timedelta(days=3), max(all_ends) + timedelta(days=3))
+
+# Add "today" marker line (mid-project for demonstration)
+today = datetime(2025, 3, 15)
+ax.axvline(today, color="#E74C3C", linewidth=2.5, linestyle="--", label="Today (Mar 15)", zorder=5)
+
+# Labels and title
+ax.set_xlabel("Timeline", fontsize=20)
+ax.set_ylabel("Tasks", fontsize=20)
+ax.set_title("gantt-basic · matplotlib · pyplots.ai", fontsize=24, fontweight="bold")
+
+# Grid (subtle, only on x-axis)
+ax.grid(True, axis="x", alpha=0.3, linestyle="--")
+ax.set_axisbelow(True)
+
+# Legend for categories
+legend_elements = [Patch(facecolor=color, edgecolor="white", label=cat) for cat, color in category_colors.items()]
+legend_elements.append(plt.Line2D([0], [0], color="#E74C3C", linewidth=2.5, linestyle="--", label="Today"))
+ax.legend(handles=legend_elements, loc="upper right", fontsize=14, framealpha=0.95)
+
+# Remove top and right spines for cleaner look
+ax.spines["top"].set_visible(False)
+ax.spines["right"].set_visible(False)
+
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")

plots/gantt-basic/metadata/matplotlib.yaml

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+library: matplotlib
+specification_id: gantt-basic
+created: '2025-12-27T19:20:43Z'
+updated: '2025-12-27T19:25:33Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20543281362
+issue: 0
+python_version: 3.13.11
+library_version: 3.10.8
+preview_url: https://storage.googleapis.com/pyplots-images/plots/gantt-basic/matplotlib/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/gantt-basic/matplotlib/plot_thumb.png
+preview_html: null
+quality_score: 95
+review:
+  strengths:
+  - Excellent color scheme using Python-branded colors with good accessibility
+  - Clean implementation with proper date handling using matplotlib.dates
+  - Logical task ordering by start date (reversed for top-to-bottom reading)
+  - Today marker with dashed red line adds practical utility
+  - Proper bar spacing and sizing for clear readability
+  - Complete legend including all categories and the Today marker
+  - Subtle x-axis grid without overwhelming the visualization
+  - Good use of tight_layout and bbox_inches for clean output
+  weaknesses:
+  - Axis labels are generic (Timeline, Tasks) - could be more descriptive like Project
+    Timeline (2025) and Project Tasks
+  - Could leverage more matplotlib features like annotations for key milestones