feat(plotly): implement scatter-categorical

plots/scatter-categorical/implementations/plotly.py

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+""" pyplots.ai
+scatter-categorical: Categorical Scatter Plot
+Library: plotly 6.5.0 | Python 3.13.11
+Quality: 93/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import plotly.graph_objects as go
+
+
+# Data - Product performance across regions
+np.random.seed(42)
+n_per_group = 40
+
+# Generate distinct clusters for each region
+regions = ["North", "South", "West", "East"]
+colors = ["#306998", "#FFD43B", "#8B5CF6", "#10B981"]
+
+data = {
+    "North": {"x": np.random.normal(35, 8, n_per_group), "y": np.random.normal(75, 10, n_per_group)},
+    "South": {"x": np.random.normal(55, 10, n_per_group), "y": np.random.normal(60, 12, n_per_group)},
+    "West": {"x": np.random.normal(70, 7, n_per_group), "y": np.random.normal(85, 8, n_per_group)},
+    "East": {"x": np.random.normal(45, 9, n_per_group), "y": np.random.normal(45, 10, n_per_group)},
+}
+
+# Plot
+fig = go.Figure()
+
+for region, color in zip(regions, colors):
+    fig.add_trace(
+        go.Scatter(
+            x=data[region]["x"],
+            y=data[region]["y"],
+            mode="markers",
+            name=region,
+            marker=dict(size=14, color=color, opacity=0.7, line=dict(width=1, color="white")),
+            hovertemplate=f"{region}<br>Marketing: %{{x:.1f}}%<br>Sales: %{{y:.1f}}%<extra></extra>",
+        )
+    )
+
+# Layout
+fig.update_layout(
+    title=dict(text="scatter-categorical · plotly · pyplots.ai", font=dict(size=28), x=0.5, xanchor="center"),
+    xaxis=dict(
+        title=dict(text="Marketing Investment (%)", font=dict(size=22)),
+        tickfont=dict(size=18),
+        gridcolor="rgba(0,0,0,0.1)",
+        gridwidth=1,
+        showgrid=True,
+    ),
+    yaxis=dict(
+        title=dict(text="Sales Growth (%)", font=dict(size=22)),
+        tickfont=dict(size=18),
+        gridcolor="rgba(0,0,0,0.1)",
+        gridwidth=1,
+        showgrid=True,
+    ),
+    legend=dict(
+        title=dict(text="Region", font=dict(size=20)),
+        font=dict(size=18),
+        bordercolor="rgba(0,0,0,0.2)",
+        borderwidth=1,
+        x=1.02,
+        y=0.5,
+        yanchor="middle",
+    ),
+    template="plotly_white",
+    margin=dict(l=80, r=150, t=80, b=80),
+    plot_bgcolor="white",
+)
+
+# Save as PNG and HTML
+fig.write_image("plot.png", width=1600, height=900, scale=3)
+fig.write_html("plot.html", include_plotlyjs="cdn")

plots/scatter-categorical/metadata/plotly.yaml

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+library: plotly
+specification_id: scatter-categorical
+created: '2025-12-30T10:37:46Z'
+updated: '2025-12-30T10:44:50Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20594554925
+issue: 0
+python_version: 3.13.11
+library_version: 6.5.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-categorical/plotly/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/scatter-categorical/plotly/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-categorical/plotly/plot.html
+quality_score: 93
+review:
+  strengths:
+  - Excellent color palette that is colorblind-accessible (blue, yellow, purple, green)
+  - Clean layout with proper margins and well-positioned legend
+  - Good use of hovertemplate for interactive exploration in HTML output
+  - White marker borders provide visual distinction for overlapping points
+  - Realistic business context (regional product performance)
+  - Proper title format following pyplots.ai conventions
+  weaknesses:
+  - Grid alpha at 0.1 is perhaps too subtle; 0.2-0.3 would provide better reference
+    without being distracting
+  - Legend border is minimal but could be removed entirely for cleaner look
+  - Some sales growth values exceed 100% which is mathematically possible but unusual