feat(plotly): implement histogram-cumulative (#2571)

## Implementation: `histogram-cumulative` - plotly

Implements the **plotly** version of `histogram-cumulative`.

**File:** `plots/histogram-cumulative/implementations/plotly.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20593348147)*

---------

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/histogram-cumulative/implementations/plotly.py

@@ -0,0 +1,121 @@
+""" pyplots.ai
+histogram-cumulative: Cumulative Histogram
+Library: plotly 6.5.0 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import plotly.graph_objects as go
+
+
+# Data: Simulated test scores with realistic distribution
+np.random.seed(42)
+scores = np.concatenate(
+    [
+        np.random.normal(65, 10, 300),  # Average performers
+        np.random.normal(85, 5, 150),  # High performers
+        np.random.normal(45, 8, 50),  # Low performers
+    ]
+)
+scores = np.clip(scores, 0, 100)  # Keep scores in valid range
+
+# Calculate cumulative histogram
+bin_count = 25
+counts, bin_edges = np.histogram(scores, bins=bin_count)
+cumulative_counts = np.cumsum(counts)
+cumulative_proportion = cumulative_counts / len(scores)
+
+# Use bin centers for x-axis
+bin_centers = (bin_edges[:-1] + bin_edges[1:]) / 2
+
+# Create figure
+fig = go.Figure()
+
+# Add cumulative histogram as step line
+fig.add_trace(
+    go.Scatter(
+        x=bin_edges[1:],  # Right edge of each bin
+        y=cumulative_proportion,
+        mode="lines",
+        line=dict(
+            color="#306998",  # Python Blue
+            width=4,
+            shape="hv",  # Step function (horizontal then vertical)
+        ),
+        fill="tozeroy",
+        fillcolor="rgba(48, 105, 152, 0.3)",
+        name="Cumulative Distribution",
+        hovertemplate="Score ≤ %{x:.1f}<br>Proportion: %{y:.2%}<extra></extra>",
+    )
+)
+
+# Add reference lines for key percentiles
+percentiles = [0.25, 0.50, 0.75]
+percentile_labels = ["25th", "50th (Median)", "75th"]
+for p, label in zip(percentiles, percentile_labels):
+    x_val = np.percentile(scores, p * 100)
+    fig.add_trace(
+        go.Scatter(
+            x=[x_val, x_val],
+            y=[0, p],
+            mode="lines",
+            line=dict(color="#FFD43B", width=2, dash="dash"),  # Python Yellow
+            showlegend=False,
+            hoverinfo="skip",
+        )
+    )
+    fig.add_trace(
+        go.Scatter(
+            x=[0, x_val],
+            y=[p, p],
+            mode="lines",
+            line=dict(color="#FFD43B", width=2, dash="dash"),
+            showlegend=False,
+            hoverinfo="skip",
+        )
+    )
+
+# Add percentile annotations
+fig.add_trace(
+    go.Scatter(
+        x=[np.percentile(scores, 25), np.percentile(scores, 50), np.percentile(scores, 75)],
+        y=[0.25, 0.50, 0.75],
+        mode="markers+text",
+        marker=dict(color="#FFD43B", size=14, line=dict(color="#306998", width=2)),
+        text=["25%", "50%", "75%"],
+        textposition="top right",
+        textfont=dict(size=16, color="#306998"),
+        showlegend=False,
+        hovertemplate="%{text} of scores ≤ %{x:.1f}<extra></extra>",
+    )
+)
+
+# Update layout
+fig.update_layout(
+    title=dict(text="histogram-cumulative · plotly · pyplots.ai", font=dict(size=28), x=0.5, xanchor="center"),
+    xaxis=dict(
+        title=dict(text="Test Score (points)", font=dict(size=22)),
+        tickfont=dict(size=18),
+        range=[0, 105],
+        showgrid=True,
+        gridcolor="rgba(0,0,0,0.1)",
+        gridwidth=1,
+    ),
+    yaxis=dict(
+        title=dict(text="Cumulative Proportion", font=dict(size=22)),
+        tickfont=dict(size=18),
+        tickformat=".0%",
+        range=[0, 1.05],
+        showgrid=True,
+        gridcolor="rgba(0,0,0,0.1)",
+        gridwidth=1,
+    ),
+    template="plotly_white",
+    showlegend=True,
+    legend=dict(x=0.02, y=0.98, font=dict(size=16), bgcolor="rgba(255,255,255,0.8)"),
+    margin=dict(l=80, r=40, t=80, b=80),
+)
+
+# Save outputs
+fig.write_image("plot.png", width=1600, height=900, scale=3)
+fig.write_html("plot.html", include_plotlyjs=True, full_html=True)

plots/histogram-cumulative/metadata/plotly.yaml

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+library: plotly
+specification_id: histogram-cumulative
+created: '2025-12-30T09:31:29Z'
+updated: '2025-12-30T09:40:27Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20593348147
+issue: 0
+python_version: 3.13.11
+library_version: 6.5.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/histogram-cumulative/plotly/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/histogram-cumulative/plotly/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/histogram-cumulative/plotly/plot.html
+quality_score: 92
+review:
+  strengths:
+  - Excellent visual design with clear step function representation of cumulative
+    distribution
+  - Thoughtful addition of percentile reference lines (25th, 50th, 75th) with dashed
+    yellow styling that enhances understanding
+  - Custom hover templates provide informative tooltips showing exact proportions
+  - Proper use of shape=hv for authentic step function appearance
+  - Good color scheme using Python Blue and Yellow with appropriate contrast
+  weaknesses:
+  - Uses manual histogram calculation with np.histogram instead of Plotly native go.Histogram
+    with cumulative_enabled=True
+  - Legend position in upper-left could be moved to avoid potential visual overlap