feat(plotly): implement bar-error

plots/bar-error/implementations/plotly.py

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+""" pyplots.ai
+bar-error: Bar Chart with Error Bars
+Library: plotly 6.5.0 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-27
+"""
+
+import numpy as np
+import plotly.graph_objects as go
+
+
+# Data - Lab experiment comparing treatment effectiveness
+np.random.seed(42)
+categories = ["Control", "Treatment A", "Treatment B", "Treatment C", "Treatment D"]
+values = np.array([45.2, 62.8, 58.3, 71.5, 55.9])
+# Asymmetric errors to show realistic experimental variation
+errors_lower = np.array([4.2, 5.8, 3.9, 6.1, 4.5])
+errors_upper = np.array([5.1, 7.2, 4.6, 8.3, 5.8])
+
+# Create figure
+fig = go.Figure()
+
+fig.add_trace(
+    go.Bar(
+        x=categories,
+        y=values,
+        marker=dict(color="#306998", line=dict(color="#1e4d6b", width=2)),
+        error_y=dict(
+            type="data",
+            symmetric=False,
+            array=errors_upper,
+            arrayminus=errors_lower,
+            color="#333333",
+            thickness=3,
+            width=12,  # Cap width
+        ),
+        name="Measurement",
+    )
+)
+
+# Layout for 4800x2700 px output
+fig.update_layout(
+    title=dict(
+        text="Lab Treatment Results · bar-error · plotly · pyplots.ai",
+        font=dict(size=32, color="#333333"),
+        x=0.5,
+        xanchor="center",
+    ),
+    xaxis=dict(title=dict(text="Treatment Group", font=dict(size=24)), tickfont=dict(size=20), showgrid=False),
+    yaxis=dict(
+        title=dict(text="Response Value (%)", font=dict(size=24)),
+        tickfont=dict(size=20),
+        gridcolor="rgba(0,0,0,0.1)",
+        gridwidth=1,
+        range=[0, 90],
+    ),
+    template="plotly_white",
+    showlegend=False,
+    margin=dict(l=100, r=80, t=120, b=100),
+    annotations=[
+        dict(
+            text="Error bars: ±1 SD (asymmetric)",
+            xref="paper",
+            yref="paper",
+            x=0.98,
+            y=0.98,
+            xanchor="right",
+            yanchor="top",
+            font=dict(size=18, color="#666666"),
+            showarrow=False,
+        )
+    ],
+)
+
+# Save as PNG (4800x2700 px) and HTML
+fig.write_image("plot.png", width=1600, height=900, scale=3)
+fig.write_html("plot.html", include_plotlyjs="cdn")

plots/bar-error/metadata/plotly.yaml

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+library: plotly
+specification_id: bar-error
+created: '2025-12-27T19:20:48Z'
+updated: '2025-12-27T19:25:46Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20543280389
+issue: 0
+python_version: 3.13.11
+library_version: 6.5.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/bar-error/plotly/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/bar-error/plotly/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/bar-error/plotly/plot.html
+quality_score: 92
+review:
+  strengths:
+  - Excellent visual clarity with well-sized text and properly styled error bars with
+    visible caps
+  - Perfect spec compliance including the required annotation explaining error bar
+    meaning
+  - Realistic lab experiment context that demonstrates the practical use case
+  - Clean KISS code structure following all conventions
+  - Asymmetric error bars correctly implemented showing realistic experimental variation
+  weaknesses:
+  - Legend is disabled (showlegend=False) - while the annotation works, a legend entry
+    would be more standard
+  - Could leverage Plotly hover templates to show exact values and error ranges on
+    interaction
+  - Error magnitude variation across groups is relatively uniform - more dramatic
+    differences would better showcase the feature