feat(letsplot): implement errorbar-asymmetric (#2814)

## Implementation: `errorbar-asymmetric` - letsplot

Implements the **letsplot** version of `errorbar-asymmetric`.

**File:** `plots/errorbar-asymmetric/implementations/letsplot.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20602452663)*

---------

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

Author: github-actions[bot]

plots/errorbar-asymmetric/implementations/letsplot.py

@@ -0,0 +1,60 @@
+""" pyplots.ai
+errorbar-asymmetric: Asymmetric Error Bars Plot
+Library: letsplot 4.8.2 | Python 3.13.11
+Quality: 93/100 | Created: 2025-12-30
+"""
+# ruff: noqa: F405
+
+import numpy as np
+import pandas as pd
+from lets_plot import *  # noqa: F403
+
+
+LetsPlot.setup_html()
+
+# Data - Quarterly sales performance with asymmetric confidence intervals
+np.random.seed(42)
+quarters = ["Q1", "Q2", "Q3", "Q4"]
+sales = [85, 92, 78, 105]  # Sales in thousands
+# Asymmetric errors: different upside/downside uncertainty
+error_lower = [8, 5, 12, 7]  # Lower error (downside risk)
+error_upper = [15, 18, 6, 22]  # Upper error (upside potential)
+
+df = pd.DataFrame(
+    {
+        "quarter": quarters,
+        "sales": sales,
+        "ymin": [s - el for s, el in zip(sales, error_lower, strict=True)],
+        "ymax": [s + eu for s, eu in zip(sales, error_upper, strict=True)],
+    }
+)
+
+# Plot
+plot = (
+    ggplot(df, aes(x="quarter", y="sales"))
+    + geom_point(size=6, color="#306998", alpha=0.9)
+    + geom_errorbar(aes(ymin="ymin", ymax="ymax"), width=0.3, size=1.5, color="#306998")
+    + labs(
+        x="Quarter",
+        y="Sales (thousands USD)",
+        title="errorbar-asymmetric · letsplot · pyplots.ai",
+        caption="Error bars represent 10th-90th percentile forecast range",
+    )
+    + scale_y_continuous(limits=[50, 140])
+    + theme_minimal()
+    + theme(
+        plot_title=element_text(size=24, face="bold"),
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+        plot_caption=element_text(size=14),
+        panel_grid_major=element_line(color="#cccccc", size=0.3),
+        panel_grid_minor=element_blank(),
+    )
+    + ggsize(1600, 900)
+)
+
+# Save
+ggsave(plot, "plot.png", scale=3, path=".")
+
+# Save HTML for interactive version
+ggsave(plot, "plot.html", path=".")

plots/errorbar-asymmetric/metadata/letsplot.yaml

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+library: letsplot
+specification_id: errorbar-asymmetric
+created: '2025-12-30T17:48:53Z'
+updated: '2025-12-30T17:57:28Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20602452663
+issue: 0
+python_version: 3.13.11
+library_version: 4.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/errorbar-asymmetric/letsplot/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/errorbar-asymmetric/letsplot/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/errorbar-asymmetric/letsplot/plot.html
+quality_score: 93
+review:
+  strengths:
+  - Excellent visual clarity with well-sized elements and readable text at all levels
+  - Clear demonstration of asymmetric error bars with visible caps
+  - Proper title format and informative caption explaining the error bounds
+  - Clean, KISS-compliant code structure following lets-plot conventions
+  - Good use of theme_minimal() with subtle grid customization
+  - Generates both PNG and HTML outputs as expected for lets-plot
+  weaknesses:
+  - The interactive HTML version does not include tooltips to show exact values on
+    hover
+  - Grid/Legend score reduced because there is no formal legend element (caption serves
+    the purpose but is not a legend)