feat(bokeh): implement line-timeseries-rolling

[github-actions]

Implementation: line-timeseries-rolling - bokeh

Implements the bokeh version of line-timeseries-rolling.

File: plots/line-timeseries-rolling/implementations/bokeh.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a time series visualization of daily temperature data spanning January 2024 to January 2025. A semi-transparent blue line shows raw daily temperature readings with visible day-to-day noise/volatility. A prominent smooth yellow/gold line overlays the raw data showing the 30-day rolling average. The visualization clearly demonstrates a seasonal temperature pattern, with values starting around 5-10°C in January, rising to peak around 35°C in July (summer), then declining back toward 0-5°C by December. The title "line-timeseries-rolling · bokeh · pyplots.ai" appears in the top left. A legend distinguishes "Raw Data" (blue) from "30-Day Rolling Average" (yellow). The x-axis shows month labels (Jan 2024 through Jan 2025), and the y-axis displays "Temperature (°C)" ranging from 0 to ~45. A subtle grid with dashed lines aids readability. The rolling average line is shorter at both ends due to the centered window calculation.

Quality Score: 92/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (9/10) - Title, axis labels, and tick marks are readable; legend text could be slightly larger
• VQ-02: No Overlap (8/8) - No overlapping text elements
• VQ-03: Element Visibility (7/8) - Lines well-sized; raw data alpha=0.5 appropriate for density; rolling avg line prominent
• VQ-04: Color Accessibility (5/5) - Blue/yellow contrast is colorblind-safe (not red-green)
• VQ-05: Layout Balance (5/5) - Plot fills canvas well with balanced margins
• VQ-06: Axis Labels (2/2) - "Temperature (°C)" and "Date" with units
• VQ-07: Grid & Legend (0/2) - Grid is subtle (alpha=0.3), but legend labels appear quite small relative to canvas size

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct time series line plot with rolling average overlay
• SC-02: Data Mapping (5/5) - Dates on X-axis, temperature values on Y-axis
• SC-03: Required Features (5/5) - Raw data line, rolling average line, legend with window size, grid lines
• SC-04: Data Range (3/3) - All data visible within axes
• SC-05: Legend Accuracy (2/2) - Legend correctly labels "Raw Data" and "30-Day Rolling Average"
• SC-06: Title Format (2/2) - Correct format: "line-timeseries-rolling · bokeh · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows seasonal trend, noise reduction, rolling avg shorter than raw data
• DQ-02: Realistic Context (7/7) - Daily temperature readings over a year is a perfect, neutral real-world scenario
• DQ-03: Appropriate Scale (4/5) - Temperature range 0-45°C is realistic; some values slightly exceed typical range

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Linear script: imports → data → plot → save
• CQ-02: Reproducibility (3/3) - np.random.seed(42) used
• CQ-03: Clean Imports (2/2) - All imports used
• CQ-04: No Deprecated API (1/1) - Uses current Bokeh API
• CQ-05: Output Correct (1/1) - Saves as plot.png and plot.html

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Uses ColumnDataSource properly, interactive tools, HTML output; could leverage HoverTool for showing exact values

Strengths

• Excellent visual distinction between raw data (blue, semi-transparent) and rolling average (yellow, prominent)
• Realistic temperature scenario with clear seasonal pattern that demonstrates the value of rolling averages
• Proper handling of NaN values at rolling window boundaries by creating separate data sources
• Interactive tools included (pan, wheel_zoom, box_zoom, reset, save) and HTML output generated
• Clean KISS code structure following Bokeh best practices with ColumnDataSource

Weaknesses

• Legend text appears small at the top left corner when viewing the full-resolution image
• Could add HoverTool to display exact date and temperature values on hover for better interactivity

Verdict: APPROVED