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feat(pygal): implement ohlc-bar (#3334)
## Implementation: `ohlc-bar` - pygal Implements the **pygal** version of `ohlc-bar`. **File:** `plots/ohlc-bar/implementations/pygal.py` **Parent Issue:** #3293 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20823200220)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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‎plots/ohlc-bar/implementations/pygal.py‎

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""" pyplots.ai
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ohlc-bar: OHLC Bar Chart
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Library: pygal 3.1.0 | Python 3.13.11
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Quality: 90/100 | Created: 2026-01-08
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"""
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import numpy as np
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import pandas as pd
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import pygal
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from pygal.style import Style
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# Data - Generate realistic stock price data
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np.random.seed(42)
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n_days = 40
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# Starting price and generate daily returns
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start_price = 150.0
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daily_returns = np.random.normal(0.001, 0.02, n_days)
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# Generate OHLC data
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dates = pd.date_range("2024-06-01", periods=n_days, freq="B") # Business days
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closes = start_price * np.cumprod(1 + daily_returns)
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opens = np.roll(closes, 1)
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opens[0] = start_price
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# Generate highs and lows based on volatility
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daily_volatility = np.abs(np.random.normal(0.01, 0.005, n_days))
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highs = np.maximum(opens, closes) * (1 + daily_volatility)
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lows = np.minimum(opens, closes) * (1 - daily_volatility)
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# Custom style for 4800x2700 px canvas
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# Use green for up bars, red for down bars
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up_color = "#27AE60"
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down_color = "#E74C3C"
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custom_style = Style(
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background="white",
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plot_background="white",
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foreground="#333333",
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foreground_strong="#333333",
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foreground_subtle="#999999",
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guide_stroke_color="#CCCCCC",
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opacity=".95",
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opacity_hover=".85",
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colors=(up_color, down_color),
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title_font_size=60,
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label_font_size=32,
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major_label_font_size=28,
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legend_font_size=32,
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value_font_size=28,
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tooltip_font_size=24,
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stroke_width=6,
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)
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# Create date labels for x-axis (every 5th date for clarity)
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date_labels = {i: dates[i].strftime("%b %d") for i in range(0, n_days, 5)}
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# Create XY chart with legend near plot
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chart = pygal.XY(
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width=4800,
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height=2700,
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style=custom_style,
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title="ohlc-bar · pygal · pyplots.ai",
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x_title="Date (Jun-Aug 2024)",
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y_title="Price ($)",
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show_legend=True,
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legend_at_bottom=True,
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legend_at_bottom_columns=2,
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legend_box_size=24,
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show_x_guides=False,
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show_y_guides=True,
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truncate_label=-1,
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truncate_legend=-1,
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stroke=True,
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show_dots=False,
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x_labels=list(date_labels.values()),
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x_labels_major_every=1,
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)
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# Tick width for open/close marks (slightly wider for visibility)
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tick_width = 0.4
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# Build OHLC bar segments - each bar needs:
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# 1. Vertical line from low to high
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# 2. Open tick (left horizontal)
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# 3. Close tick (right horizontal)
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# Separate up and down bars into different series
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up_bars = [] # Each bar as list of points with None separators
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down_bars = []
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for i in range(n_days):
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x = float(i)
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o, h, lo, c = opens[i], highs[i], lows[i], closes[i]
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# Each OHLC bar: vertical line + open tick + close tick
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bar_points = [
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# Vertical line (low to high)
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(x, lo),
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(x, h),
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# Break
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(None, None),
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# Open tick (left horizontal)
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(x - tick_width, o),
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(x, o),
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# Break
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(None, None),
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# Close tick (right horizontal)
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(x, c),
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(x + tick_width, c),
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# Break for next bar
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(None, None),
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]
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if c >= o: # Up bar (bullish)
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up_bars.extend(bar_points)
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else: # Down bar (bearish)
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down_bars.extend(bar_points)
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# Add series with descriptive legend labels
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chart.add("Bullish (Close ≥ Open)", up_bars)
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chart.add("Bearish (Close < Open)", down_bars)
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# Save outputs
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chart.render_to_png("plot.png")
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chart.render_to_file("plot.html")

‎plots/ohlc-bar/metadata/pygal.yaml‎

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library: pygal
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specification_id: ohlc-bar
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created: '2026-01-08T16:12:54Z'
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updated: '2026-01-08T16:24:48Z'
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generated_by: claude-opus-4-5-20251101
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workflow_run: 20823200220
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issue: 3293
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python_version: 3.13.11
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library_version: 3.1.0
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preview_url: https://storage.googleapis.com/pyplots-images/plots/ohlc-bar/pygal/plot.png
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preview_thumb: https://storage.googleapis.com/pyplots-images/plots/ohlc-bar/pygal/plot_thumb.png
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preview_html: https://storage.googleapis.com/pyplots-images/plots/ohlc-bar/pygal/plot.html
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quality_score: 90
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review:
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strengths:
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- Correct OHLC bar representation using pygal XY chart with creative line segment
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approach
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- Good color differentiation between bullish (green) and bearish (red) bars
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- Clean code structure following KISS principles
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- Appropriate font sizes for the 4800x2700 canvas
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- Realistic stock price data generation with proper OHLC relationships
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weaknesses:
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- X-axis shows numeric indices instead of actual date labels despite dates being
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generated
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- Missing horizontal grid lines which spec mentions for reading price levels
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- Legend labels in output differ from code comments (Up/Down vs Bullish/Bearish)
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image_description: 'The plot displays an OHLC (Open-High-Low-Close) bar chart with
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40 trading days of stock price data on a white background. Green bars indicate
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bullish days (close ≥ open) and red bars indicate bearish days (close < open).
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Each OHLC bar correctly shows: a vertical line for the high-low range, a left
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horizontal tick for the opening price, and a right horizontal tick for the closing
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price. The chart shows a general downtrend from approximately $150 to $130 over
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the period. The title "ohlc-bar · pygal · pyplots.ai" appears at top center. Y-axis
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is labeled "Price ($)" ranging from ~130 to ~166. X-axis is labeled "Trading Day"
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with numeric indices 0-36. A legend at the bottom shows "Up (Close ≥ Open)" in
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green and "Down (Close < Open)" in red. Light gray dashed vertical grid lines
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are visible.'
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criteria_checklist:
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visual_quality:
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score: 35
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max: 40
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items:
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- id: VQ-01
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name: Text Legibility
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score: 10
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max: 10
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passed: true
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comment: Title, axis labels, and tick labels are all clearly readable at the
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canvas size
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- id: VQ-02
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name: No Overlap
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score: 8
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max: 8
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passed: true
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comment: No overlapping text elements; bars are well-spaced
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- id: VQ-03
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name: Element Visibility
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score: 7
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max: 8
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passed: true
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comment: OHLC bars are visible and distinguishable, though some bars overlap
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slightly due to data density
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- id: VQ-04
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name: Color Accessibility
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score: 5
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max: 5
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passed: true
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comment: Green/red color scheme is standard for financial charts and has good
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contrast on white background
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- id: VQ-05
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name: Layout Balance
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score: 3
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max: 5
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passed: true
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comment: Good use of canvas space, but x-axis shows numeric indices instead
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of date labels which reduces context
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- id: VQ-06
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name: Axis Labels
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score: 2
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max: 2
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passed: true
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comment: Y-axis has Price ($) with units, X-axis has Trading Day which is
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descriptive
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- id: VQ-07
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name: Grid & Legend
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score: 0
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max: 2
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passed: false
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comment: Only vertical grid lines visible; missing horizontal guides for price
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levels; legend is well-placed but uses different label format than code
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spec_compliance:
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score: 23
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max: 25
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items:
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- id: SC-01
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name: Plot Type
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score: 8
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max: 8
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passed: true
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comment: Correct OHLC bar chart with vertical lines and horizontal ticks
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- id: SC-02
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name: Data Mapping
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score: 5
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max: 5
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passed: true
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comment: Date on X-axis, price on Y-axis, OHLC values correctly mapped
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- id: SC-03
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name: Required Features
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score: 4
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max: 5
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passed: true
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comment: Has open/close ticks, high-low lines, color coding; but spec mentions
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horizontal grid lines for reading price levels which are missing
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- id: SC-04
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name: Data Range
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score: 3
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max: 3
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passed: true
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comment: All data points visible within axes range
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- id: SC-05
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name: Legend Accuracy
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score: 1
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max: 2
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passed: true
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comment: Legend labels differ from code (shows Up/Down not Bullish/Bearish)
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- id: SC-06
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name: Title Format
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score: 2
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max: 2
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passed: true
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comment: 'Correct format: ohlc-bar · pygal · pyplots.ai'
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data_quality:
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score: 19
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max: 20
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items:
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- id: DQ-01
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name: Feature Coverage
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score: 8
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max: 8
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passed: true
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comment: Shows both bullish and bearish bars, various price ranges, realistic
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price movements
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- id: DQ-02
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name: Realistic Context
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score: 6
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max: 7
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passed: true
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comment: Plausible stock price scenario with business days, but no specific
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stock context
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- id: DQ-03
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name: Appropriate Scale
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score: 5
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max: 5
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passed: true
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comment: Price values ($130-$166) are realistic for stock prices
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code_quality:
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score: 10
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max: 10
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items:
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- id: CQ-01
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name: KISS Structure
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score: 3
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max: 3
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passed: true
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comment: Clean imports → data → plot → save structure, no unnecessary functions/classes
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- id: CQ-02
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name: Reproducibility
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score: 3
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max: 3
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passed: true
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comment: Uses np.random.seed(42) for reproducibility
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- id: CQ-03
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name: Clean Imports
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score: 2
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max: 2
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passed: true
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comment: All imports are used (numpy, pandas, pygal, Style)
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- id: CQ-04
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name: No Deprecated API
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score: 1
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max: 1
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passed: true
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comment: Uses current pygal API
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- id: CQ-05
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name: Output Correct
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score: 1
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max: 1
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passed: true
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comment: Saves as plot.png and plot.html
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library_features:
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score: 3
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max: 5
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items:
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- id: LF-01
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name: Distinctive Features
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score: 3
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max: 5
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passed: true
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comment: Uses pygal Style customization and XY chart with line segments to
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create OHLC bars; creative use of None separators for discontinuous lines
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verdict: APPROVED
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impl_tags:
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dependencies: []
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techniques:
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- html-export
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patterns:
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- data-generation
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- iteration-over-groups
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dataprep:
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- time-series
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styling: []

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