update(area-basic): seaborn — comprehensive quality review

plots/area-basic/implementations/seaborn.py

@@ -1,7 +1,7 @@
 """ pyplots.ai
 area-basic: Basic Area Chart
-Library: seaborn 0.13.2 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-23
+Library: seaborn 0.13.2 | Python 3.14.2
+Quality: 98/100 | Created: 2025-12-23
 """
 
 import matplotlib.pyplot as plt
@@ -14,34 +14,48 @@
 np.random.seed(42)
 dates = pd.date_range(start="2024-01-01", periods=30, freq="D")
 
-# Simulate realistic web traffic with weekly pattern and trend
+# Simulate realistic web traffic with weekly pattern, trend, and a traffic spike
 base_visitors = 5000
 trend = np.linspace(0, 1500, 30)
 weekly_pattern = np.array([1.0, 1.1, 1.15, 1.2, 1.1, 0.7, 0.65] * 5)[:30]
 noise = np.random.randn(30) * 300
 visitors = (base_visitors + trend) * weekly_pattern + noise
-visitors = np.maximum(visitors, 1000)  # Ensure positive values
+visitors[17] *= 1.45  # Traffic spike from a viral post on day 18
+visitors = np.maximum(visitors, 1000)
 
 df = pd.DataFrame({"date": dates, "visitors": visitors})
 
-# Plot
+# Plot - seaborn styling and theme
+sns.set_style("whitegrid", {"grid.linestyle": "--", "grid.alpha": 0.3})
+sns.set_context("talk", font_scale=1.1)
+
 fig, ax = plt.subplots(figsize=(16, 9))
 
-# Area fill with semi-transparent Python Blue
+# Area chart using seaborn lineplot with fill
+sns.lineplot(data=df, x="date", y="visitors", ax=ax, color="#306998", linewidth=3, label="Daily visitors")
 ax.fill_between(df["date"], df["visitors"], alpha=0.4, color="#306998")
 
-# Line on top using seaborn
-sns.lineplot(data=df, x="date", y="visitors", ax=ax, color="#306998", linewidth=3)
+# Annotate the traffic spike
+spike_idx = 17
+ax.annotate(
+    "Viral post",
+    xy=(df["date"].iloc[spike_idx], df["visitors"].iloc[spike_idx]),
+    xytext=(df["date"].iloc[spike_idx - 6], df["visitors"].iloc[spike_idx] * 1.0),
+    fontsize=16,
+    color="#1a3a5c",
+    arrowprops={"arrowstyle": "->", "color": "#1a3a5c", "lw": 2},
+    ha="center",
+)
 
 # Style
 ax.set_xlabel("Date", fontsize=20)
 ax.set_ylabel("Visitors (count)", fontsize=20)
 ax.set_title("area-basic · seaborn · pyplots.ai", fontsize=24)
 ax.tick_params(axis="both", labelsize=16)
-ax.grid(True, alpha=0.3, linestyle="--")
+ax.legend(fontsize=16, loc="upper left", framealpha=0.9)
 
-# Set y-axis to start at 0 to emphasize area magnitude
-ax.set_ylim(bottom=0)
+# Set y-axis to start at 0, cap top to reduce whitespace
+ax.set_ylim(bottom=0, top=df["visitors"].max() * 1.12)
 
 # Format x-axis dates
 fig.autofmt_xdate(rotation=45)

plots/area-basic/metadata/seaborn.yaml

@@ -1,98 +1,104 @@
 library: seaborn
 specification_id: area-basic
 created: '2025-12-23T00:47:02Z'
-updated: '2025-12-23T00:51:01Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-11T22:26:29Z'
+generated_by: claude-opus-4-6
 workflow_run: 20447957405
 issue: 0
-python_version: 3.13.11
+python_version: 3.14.2
 library_version: 0.13.2
 preview_url: https://storage.googleapis.com/pyplots-images/plots/area-basic/seaborn/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/area-basic/seaborn/plot_thumb.png
 preview_html: null
-quality_score: 91
+quality_score: 98
 impl_tags:
   dependencies: []
-  techniques: []
+  techniques:
+  - annotations
   patterns:
-    - data-generation
-    - explicit-figure
+  - data-generation
+  - explicit-figure
   dataprep:
-    - time-series
+  - time-series
   styling:
-    - alpha-blending
-    - grid-styling
+  - alpha-blending
+  - grid-styling
 review:
   strengths:
-  - Excellent visual design with proper font sizes, color choices, and layout
-  - Realistic website traffic data with weekly patterns and upward trend effectively
-    demonstrates the area chart strength in showing magnitude over time
-  - Correct title format and axis labels with units
-  - Proper use of semi-transparent fill (alpha 0.4) as recommended in spec
-  - Y-axis starting at 0 correctly emphasizes the cumulative magnitude
+  - Excellent data generation with realistic weekly patterns, upward trend, and a
+    viral post spike — makes the area chart compelling and informative
+  - Clean annotation with arrow pointing to the traffic spike adds storytelling value
+  - Proper use of seaborn theming (whitegrid style, talk context) provides a polished,
+    professional look
+  - Semi-transparent fill at alpha 0.4 balances visual weight with readability
+  - Y-axis starting at 0 correctly emphasizes the volume aspect of the area chart
   weaknesses:
-  - The implementation uses matplotlib fill_between for the area rather than exploring
-    seaborn native capabilities (though seaborn lacks a dedicated area chart function)
-  - 'Grid legend scoring: single series plots could benefit from a subtle annotation
-    or data source note'
-  image_description: The plot displays a basic area chart showing website visitors
-    over time (January 2024). The chart uses a semi-transparent blue fill (#306998
-    Python Blue at alpha 0.4) with a darker blue line (linewidth 3) on top. The x-axis
-    shows dates from 2024-01-01 to 2024-01-29 with rotated labels at 45 degrees. The
-    y-axis shows visitor counts from 0 to approximately 7500. The title "area-basic
-    · seaborn · pyplots.ai" appears at the top. A clear weekly pattern is visible
-    with dips on weekends (lower traffic) and peaks mid-week. There's also an overall
-    upward trend. The gridlines are subtle with alpha 0.3 and dashed style.
+  - The fill_between call is pure matplotlib rather than a seaborn-native feature
+    — though this is unavoidable since seaborn lacks a dedicated area chart function
+  image_description: The plot displays a basic area chart showing daily website visitors
+    over January 2024 (30 days). A single blue (#306998) line traces the visitor count
+    with the area below filled in a semi-transparent blue (alpha ~0.4). The y-axis
+    starts at 0 and extends to approximately 11,200 with label "Visitors (count)".
+    The x-axis shows dates from 2024-01-01 to 2024-01-30, with labels rotated 45°
+    for readability. A clear weekly cyclic pattern is visible — peaks mid-week around
+    6,000-7,000 and dips on weekends to ~3,500-4,000. An upward trend is apparent
+    over the month. A notable traffic spike around January 18 reaches ~10,300 visitors,
+    annotated with "Viral post" and an arrow pointing to the peak. The background
+    uses a whitegrid style with dashed gridlines at low opacity. A legend in the upper
+    left shows "Daily visitors". The title reads "area-basic · seaborn · pyplots.ai"
+    in the correct format.
   criteria_checklist:
     visual_quality:
-      score: 37
+      score: 40
       max: 40
       items:
       - id: VQ-01
         name: Text Legibility
         score: 10
         max: 10
         passed: true
-        comment: Title at fontsize 24, axis labels at 20, tick labels at 16, all perfectly
-          readable
+        comment: Title 24pt, labels 20pt, ticks 16pt — all perfectly readable at full
+          resolution
       - id: VQ-02
         name: No Overlap
         score: 8
         max: 8
         passed: true
-        comment: No overlapping text, date labels are rotated to avoid collision
+        comment: Date labels rotated 45°, annotation clear of other elements, legend
+          in upper left
       - id: VQ-03
         name: Element Visibility
         score: 8
         max: 8
         passed: true
-        comment: Line width of 3 is optimal, area fill at alpha 0.4 shows magnitude
-          clearly
+        comment: Line width 3 appropriate for 30 data points, fill alpha 0.4 gives
+          good visual weight
       - id: VQ-04
         name: Color Accessibility
         score: 5
         max: 5
         passed: true
-        comment: Single color scheme (Python Blue), colorblind-safe
+        comment: Single blue color series, no colorblind concerns
       - id: VQ-05
         name: Layout Balance
-        score: 4
+        score: 5
         max: 5
         passed: true
-        comment: Good proportions, slight excess whitespace at top
+        comment: Plot fills canvas well, balanced margins, y-axis starting at 0 gives
+          proper area emphasis
       - id: VQ-06
         name: Axis Labels
         score: 2
         max: 2
         passed: true
-        comment: '"Date" and "Visitors (count)" - descriptive with units'
+        comment: Date and Visitors (count) — descriptive with units
       - id: VQ-07
         name: Grid & Legend
-        score: 0
+        score: 2
         max: 2
         passed: true
-        comment: Grid is good (alpha 0.3), but no legend present (single series, acceptable
-          but not ideal)
+        comment: Dashed grid at alpha 0.3 is subtle, legend well-placed with framealpha
+          0.9
     spec_compliance:
       score: 25
       max: 25
@@ -108,102 +114,101 @@ review:
         score: 5
         max: 5
         passed: true
-        comment: X=datetime (dates), Y=numeric (visitors) correctly assigned
+        comment: X = dates (continuous time), Y = visitors (numeric magnitude)
       - id: SC-03
         name: Required Features
         score: 5
         max: 5
         passed: true
-        comment: Semi-transparent fill (alpha 0.4), gridlines, clear axis labels all
-          present
+        comment: Semi-transparent fill (alpha 0.4), gridlines present, clear axis
+          labels with units
       - id: SC-04
         name: Data Range
         score: 3
         max: 3
         passed: true
-        comment: Y-axis starts at 0 (emphasizes area magnitude), all data visible
+        comment: Y starts at 0, all 30 data points visible within axes
       - id: SC-05
         name: Legend Accuracy
         score: 2
         max: 2
         passed: true
-        comment: Single series, no legend needed
+        comment: Daily visitors matches data correctly
       - id: SC-06
         name: Title Format
         score: 2
         max: 2
         passed: true
-        comment: Uses correct format "area-basic · seaborn · pyplots.ai"
+        comment: area-basic · seaborn · pyplots.ai in correct format
     data_quality:
-      score: 17
+      score: 20
       max: 20
       items:
       - id: DQ-01
         name: Feature Coverage
-        score: 6
+        score: 8
         max: 8
         passed: true
-        comment: Shows weekly pattern and upward trend, demonstrates magnitude emphasis
-          well, but could show more variety (e.g., occasional anomalies)
+        comment: Shows upward trend, weekly cyclic pattern, traffic spike, noise —
+          demonstrates area chart volume emphasis
       - id: DQ-02
         name: Realistic Context
         score: 7
         max: 7
         passed: true
-        comment: Daily website visitors over a month is a perfect real-world scenario
+        comment: Website traffic with realistic weekly patterns (weekend dips), neutral
+          topic
       - id: DQ-03
         name: Appropriate Scale
-        score: 4
+        score: 5
         max: 5
         passed: true
-        comment: Values 3000-7500 are realistic for website traffic, though starting
-          y at 0 adds some empty space
+        comment: 3,000–10,000 daily visitors plausible for mid-sized site, 1.45x spike
+          realistic
     code_quality:
-      score: 9
+      score: 10
       max: 10
       items:
       - id: CQ-01
         name: KISS Structure
         score: 3
         max: 3
         passed: true
-        comment: Clean imports → data → plot → save structure, no functions/classes
+        comment: Clean Imports → Data → Plot → Save flow, no functions/classes
       - id: CQ-02
         name: Reproducibility
         score: 3
         max: 3
         passed: true
-        comment: Uses np.random.seed(42)
+        comment: np.random.seed(42) set
       - id: CQ-03
         name: Clean Imports
         score: 2
         max: 2
         passed: true
-        comment: All imports are used (matplotlib, numpy, pandas, seaborn)
+        comment: All four imports (matplotlib, numpy, pandas, seaborn) are used
       - id: CQ-04
         name: No Deprecated API
-        score: 0
+        score: 1
         max: 1
         passed: true
-        comment: 'Minor: Uses ax.fill_between from matplotlib instead of seaborn-native
-          approach'
+        comment: No deprecated functions
       - id: CQ-05
         name: Output Correct
         score: 1
         max: 1
         passed: true
-        comment: Saves as plot.png with dpi=300
+        comment: Saves as plot.png at dpi=300
     library_features:
       score: 3
       max: 5
       items:
       - id: LF-01
-        name: Uses distinctive library features
+        name: Distinctive Features
         score: 3
         max: 5
         passed: true
-        comment: Uses sns.lineplot which is seaborn-native, but the area fill uses
-          matplotlib's ax.fill_between. Seaborn doesn't have a native area chart function,
-          so this hybrid approach is acceptable but doesn't showcase seaborn's distinctive
-          features like regplot, kdeplot, or statistical aggregation.
+        comment: Good use of sns.set_style, sns.set_context, and sns.lineplot. Area
+          fill uses matplotlib fill_between since seaborn lacks native area chart
+          function.
   verdict: APPROVED