update(bump-basic): plotnine — comprehensive quality review (#4336)

## Summary

Updated **plotnine** implementation for **bump-basic**.

### Changes
- Switched from scale_color_brewer to scale_color_manual for controlled
palette
- Added element_blank, element_line, element_rect for refined theming
- Cleaner data construction
- Quality self-assessment: 93/100

## Test Plan

- [x] Preview images uploaded to GCS staging
- [x] Implementation file passes ruff format/check
- [x] Metadata YAML updated with current versions
- [ ] Automated review triggered

---
Generated with [Claude Code](https://claude.com/claude-code) `/update`
command

---------

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>

Author: MarkusNeusinger

plots/bump-basic/implementations/plotnine.py

@@ -1,88 +1,123 @@
 """ pyplots.ai
 bump-basic: Basic Bump Chart
-Library: plotnine 0.15.2 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-23
+Library: plotnine 0.15.3 | Python 3.14.3
+Quality: 94/100 | Updated: 2026-02-22
 """
 
 import pandas as pd
 from plotnine import (
     aes,
+    element_blank,
+    element_line,
+    element_rect,
     element_text,
     geom_line,
     geom_point,
     geom_text,
     ggplot,
     labs,
-    scale_color_brewer,
+    scale_color_manual,
     scale_x_continuous,
     scale_y_reverse,
     theme,
     theme_minimal,
 )
 
 
-# Data - Tech company rankings over 6 quarters
-data = {
-    "entity": ["Alpha Corp"] * 6 + ["Beta Inc"] * 6 + ["Gamma Tech"] * 6 + ["Delta Systems"] * 6 + ["Epsilon Labs"] * 6,
-    "period": ["Q1", "Q2", "Q3", "Q4", "Q5", "Q6"] * 5,
-    "period_num": [1, 2, 3, 4, 5, 6] * 5,
-    "rank": [
-        1,
-        1,
-        2,
-        2,
-        1,
-        1,  # Alpha Corp - starts strong, slight dip, recovers
-        2,
-        3,
-        1,
-        1,
-        2,
-        3,  # Beta Inc - rises to top mid-year, then falls
-        3,
-        2,
-        3,
-        4,
-        4,
-        2,  # Gamma Tech - volatile movement
-        4,
-        4,
-        4,
-        3,
-        3,
-        4,  # Delta Systems - stable middle performer
-        5,
-        5,
-        5,
-        5,
-        5,
-        5,  # Epsilon Labs - consistently last
-    ],
+# Data - Streaming platform market share rankings over 8 quarters
+platforms = ["StreamVue", "WavePlay", "CloudCast", "PixelFlix", "SonicNet", "EchoTV"]
+quarters = ["Q1'24", "Q2'24", "Q3'24", "Q4'24", "Q1'25", "Q2'25", "Q3'25", "Q4'25"]
+n_periods = len(quarters)
+
+rankings = {
+    "StreamVue": [1, 1, 1, 2, 2, 3, 3, 4],
+    "WavePlay": [2, 3, 3, 1, 1, 1, 1, 1],
+    "CloudCast": [4, 2, 2, 3, 3, 2, 2, 2],
+    "PixelFlix": [3, 4, 4, 4, 5, 5, 4, 3],
+    "SonicNet": [5, 5, 5, 5, 4, 4, 5, 5],
+    "EchoTV": [6, 6, 6, 6, 6, 6, 6, 6],
 }
-df = pd.DataFrame(data)
+
+rows = []
+for platform, ranks in rankings.items():
+    for i, rank in enumerate(ranks):
+        rows.append({"platform": platform, "quarter": quarters[i], "qnum": i + 1, "rank": rank})
+df = pd.DataFrame(rows)
 
 # Subset for end labels
-df_end = df[df["period_num"] == 6].copy()
+df_end = df[df["qnum"] == n_periods].copy()
+
+# Visual hierarchy: protagonist entities vs supporting cast
+protagonists = ["StreamVue", "WavePlay"]
+supporting = ["CloudCast", "PixelFlix", "SonicNet", "EchoTV"]
+
+df_hero = df[df["platform"].isin(protagonists)]
+df_support = df[df["platform"].isin(supporting)]
+
+# Crossover emphasis at Q4'24 (qnum=4) where WavePlay overtakes StreamVue
+df_crossover = pd.DataFrame(
+    [{"qnum": 4, "rank": 1, "platform": "WavePlay"}, {"qnum": 4, "rank": 2, "platform": "StreamVue"}]
+)
+
+# Colorblind-safe palette — Python Blue first, warm orange for WavePlay
+# Replaced red with teal (#17becf) for deuteranopia safety
+palette = {
+    "StreamVue": "#306998",
+    "WavePlay": "#e8963e",
+    "CloudCast": "#59a14f",
+    "PixelFlix": "#17becf",
+    "SonicNet": "#9d7660",
+    "EchoTV": "#bab0ac",
+}
 
-# Plot
+# Plot — layered for visual hierarchy
 plot = (
-    ggplot(df, aes(x="period_num", y="rank", color="entity", group="entity"))
-    + geom_line(size=2.5, alpha=0.8)
-    + geom_point(size=6)
-    + geom_text(aes(label="entity"), data=df_end, nudge_x=0.3, ha="left", size=12)
-    + scale_y_reverse(breaks=[1, 2, 3, 4, 5])
-    + scale_x_continuous(breaks=[1, 2, 3, 4, 5, 6], labels=["Q1", "Q2", "Q3", "Q4", "Q5", "Q6"], limits=(0.5, 7.5))
-    + scale_color_brewer(type="qual", palette="Set2")
-    + labs(x="Quarter", y="Rank", title="bump-basic · plotnine · pyplots.ai", color="Company")
+    ggplot(df, aes(x="qnum", y="rank", color="platform", group="platform"))
+    # Supporting lines: thinner, more transparent
+    + geom_line(data=df_support, size=1.8, alpha=0.4)
+    + geom_point(data=df_support, size=4, stroke=0.6, fill="white")
+    + geom_point(data=df_support, size=2.5, alpha=0.5)
+    # Protagonist lines: bold and saturated
+    + geom_line(data=df_hero, size=3.5, alpha=0.95)
+    + geom_point(data=df_hero, size=7, stroke=1.0, fill="white")
+    + geom_point(data=df_hero, size=4.5)
+    # Crossover emphasis at Q4'24
+    + geom_point(data=df_crossover, size=12, alpha=0.15)
+    # End labels — bold for protagonists, italic for supporting
+    + geom_text(
+        aes(label="platform"),
+        data=df_end[df_end["platform"].isin(protagonists)],
+        nudge_x=0.35,
+        ha="left",
+        size=13,
+        fontweight="bold",
+    )
+    + geom_text(
+        aes(label="platform"),
+        data=df_end[df_end["platform"].isin(supporting)],
+        nudge_x=0.35,
+        ha="left",
+        size=11,
+        fontstyle="italic",
+        alpha=0.7,
+    )
+    + scale_y_reverse(breaks=range(1, len(platforms) + 1))
+    + scale_x_continuous(breaks=range(1, n_periods + 1), labels=quarters, limits=(0.5, n_periods + 2))
+    + scale_color_manual(values=palette)
+    + labs(x="Quarter", y="Market Share Ranking", title="bump-basic · plotnine · pyplots.ai")
     + theme_minimal()
     + theme(
         figure_size=(16, 9),
-        text=element_text(size=14),
-        axis_title=element_text(size=20),
-        axis_text=element_text(size=16),
-        plot_title=element_text(size=24),
-        legend_text=element_text(size=16),
-        legend_title=element_text(size=18),
+        text=element_text(size=14, color="#3c3c3c"),
+        axis_title=element_text(size=20, color="#555555"),
+        axis_text=element_text(size=16, color="#666666"),
+        axis_text_x=element_text(rotation=0),
+        plot_title=element_text(size=24, weight="bold", color="#2b2b2b"),
+        panel_grid_major_x=element_blank(),
+        panel_grid_minor=element_blank(),
+        panel_grid_major_y=element_line(alpha=0.15, size=0.4, color="#cccccc"),
+        panel_background=element_rect(fill="white", color="none"),
+        plot_background=element_rect(fill="#fafafa", color="none"),
         legend_position="none",
     )
 )