feat(plotnine): implement bar-grouped

plots/bar-grouped/implementations/python/plotnine.py

@@ -1,12 +1,36 @@
-""" pyplots.ai
+""" anyplot.ai
 bar-grouped: Grouped Bar Chart
-Library: plotnine 0.15.2 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-24
+Library: plotnine 0.15.4 | Python 3.13.13
+Quality: 83/100 | Updated: 2026-05-06
 """
 
+import os
+
 import pandas as pd
-from plotnine import aes, element_text, geom_bar, ggplot, labs, position_dodge, scale_fill_manual, theme, theme_minimal
+from plotnine import (
+    aes,
+    element_line,
+    element_rect,
+    element_text,
+    geom_bar,
+    ggplot,
+    ggsave,
+    labs,
+    position_dodge,
+    scale_fill_manual,
+    theme,
+)
+
 
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+
+# Okabe-Ito palette (first series always #009E73)
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2"]
 
 # Data - Quarterly revenue by product line
 data = {
@@ -29,26 +53,33 @@
 }
 df = pd.DataFrame(data)
 
-# Define colors - Python Blue and Yellow, plus a complementary color
-colors = ["#306998", "#FFD43B", "#4B8BBE"]
+# Ensure categorical order matches Okabe-Ito palette order
+df["Product"] = pd.Categorical(df["Product"], categories=["Software", "Hardware", "Services"], ordered=True)
+
+# Theme-adaptive chrome
+anyplot_theme = theme(
+    plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+    panel_background=element_rect(fill=PAGE_BG),
+    panel_grid_major=element_line(color=INK_SOFT, size=0.3, alpha=0.10),
+    panel_border=element_rect(color=INK_SOFT, fill=None),
+    axis_title=element_text(size=20, color=INK),
+    axis_text=element_text(size=16, color=INK_SOFT),
+    axis_line=element_line(color=INK_SOFT),
+    plot_title=element_text(size=24, color=INK),
+    legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT),
+    legend_text=element_text(size=16, color=INK_SOFT),
+    legend_title=element_text(size=18, color=INK),
+    figure_size=(16, 9),
+)
 
-# Create grouped bar chart
+# Plot
 plot = (
     ggplot(df, aes(x="Quarter", y="Revenue", fill="Product"))
     + geom_bar(stat="identity", position=position_dodge(width=0.8), width=0.7)
-    + scale_fill_manual(values=colors)
-    + labs(x="Quarter", y="Revenue ($ millions)", title="bar-grouped · plotnine · pyplots.ai", fill="Product Line")
-    + 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),
-    )
+    + scale_fill_manual(values=OKABE_ITO)
+    + labs(x="Quarter", y="Revenue ($ millions)", title="bar-grouped · plotnine · anyplot.ai", fill="Product Line")
+    + anyplot_theme
 )
 
 # Save
-plot.save("plot.png", dpi=300)
+ggsave(plot, filename=f"plot-{THEME}.png", dpi=300, width=16, height=9)