feat(letsplot): implement bar-race-animated

plots/bar-race-animated/implementations/python/letsplot.py

@@ -1,50 +1,63 @@
-""" pyplots.ai
+""" anyplot.ai
 bar-race-animated: Animated Bar Chart Race
-Library: letsplot 4.8.2 | Python 3.13.11
-Quality: 91/100 | Created: 2026-01-11
+Library: letsplot 4.9.0 | Python 3.13.13
+Quality: 86/100 | Updated: 2026-05-19
 """
 
+import os
+
 import numpy as np
 import pandas as pd
 from lets_plot import *
 
 
 LetsPlot.setup_html()
 
-# Data: Simulated streaming platform subscriber counts (millions) over 8 years
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2", "#CC79A7", "#E69F00", "#56B4E9"]
+
 np.random.seed(42)
 
 platforms = ["StreamMax", "ViewHub", "FlixNet", "WatchNow", "CineCloud", "MediaFlow"]
 years = list(range(2016, 2024))
-colors = ["#306998", "#FFD43B", "#DC2626", "#059669", "#7C3AED", "#EA580C"]
 
-# Generate realistic growth patterns for each platform
-data_rows = []
-base_values = [50, 80, 120, 30, 20, 40]  # Starting subscribers in millions
-growth_rates = [1.35, 1.15, 1.08, 1.45, 1.55, 1.25]  # Annual growth multipliers
+# Plausible growth: FlixNet dominates early, WatchNow/CineCloud surge to overtake
+base_values = [60, 100, 155, 28, 18, 65]
+growth_rates = [1.16, 1.08, 1.03, 1.26, 1.30, 1.10]
 
+data_rows = []
 for i, platform in enumerate(platforms):
     value = base_values[i]
     for year in years:
-        # Add some randomness to growth
         noise = np.random.uniform(0.9, 1.1)
         value = value * growth_rates[i] * noise
         data_rows.append({"platform": platform, "year": year, "subscribers": round(value, 1)})
 
 df = pd.DataFrame(data_rows)
 
-# Select 4 key time snapshots for the small multiples grid
+platform_colors = dict(zip(platforms, OKABE_ITO))
 snapshot_years = [2016, 2018, 2021, 2023]
 
-# Assign consistent colors to each platform (dictionary for named mapping)
-platform_colors = dict(zip(platforms, colors))
+anyplot_theme = theme(
+    plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+    panel_background=element_rect(fill=PAGE_BG),
+    panel_grid_major=element_blank(),
+    panel_grid_minor=element_blank(),
+    axis_title=element_text(color=INK),
+    axis_text=element_text(color=INK_SOFT),
+    axis_line=element_line(color=INK_SOFT),
+    plot_title=element_text(color=INK),
+    legend_position="none",
+)
 
-# Build individual plots for each snapshot year
 plots = []
 for year in snapshot_years:
     year_data = df[df["year"] == year].copy()
     year_data = year_data.sort_values("subscribers", ascending=True)
-    # Create ordered factor for proper bar ordering (sorted by value)
     year_data["platform"] = pd.Categorical(
         year_data["platform"], categories=year_data["platform"].tolist(), ordered=True
     )
@@ -56,29 +69,26 @@
         + scale_fill_manual(values=platform_colors)
         + labs(title=str(year), x="", y="Subscribers (millions)")
         + theme_minimal()
+        + anyplot_theme
         + theme(
-            plot_title=element_text(size=28, face="bold"),
-            axis_title_x=element_text(size=18),
+            plot_title=element_text(size=28, face="bold", color=INK),
+            axis_title_x=element_text(size=18, color=INK),
             axis_title_y=element_blank(),
-            axis_text_x=element_text(size=16),
-            axis_text_y=element_text(size=18),
-            legend_position="none",
-            panel_grid_major_y=element_blank(),
-            panel_grid_minor=element_blank(),
+            axis_text_x=element_text(size=16, color=INK_SOFT),
+            axis_text_y=element_text(size=18, color=INK_SOFT),
         )
     )
     plots.append(plot)
 
-# Use gggrid for 2x2 layout with overall title
 grid = (
     gggrid(plots, ncol=2)
-    + labs(title="bar-race-animated · letsplot · pyplots.ai")
-    + theme(plot_title=element_text(size=32, face="bold", hjust=0.5))
+    + labs(title="bar-race-animated · python · letsplot · anyplot.ai")
+    + theme(
+        plot_title=element_text(size=32, face="bold", hjust=0.5, color=INK),
+        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+    )
     + ggsize(1600, 900)
 )
 
-# Save as PNG (scale=3 for 4800x2700 px output)
-ggsave(grid, "plot.png", path=".", scale=3)
-
-# Save interactive HTML version
-ggsave(grid, "plot.html", path=".")
+ggsave(grid, f"plot-{THEME}.png", path=".", scale=3)
+ggsave(grid, f"plot-{THEME}.html", path=".")