feat(altair): implement scatter-animated-controls

plots/scatter-animated-controls/implementations/altair.py

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+""" pyplots.ai
+scatter-animated-controls: Animated Scatter Plot with Play Controls
+Library: altair 6.0.0 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-31
+"""
+
+import altair as alt
+import numpy as np
+import pandas as pd
+
+
+# Data: Simulated country development metrics over years
+np.random.seed(42)
+
+# Create 12 countries tracked over 20 years (showing 4 key time points)
+countries = [
+    "Country A",
+    "Country B",
+    "Country C",
+    "Country D",
+    "Country E",
+    "Country F",
+    "Country G",
+    "Country H",
+    "Country I",
+    "Country J",
+    "Country K",
+    "Country L",
+]
+years = [2000, 2007, 2014, 2021]  # Key time points for faceted view
+
+# Base values for each country (GDP per capita in thousands, life expectancy)
+base_gdp = np.array([5, 8, 12, 15, 20, 25, 3, 10, 18, 30, 6, 22])
+base_life = np.array([55, 60, 65, 70, 72, 75, 50, 62, 68, 78, 58, 74])
+population = np.array([50, 80, 120, 45, 200, 30, 150, 90, 60, 25, 180, 40])  # In millions
+
+# Regions for color coding
+regions = [
+    "Region 1",
+    "Region 2",
+    "Region 1",
+    "Region 2",
+    "Region 3",
+    "Region 3",
+    "Region 1",
+    "Region 2",
+    "Region 3",
+    "Region 3",
+    "Region 1",
+    "Region 2",
+]
+
+data = []
+for i, country in enumerate(countries):
+    for j, year in enumerate(years):
+        # Simulate growth over time with some variation
+        growth_factor = 1 + j * 0.15 + np.random.uniform(-0.05, 0.1)
+        life_improvement = j * 2.5 + np.random.uniform(-1, 2)
+
+        gdp = base_gdp[i] * growth_factor
+        life_exp = min(85, base_life[i] + life_improvement)
+        pop = population[i] * (1 + j * 0.02)  # Slight population growth
+
+        data.append(
+            {
+                "Country": country,
+                "Year": year,
+                "GDP per Capita (thousands USD)": round(gdp, 1),
+                "Life Expectancy (years)": round(life_exp, 1),
+                "Population (millions)": round(pop, 1),
+                "Region": regions[i],
+            }
+        )
+
+df = pd.DataFrame(data)
+
+# Color palette
+color_scale = alt.Scale(domain=["Region 1", "Region 2", "Region 3"], range=["#306998", "#FFD43B", "#6B8E23"])
+
+# Create faceted scatter plot showing evolution across key years
+chart = (
+    alt.Chart(df)
+    .mark_circle(opacity=0.8, stroke="#333333", strokeWidth=1)
+    .encode(
+        x=alt.X(
+            "GDP per Capita (thousands USD):Q", title="GDP per Capita (thousands USD)", scale=alt.Scale(domain=[0, 50])
+        ),
+        y=alt.Y("Life Expectancy (years):Q", title="Life Expectancy (years)", scale=alt.Scale(domain=[45, 90])),
+        size=alt.Size(
+            "Population (millions):Q",
+            scale=alt.Scale(range=[100, 2000]),
+            legend=alt.Legend(title="Population (millions)", titleFontSize=16, labelFontSize=14),
+        ),
+        color=alt.Color(
+            "Region:N", scale=color_scale, legend=alt.Legend(title="Region", titleFontSize=16, labelFontSize=14)
+        ),
+        tooltip=[
+            "Country",
+            "Year",
+            "GDP per Capita (thousands USD)",
+            "Life Expectancy (years)",
+            "Population (millions)",
+            "Region",
+        ],
+    )
+    .properties(width=350, height=550)
+    .facet(
+        column=alt.Column(
+            "Year:O", header=alt.Header(title=None, labelFontSize=24, labelFontWeight="bold", labelColor="#333333")
+        )
+    )
+    .properties(
+        title=alt.Title(
+            "scatter-animated-controls · altair · pyplots.ai",
+            fontSize=28,
+            anchor="middle",
+            subtitle="Country Development Metrics Across Key Years (Static Faceted View)",
+            subtitleFontSize=18,
+            subtitleColor="#666666",
+        )
+    )
+    .configure_axis(labelFontSize=14, titleFontSize=18, gridColor="#E0E0E0", gridOpacity=0.5)
+    .configure_view(strokeWidth=0)
+    .configure_legend(orient="right", padding=20)
+)
+
+# Save outputs
+chart.save("plot.png", scale_factor=3.0)
+chart.save("plot.html")

plots/scatter-animated-controls/metadata/altair.yaml

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+library: altair
+specification_id: scatter-animated-controls
+created: '2025-12-31T13:51:00Z'
+updated: '2025-12-31T13:54:38Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20620303747
+issue: 3067
+python_version: 3.13.11
+library_version: 6.0.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-animated-controls/altair/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/scatter-animated-controls/altair/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-animated-controls/altair/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent adaptation of animated concept to static faceted view, following spec
+    guidance for libraries without animation
+  - Clean Gapminder-inspired data with realistic development metrics across multiple
+    decades
+  - Good use of Altair declarative grammar with proper encoding types (Q, N, O)
+  - Effective use of size encoding for population and color for regions
+  - Proper scale domains ensure consistent axes across all facets for easy comparison
+  weaknesses:
+  - Year labels at top of facets could be slightly larger for emphasis
+  - Legend placement creates slight right-margin crowding; could benefit from more
+    padding
+  - Missing interactive() call for HTML output which would enable zoom/pan exploration