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feat(altair): implement scatter-animated-controls (#3081)
## Implementation: `scatter-animated-controls` - altair Implements the **altair** version of `scatter-animated-controls`. **File:** `plots/scatter-animated-controls/implementations/altair.py` **Parent Issue:** #3067 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20620303747)* --------- 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>
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‎plots/scatter-animated-controls/implementations/altair.py‎

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

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

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

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