feat(plotly): implement scatter-animated-controls

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

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+""" pyplots.ai
+scatter-animated-controls: Animated Scatter Plot with Play Controls
+Library: plotly 6.5.0 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-31
+"""
+
+import numpy as np
+import pandas as pd
+import plotly.express as px
+
+
+# Data: Simulated country data (GDP, life expectancy, population) over 20 years
+np.random.seed(42)
+
+countries = ["Alpha", "Beta", "Gamma", "Delta", "Epsilon", "Zeta", "Eta", "Theta"]
+regions = ["North", "North", "South", "South", "East", "East", "West", "West"]
+years = list(range(2000, 2021))
+
+# Base values for each country
+base_gdp = np.array([8000, 12000, 3000, 5000, 15000, 7000, 4000, 20000])
+base_life_exp = np.array([65, 72, 58, 62, 75, 68, 60, 78])
+base_pop = np.array([50, 30, 120, 80, 25, 45, 90, 20])
+
+# Build dataset with growth trends
+data = []
+for i, country in enumerate(countries):
+    for year_idx, year in enumerate(years):
+        # GDP growth with some variation (1-5% annual growth)
+        growth_factor = 1 + np.random.uniform(0.01, 0.05)
+        gdp = base_gdp[i] * (growth_factor**year_idx) + np.random.normal(0, 500)
+        gdp = max(1000, gdp)
+
+        # Life expectancy slowly increases (0.1-0.3 years per year)
+        life_exp = base_life_exp[i] + year_idx * np.random.uniform(0.1, 0.3) + np.random.normal(0, 0.5)
+        life_exp = min(max(50, life_exp), 85)
+
+        # Population changes (0.5-2% annual change)
+        pop_factor = 1 + np.random.uniform(0.005, 0.02)
+        pop = base_pop[i] * (pop_factor**year_idx) + np.random.normal(0, 2)
+        pop = max(10, pop)
+
+        data.append(
+            {
+                "Country": country,
+                "Region": regions[i],
+                "Year": year,
+                "GDP per Capita ($)": gdp,
+                "Life Expectancy (years)": life_exp,
+                "Population (millions)": pop,
+            }
+        )
+
+df = pd.DataFrame(data)
+
+# Create animated scatter plot with Gapminder-style visualization
+fig = px.scatter(
+    df,
+    x="GDP per Capita ($)",
+    y="Life Expectancy (years)",
+    size="Population (millions)",
+    color="Region",
+    hover_name="Country",
+    animation_frame="Year",
+    animation_group="Country",
+    size_max=80,
+    range_x=[0, df["GDP per Capita ($)"].max() * 1.1],
+    range_y=[50, 88],
+    color_discrete_sequence=["#306998", "#FFD43B", "#E74C3C", "#2ECC71"],
+)
+
+# Update layout for large canvas
+fig.update_layout(
+    title=dict(
+        text="scatter-animated-controls · plotly · pyplots.ai",
+        font=dict(size=32, color="#333333"),
+        x=0.5,
+        xanchor="center",
+    ),
+    xaxis=dict(
+        title=dict(text="GDP per Capita ($)", font=dict(size=24)),
+        tickfont=dict(size=18),
+        gridcolor="rgba(0,0,0,0.1)",
+        showgrid=True,
+    ),
+    yaxis=dict(
+        title=dict(text="Life Expectancy (years)", font=dict(size=24)),
+        tickfont=dict(size=18),
+        gridcolor="rgba(0,0,0,0.1)",
+        showgrid=True,
+    ),
+    legend=dict(
+        title=dict(text="Region", font=dict(size=20)),
+        font=dict(size=18),
+        x=0.02,
+        y=0.98,
+        bgcolor="rgba(255,255,255,0.8)",
+    ),
+    template="plotly_white",
+    paper_bgcolor="white",
+    plot_bgcolor="white",
+    margin=dict(l=100, r=100, t=120, b=150),
+)
+
+# Update marker styling
+fig.update_traces(marker=dict(line=dict(width=2, color="white"), opacity=0.85))
+
+# Update animation settings for smooth playback
+fig.update_layout(
+    updatemenus=[
+        dict(
+            type="buttons",
+            showactive=False,
+            y=-0.08,
+            x=0.05,
+            xanchor="left",
+            buttons=[
+                dict(
+                    label="▶ Play",
+                    method="animate",
+                    args=[
+                        None,
+                        dict(
+                            frame=dict(duration=500, redraw=True),
+                            fromcurrent=True,
+                            transition=dict(duration=300, easing="cubic-in-out"),
+                        ),
+                    ],
+                ),
+                dict(
+                    label="⏸ Pause",
+                    method="animate",
+                    args=[
+                        [None],
+                        dict(frame=dict(duration=0, redraw=False), mode="immediate", transition=dict(duration=0)),
+                    ],
+                ),
+            ],
+            font=dict(size=16),
+        )
+    ],
+    sliders=[
+        dict(
+            active=0,
+            yanchor="top",
+            xanchor="left",
+            currentvalue=dict(font=dict(size=24), prefix="Year: ", visible=True, xanchor="center"),
+            transition=dict(duration=300, easing="cubic-in-out"),
+            pad=dict(b=10, t=50),
+            len=0.85,
+            x=0.1,
+            y=-0.02,
+            steps=[
+                dict(
+                    args=[
+                        [str(year)],
+                        dict(frame=dict(duration=300, redraw=True), mode="immediate", transition=dict(duration=300)),
+                    ],
+                    label=str(year),
+                    method="animate",
+                )
+                for year in years
+            ],
+            font=dict(size=14),
+        )
+    ],
+)
+
+# Add year annotation in background for emphasis
+fig.add_annotation(
+    x=0.98,
+    y=0.95,
+    xref="paper",
+    yref="paper",
+    text="2000",
+    showarrow=False,
+    font=dict(size=72, color="rgba(0,0,0,0.08)"),
+    xanchor="right",
+    yanchor="top",
+)
+
+# Save static PNG (showing first frame)
+fig.write_image("plot.png", width=1600, height=900, scale=3)
+
+# Save interactive HTML
+fig.write_html("plot.html", include_plotlyjs=True, full_html=True)

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

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+library: plotly
+specification_id: scatter-animated-controls
+created: '2025-12-31T13:51:22Z'
+updated: '2025-12-31T13:54:25Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20620300949
+issue: 3067
+python_version: 3.13.11
+library_version: 6.5.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-animated-controls/plotly/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/scatter-animated-controls/plotly/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-animated-controls/plotly/plot.html
+quality_score: 92
+review:
+  strengths:
+  - 'Excellent Gapminder-style visualization with all key elements: play/pause controls,
+    timeline slider, year watermark'
+  - Clean code structure with realistic simulated country data showing growth over
+    20 years
+  - Proper use of Plotly animation features including smooth transitions (cubic-in-out
+    easing)
+  - Good accessibility with distinct colors and proper font sizing throughout
+  - Both PNG and HTML outputs generated for static and interactive viewing
+  weaknesses:
+  - Some bubble overlap in the lower-left cluster makes individual countries harder
+    to distinguish in year 2000
+  - Legend positioned inside the plot area could potentially overlap with data points
+    in some frames
+  - Year watermark annotation shows static 2000 and does not update with animation
+    frames