feat(plotnine): implement scatter-pitch-events (#5096)

## Implementation: `scatter-pitch-events` - plotnine

Implements the **plotnine** version of `scatter-pitch-events`.

**File:** `plots/scatter-pitch-events/implementations/plotnine.py`

**Parent Issue:** #4417

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/23342848892)*

---------

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>

Author: github-actions[bot]

plots/scatter-pitch-events/implementations/plotnine.py

@@ -0,0 +1,226 @@
+""" pyplots.ai
+scatter-pitch-events: Soccer Pitch Event Map
+Library: plotnine 0.15.3 | Python 3.14.3
+Quality: 90/100 | Created: 2026-03-20
+"""
+
+import numpy as np
+import pandas as pd
+from plotnine import (
+    aes,
+    annotate,
+    arrow,
+    coord_fixed,
+    element_blank,
+    element_rect,
+    element_text,
+    geom_path,
+    geom_point,
+    geom_segment,
+    ggplot,
+    guide_legend,
+    guides,
+    labs,
+    scale_alpha_manual,
+    scale_color_manual,
+    scale_shape_manual,
+    scale_x_continuous,
+    scale_y_continuous,
+    theme,
+)
+
+
+# Data
+np.random.seed(42)
+
+n_events = 120
+event_types = np.random.choice(["Pass", "Shot", "Tackle", "Interception"], size=n_events, p=[0.50, 0.15, 0.20, 0.15])
+
+# Vectorized position generation with event-specific distributions
+x_ranges = {"Pass": (10, 95), "Shot": (65, 100), "Tackle": (15, 80), "Interception": (20, 75)}
+y_ranges = {"Pass": (5, 63), "Shot": (15, 53), "Tackle": (5, 63), "Interception": (5, 63)}
+success_p = {"Pass": 0.75, "Shot": 0.30, "Tackle": 0.65, "Interception": 0.70}
+
+x_positions = np.array([np.random.uniform(*x_ranges[e]) for e in event_types])
+y_positions = np.array([np.random.uniform(*y_ranges[e]) for e in event_types])
+outcomes = [np.random.choice(["Successful", "Unsuccessful"], p=[success_p[e], 1 - success_p[e]]) for e in event_types]
+
+# Arrow endpoints: passes forward-biased, shots toward goal, others stay in place
+x_end = x_positions.copy()
+y_end = y_positions.copy()
+for i, evt in enumerate(event_types):
+    if evt == "Pass":
+        dx = np.random.uniform(5, 20) * np.random.choice([-1, 1], p=[0.15, 0.85])
+        dy = np.random.uniform(-12, 12)
+        x_end[i] = np.clip(x_positions[i] + dx, 0, 105)
+        y_end[i] = np.clip(y_positions[i] + dy, 0, 68)
+    elif evt == "Shot":
+        x_end[i] = 105
+        y_end[i] = np.random.uniform(28, 40)
+
+df = pd.DataFrame(
+    {
+        "x": x_positions,
+        "y": y_positions,
+        "x_end": x_end,
+        "y_end": y_end,
+        "event_type": pd.Categorical(event_types, categories=["Pass", "Shot", "Tackle", "Interception"]),
+        "outcome": pd.Categorical(outcomes, categories=["Successful", "Unsuccessful"]),
+    }
+)
+
+# Separate layers for visual hierarchy
+df_shots = df[df["event_type"] == "Shot"].copy()
+df_other = df[df["event_type"] != "Shot"].copy()
+df_pass_arrows = df[df["event_type"] == "Pass"].copy()
+df_shot_arrows = df[df["event_type"] == "Shot"].copy()
+
+# Pitch styling — deep green with cream white lines for a premium look
+pitch_color = "#1a6b30"
+line_color = "#ffffffcc"
+lw = 0.7
+
+# Center circle
+theta = np.linspace(0, 2 * np.pi, 100)
+center_circle = pd.DataFrame({"cx": 52.5 + 9.15 * np.cos(theta), "cy": 34 + 9.15 * np.sin(theta), "grp": 1})
+
+# Penalty arcs
+theta_left = np.linspace(-0.65, 0.65, 50)
+left_arc = pd.DataFrame({"cx": 11 + 9.15 * np.cos(theta_left), "cy": 34 + 9.15 * np.sin(theta_left), "grp": 2})
+theta_right = np.linspace(np.pi - 0.65, np.pi + 0.65, 50)
+right_arc = pd.DataFrame({"cx": 94 + 9.15 * np.cos(theta_right), "cy": 34 + 9.15 * np.sin(theta_right), "grp": 3})
+
+# Corner arcs
+ca_r = 1.0
+corner_arcs = pd.concat(
+    [
+        pd.DataFrame(
+            {
+                "cx": ca_r * np.cos(np.linspace(0, np.pi / 2, 20)),
+                "cy": ca_r * np.sin(np.linspace(0, np.pi / 2, 20)),
+                "grp": 4,
+            }
+        ),
+        pd.DataFrame(
+            {
+                "cx": ca_r * np.cos(np.linspace(np.pi / 2, np.pi, 20)),
+                "cy": 68 + ca_r * np.sin(np.linspace(np.pi / 2, np.pi, 20)),
+                "grp": 5,
+            }
+        ),
+        pd.DataFrame(
+            {
+                "cx": 105 + ca_r * np.cos(np.linspace(-np.pi / 2, 0, 20)),
+                "cy": ca_r * np.sin(np.linspace(-np.pi / 2, 0, 20)),
+                "grp": 6,
+            }
+        ),
+        pd.DataFrame(
+            {
+                "cx": 105 + ca_r * np.cos(np.linspace(np.pi, 3 * np.pi / 2, 20)),
+                "cy": 68 + ca_r * np.sin(np.linspace(np.pi, 3 * np.pi / 2, 20)),
+                "grp": 7,
+            }
+        ),
+    ],
+    ignore_index=True,
+)
+
+all_curves = pd.concat([center_circle, left_arc, right_arc, corner_arcs], ignore_index=True)
+
+# Colorblind-safe palette: blue, red, orange, teal — all perceptually distinct
+event_colors = {"Pass": "#4a90d9", "Shot": "#d94452", "Tackle": "#e8913a", "Interception": "#17a589"}
+event_shapes = {"Pass": "o", "Shot": "*", "Tackle": "^", "Interception": "D"}
+# Plot
+plot = (
+    ggplot(df, aes(x="x", y="y", color="event_type", shape="event_type", alpha="outcome"))
+    # Pitch background — extended to fill canvas edges
+    + annotate("rect", xmin=-5, xmax=110, ymin=-5, ymax=73, fill=pitch_color, color=pitch_color)
+    # Subtle pitch grass stripe effect (lighter bands)
+    + annotate("rect", xmin=0, xmax=105, ymin=0, ymax=68, fill="#1e7535", alpha=0.3, color="none")
+    # Pitch outline
+    + annotate("rect", xmin=0, xmax=105, ymin=0, ymax=68, fill="none", color=line_color, size=lw)
+    # Halfway line
+    + annotate("segment", x=52.5, xend=52.5, y=0, yend=68, color=line_color, size=lw)
+    # Center spot
+    + annotate("point", x=52.5, y=34, color=line_color, size=1.8, shape="o", fill=line_color)
+    # Left penalty area
+    + annotate("rect", xmin=0, xmax=16.5, ymin=13.84, ymax=54.16, fill="none", color=line_color, size=lw)
+    # Right penalty area
+    + annotate("rect", xmin=88.5, xmax=105, ymin=13.84, ymax=54.16, fill="none", color=line_color, size=lw)
+    # Left goal area
+    + annotate("rect", xmin=0, xmax=5.5, ymin=24.84, ymax=43.16, fill="none", color=line_color, size=lw)
+    # Right goal area
+    + annotate("rect", xmin=99.5, xmax=105, ymin=24.84, ymax=43.16, fill="none", color=line_color, size=lw)
+    # Penalty spots
+    + annotate("point", x=11, y=34, color=line_color, size=1.2, shape="o", fill=line_color)
+    + annotate("point", x=94, y=34, color=line_color, size=1.2, shape="o", fill=line_color)
+    # Left goal
+    + annotate("segment", x=-2, xend=-2, y=30.34, yend=37.66, color="#ffffff", size=1.5)
+    + annotate("segment", x=-2, xend=0, y=30.34, yend=30.34, color="#ffffff", size=0.5)
+    + annotate("segment", x=-2, xend=0, y=37.66, yend=37.66, color="#ffffff", size=0.5)
+    # Right goal
+    + annotate("segment", x=107, xend=107, y=30.34, yend=37.66, color="#ffffff", size=1.5)
+    + annotate("segment", x=105, xend=107, y=30.34, yend=30.34, color="#ffffff", size=0.5)
+    + annotate("segment", x=105, xend=107, y=37.66, yend=37.66, color="#ffffff", size=0.5)
+    # Curves: center circle, penalty arcs, corner arcs
+    + geom_path(data=all_curves, mapping=aes(x="cx", y="cy", group="grp"), color=line_color, size=lw, inherit_aes=False)
+    # Pass arrows — thin and subtle to avoid midfield clutter
+    + geom_segment(
+        data=df_pass_arrows,
+        mapping=aes(x="x", y="y", xend="x_end", yend="y_end", alpha="outcome"),
+        color=event_colors["Pass"],
+        size=0.4,
+        arrow=arrow(length=0.10, type="open"),
+        inherit_aes=False,
+    )
+    # Shot arrows — bolder to emphasize attacking intent
+    + geom_segment(
+        data=df_shot_arrows,
+        mapping=aes(x="x", y="y", xend="x_end", yend="y_end", alpha="outcome"),
+        color=event_colors["Shot"],
+        size=0.9,
+        arrow=arrow(length=0.18, type="open"),
+        inherit_aes=False,
+    )
+    # Non-shot markers
+    + geom_point(data=df_other, size=4.5, stroke=0.4)
+    # Shot markers — larger for focal emphasis
+    + geom_point(data=df_shots, size=8, stroke=0.4)
+    # Scales
+    + scale_color_manual(values=event_colors, name="Event Type")
+    + scale_shape_manual(values=event_shapes, name="Event Type")
+    + scale_alpha_manual(values={"Successful": 0.92, "Unsuccessful": 0.40}, name="Outcome")
+    + scale_x_continuous(limits=(-5, 110), breaks=[])
+    + scale_y_continuous(limits=(-5, 73), breaks=[])
+    + coord_fixed(ratio=1)
+    + labs(
+        title="scatter-pitch-events · plotnine · pyplots.ai",
+        subtitle="Match events: 120 actions across passes, shots, tackles & interceptions",
+    )
+    + guides(
+        color=guide_legend(override_aes={"size": 5}),
+        alpha=guide_legend(override_aes={"size": 5, "alpha": [0.92, 0.40]}),
+    )
+    + theme(
+        figure_size=(16, 9),
+        plot_title=element_text(size=24, weight="bold", color="#1a1a1a", margin={"b": 4}),
+        plot_subtitle=element_text(size=16, color="#555555", style="italic", margin={"b": 12}),
+        panel_background=element_rect(fill=pitch_color, color="none"),
+        plot_background=element_rect(fill="#f5f5f0", color="none"),
+        panel_grid_major=element_blank(),
+        panel_grid_minor=element_blank(),
+        axis_title=element_blank(),
+        axis_text=element_blank(),
+        axis_ticks=element_blank(),
+        legend_title=element_text(size=16, weight="bold", color="#2a2a2a"),
+        legend_text=element_text(size=14, color="#3a3a3a"),
+        legend_position="right",
+        legend_background=element_rect(fill="#f5f5f0", color="none"),
+        legend_key=element_rect(fill="#f5f5f0", color="none"),
+        plot_margin=0.02,
+    )
+)
+
+# Save
+plot.save("plot.png", dpi=300, verbose=False)